{"input": "services or informal networks. The focus group discussions also underscored the precarious financial situation of many refugees, including those engaging in low-paid work below their qualifications, which creates a barrier for relocations to rented housing. 78% of respondents mentioned that they would not be able to cover costs of rented housing higher than CZK 5,000 (approximately USD 213) a month, which is well below market price. In addition to the individual factors affecting relocations to standard housing, key informant interviews and consultations with NGOs, representatives of local and regional governments, and experts in social housing outlined a number of structural factors impacting relocations. These include the need to clarify and strengthen institutional roles and responsibilities in relation to refugee assistance, the need to provide clear, understandable, and timely information on the upcoming housing changes, and the need to ensure unimpeded access of residents to social services and counselling. Furthermore, findings suggest that the current situation and oversaturation of the rental market in bigger cities should not be disregarded. Coordinated support _1 UNHCR-IOM: NEW BEGINNINGS: SUPPORTING THE DIGNIFIED RELOCATION OF UKRAINIAN TEMPORARY PROTECTION_ _HOLDERS TO STANDARD HOUSING. Report on the Relocation of Ukrainian Temporary Protection Holders from Collective_ _Accommodation Facilities to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "but concentrated in high-risk areas such as the coast or river basins. In this section we present flood exposure estimated disaggregated to subnational regions, the number of which can vary across countries. World Bank household surveys are sampled to be statistically representative at different subnational levels – in this study we adopt these statistically representative subnational units which enable us to compare flood exposure estimates with socio-economic characteristics, such as income levels and poverty (Section 3.4). The disaggregation of exposure estimates highlights several subnational regions with high risks (Figure 9). Punjab, Pakistan, with a population of 120 million people, frequently experiences heavy flooding and ranks highest in terms of the absolute population headcount exposed to significant flood risk; approximately 48 million people are exposed, which is 38% of the total population. Several of the populous regions in China and India are also among the world’s subnational regions with the highest number of people exposed to flood risk. In China for instance, high population exposure tends to be close to the coast and around the Yellow River valley. However, the sub-national region with the highest population exposure in China is Guangdong in the southeast, on the South China Sea, where 43", "output": {"entities": {"named_data": [{"text": "World Bank household surveys"}], "descriptive_data": [{"text": "World Bank household surveys"}], "vague_data": []}}}
{"input": "in Zambia, driven largely by the rapid growth in mining activities, which has seen the population of the district more than double in 10 years—from around 85,000 at the time of the 2010 census to 180,000 in the 2022 census. [23] The population of Meheba, which is predominantly youthful (75.9 percent ages below 35 years), embodies the potential of a highly productive age group looking for opportunities and livelihoods. [24] The settlement’s boundaries intersect with three adjoining wards of Kalumbila District— Shilenda, Mwajimambwe, and Matebo—that have a combined population of 61,000. [25] 33. **Infrastructure provision at the Meheba settlement and within the local community will enhance productivity** **and quality of life.** It is anticipated that the improvement of rural access road infrastructure will increase both mobility and trade to and from the settlement for refugees and host communities. Current electrical supply is poor, with households relying mostly on kerosene lanterns, candles, flashlights, and generators for lighting and cell phone charging. Enhanced transport and energy will also stimulate retail business and production. The upgrading and expansion of school infrastructure will improve learning outcomes, enhance teacher retention and new recruitment, and afford greater dignity to boarding pupils, especially girls, as many are", "output": {"entities": {"named_data": [{"text": "the 2010 census"}, {"text": "the 2022 census"}], "descriptive_data": [], "vague_data": []}}}
{"input": "_Note:_ Figure 5 shows the main treatment coefficients ( _active*mine_ ) using the baseline estimation strategy (with DHS individual-level data; see table 4 for more information) in the top panel, but with different cutoffs (10 km, 20 km, 30 km, 40 km, and 50 km). *** p<0.01, **p<0.05, *p<0.1. The bottom panel shows the result using a spatial lag model that divided the plane into different treatment bins (0–10, 10–20, 20–30, 40–50) and compares them with farther away. Panel A shows the result for nonmigrants, and panel B shows the result for migrants. **6.2 Access to infrastructure and health care** Another source of heterogeneity is asset ownership and access to infrastructure. Table 8 shows that fewer households have electricity in active mining communities, but they spend less time fetching water and are more likely to own a radio (all estimates are statistically insignificant, however). There is no change in the likelihood of having a flush toilet. Moreover, it seems that households are just as likely to have access to a pit toilet as not having a toilet (and instead use a bucket, bush, and so forth). **Table 8 OLS estimates for ownership of assets and access to infrastructure** water access", "output": {"entities": {"named_data": [{"text": "DHS individual-level data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "access to health care, and are less likely to accept domestic violence. In addition, infant mortality rates decrease with up to 50% in mining communities, from very high initial levels (Benshaul-Tolonen, 2019). In a study that focuses exclusively on Ghana, Aragón and Rud (2013) explore the link between pollution from mining and agricultural productivity. The results point toward decreasing agricultural productivity because of environmental pollution and soil degradation, which could have negative welfare effects on households that do not engage in mining activities or in indirectly stimulated sectors. Lower productivity in agriculture could potentially push households to engage in mining-related sectors, in addition to pull factors such as higher wage earnings in the stimulated sectors. We explore the effects of mining activity on employment, earnings, expenditure, and children’s health outcomes in local communities and in districts with gold mining. We combine the DHS and GLSS with production data for 17 large-scale gold mines in Ghana. We find that a new large-scale gold mine changes economic outcomes, such as access to employment and cash earnings. In addition, it raises local wages and expenditure on housing and energy. An important welfare indicator in developing countries is infant mortality, and we note a", "output": {"entities": {"named_data": [{"text": "DHS and GLSS"}, {"text": "GLSS"}], "descriptive_data": [{"text": "production data for 17 large-scale gold mines"}], "vague_data": []}}}
{"input": "that the fact that M is chosen ex post (i.e., the country cannot commit not to borrow from the facility in period 1) simplifies the problem, which now boils down to the choice of period 0 borrowing, D0. Also note that, under the assumption that multilateral and private lending command the same interest rate, the actual composition of period 1 lending is immaterial for the current analysis. Then, without loss of generality, we can set D1 = 0. In the non default case, expected income can be expressed as - E(Y ) = x + (ρ 1) D0 [nd] π D0 [nd] (1 β) . (24) - - - However, the country can also borrow beyond the limit imposed by (23) and, after a shock, withdraw from the facility and default on the bond. In this case, expected income is given by - E(Y ) = (1 πγ) x + (ρ 1) D0 [d] + π (1 γ) (1 β) (25) - - - As before, the equilibrium can be characterized by income levels. In the case of rich countries (x > x [B] 1 [)] 16 The CAT DDO is a new financial product offered to middle-income country governments", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The sample is restricted to individuals living within 100 km of a deposit location ( _mine_ ), so many parts of Northern Ghana where there are few gold mines are not included in the analysis. The sample restriction is created by using the time-stable continuous distance measure that we calculate from each mine location to each DHS cluster. This is also the distance measure that we use to create the “mine” dummy, which captures whether the cluster lies within 20 km of a known gold deposit. Note that we only consider deposits that have been in production at some point until December 2012. All households are thus within 100 km of one, or several, gold deposits. To ascertain whether there is any gold production in these potential mining sites, we construct an indicator variable _active_, which takes a value of 1 if there is at least one mine within 100 km that was extracting gold in the year the household was surveyed, and 0 otherwise. While the _mine_ dummy captures some of the special characteristics of mining areas (for example, whether mines tend to open in less urban areas), the _active_ dummy captures long-range spillovers of mining. The treatment effect", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "28 This morbidity assumption is based on proxy data used in other countries in Sub-Saharan Africa for refugee camps and host communities (e.g., Somalia, Zimbabwe, South Sudan, Kenya). 29 Kip Viscusi, W., and Clayton J. Masterman. “Income Elasticities and Global Values of a Statistical Life.” [https://law.vanderbilt.edu/phd/faculty/w-kip-viscusi/355_Income_Elasticities_and_Global_VSL.pdf](https://law.vanderbilt.edu/phd/faculty/w-kip-viscusi/355_Income_Elasticities_and_Global_VSL.pdf) 30 O&M costs for infrastructure vary widely. These costs include water treatment, road resurfacing, building maintenance, cleaning, energy and staff costs. As such, the analysis uses a conservative assumption of five percent of the investment costs for annual O&M. Page 17", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "proxy data"}], "vague_data": []}}}
{"input": "we are back in the benchmark case.] [To ensure that] no default occurs, it is suffi cient to show that π(1 β)(1 γ) x ~~[I]~~ 3 [N] x ~~[B]~~ 4 [=] - γ (γρ (1 π) + πγ π γ) [>][ 0] - - which is always the case for suffi ciently small values of π. 7.3 Catastrophe lending facility As before, for high initial incomes (x x [M] 1 = [1][−][γ][(] γ [ρ][−][β][)] ≥ γ ), the borrowing constraint (22) does not bind and the country invests the optimum in both states. In turn, for x < x [M] 1 [,] [from] [(23)] D0 [nd] = [γ] 1 [ (] - [x][ + 1] γ (ρ [ −] - [β] 1) [)] [≤] [1][,] and M = D0 [nd] - (1 − β) = [γx][ −] 1 [(1][ −] γ ( [γρ] ρ [) (1] 1) [ −] [β][)] 1 [(1][ −] γ ( [γρ] ρ [) (1] 1) [ −] [β][)] - 0 ⇐⇒ x > x [M] 4 [≡] [(1][ −] [γρ] γ [) (1][ −] [β][)] - = x [IN] 3 [,] (47) γ Alternatively, a financially constrained country may choose to increase borrowing from private", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "contractors, including adherence to working hours, pay and legally mandated benefits, equal and fair recruitment, and employment, are also probable. To address these concerns, a Labor Management Procedures (LMP) document has been incorporated into the project’s ESMF, which is due by effectiveness. The LMP provides guidance on managing labor-related risks. The final ESMF will be disclosed on the MINEMA and World Bank websites. 85. **Community Health and Safety (ESS4).** Construction can generate risks to the community, including exposure to dust, noise, hazardous construction waste, and traffic-related incidents. These risks will be evaluated during the preparation of the ESMF, drawing on lessons from Phase I. Mitigation measures will be integrated into site-specific Environmental and Social Management Plans (ESMPs). The government will be required to adhere to community health and safety standards outlined in the World Bank Environmental, Health, and Safety (EHS) guidelines, as well as incident reporting and management procedures in the event of accidents or incidents. Measures to address the risks of GBV, SEA and Sexual Harassment (SH) will also be implemented to ensure community safety. 86. **Land Acquisition, Restrictions on Land Use, and Involuntary Resettlement (ESS5).** Component one activities are expected to result in land acquisition, restrictions on land", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**African migration to Israel** According to UNHCR, the Middle East and North Africa host a fifth of the world's refugees, excluding the considerable and growing population of Palestinian refugees. [5] Syria and Lebanon, Israel's northern neighbours, host a significant number. Syria is the third largest refugee hosting country in the world with, according to government figures, more than a million Iraqi refugees, while Lebanon hosts 50,000 refugees. To 3 A parliamentary inquiry found that between 2001-2005, an annual number of 1,000 women were trafficked through the border for prostitution (Lutski, 2005). Comprehensive enforcement has since significantly reduced the scale of women trafficked into Israel 4 It is reported that in the case of some Eritreans, initial payment was made already in Eritrea (Interview with a senior UNHCR official). 5Article 1D of the 1951 Convention exclude persons who receive assistance from other UN bodies. It intentionally excludes the Palestinians who were displaced as a result of the 1948 war, and were under the auspices of the United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), an agency which was established prior to UNHCR. Palestinian refugees and their descendants are now estimated at 4.7 million (UNRWA 2009).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "World Bank online screening tool, the GBV/SEA/SH risk was determined as high. Civil works will attract workers and pose SEA/SH risks. weak reporting of these cases is a challenge across most communities. LIPW activities will involve women working and receiving cash under component 2. If partners are not well trained and agree on how to spend their income, it would lead to intimate partner violence. To mitigate this risk, a GBV Action plan will be prepared, a Gender Specialist hired to support implementation, and a service provider engaged to support the coordination and implementation of the GBV Action Plan. Page 24", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "choice is influenced by climate (Mendelsohn & Dinar 2003). Further, there may be sample selection bias if we rely on farms that are observed to use dryland or irrigation. In this paper, we develop a new Ricardian model that examines dryland and irrigated land separately but treats the choice of irrigation as endogenous. A variety of factors influence the decision on whether to irrigate. Surface flows, soil types, and subsidies all play a role in making this choice. But perhaps more importantly to climate analyses, the choice is sensitive to climate. Studies that assume irrigation is exogenous fail to take into account how irrigation will change as climate changes and therefore provide biased estimates of the impact of climate change. Moreover, these analyses of only irrigated farms and only dryland farms rely on self-selected samples, not random samples. Studies that fail to account for this nonrandomness in the modeling framework will be biased (Heckman 1979; Lee 1983). In Section 2 we develop a theoretical model that improves on past efforts to model irrigation with the Ricardian approach by explicitly addressing farmer choice and selection bias. We tested this model empirically using a sample of over 8400 farmers from across 11", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "72. **Gender.** The project is aligned the with Gender strategy 2024-2030 and specifically responds to two priority areas of the strategy (i) expand and enable economic opportunities and (ii) advances in women’s participation in decision making [48] _._ Under Component 3, the project will directly increase the participation of women in economic opportunities and better enable their ownership and control of productive assets by providing technical and financial support to farmers and cooperatives owned or led by these segments. Beneficiary selection criteria and formulas will contain preferences in favor of these groups through a quota. The project will specifically address the gender gap with respect to access to financing and access to market-oriented skills as well as personal initiative training. [49] Tailored marketing campaigns will also help attract more female participation and dedicated trainings, mentoring support, and business management tools for women and other target groups will be featured. The component will measure the portion of female beneficiaries increasing income as a result of project livelihood interventions. The project will also reach women and girls at the community level through enhanced infrastructure and health and education services provision. For example, improved road infrastructure in the Meheba settlement will enhance ambulance", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "we have constructed the cyclone database to support research on household- and community-level adaptation to cyclone risks. These risks may affect coastal population dynamics in at least two ways. In the long run, the number and size of coastal communities may be affected by the long-run frequency and power of cyclone strikes. Other things equal, we would expect areas that have been largely cyclone-free for many years to be more populous than frequently-impacted areas. Shorter-term, if impact-intensive zones shift over time, 8", "output": {"entities": {"named_data": [{"text": "the cyclone database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Socio-economic Inclusion of Refugees & Host Communities in Rwanda Project Phase II (P509677) **C. Disbursement Arrangements** 56. **To manage the World Bank funding, the project will maintain segregated Designated Accounts (DA) for** **each implementing agency (IA) at the Central Bank, denominated in US dollars.** In addition, BRD will open an operational account denominated in Rwandan Francs to facilitate local currency transactions. Disbursements will follow the Interim Financial Report (IFR)-based method. The project may also use direct payments, reimbursements and special commitments, depending on the case. The project is fully funded by IDA with no counterpart funding. The signatories of the DA will be communicated to the World Bank by MINECOFIN. Upon effectiveness, the project will submit to the World Bank a request for withdrawal of funds based on six months cash forecast. Detailed arrangements for disbursement are laid out in the Disbursement and Financial Information Letter (DFIL). Based on requests, the World Bank will transfer advances to the DAs. Subsequent replenishment of the DA will be based on the submission of application of withdrawal, accompanied by quarterly IFRs, which are reviewed and cleared by the World Bank. 57. **For activities implemented at the district level, MINEMA will", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "fastgini [15] in STATA). We do this for both the cluster and district level. None of the effects of mining are statistically significant, but they point to increased asset wealth. **Table 9 OLS estimates for wealth and inequality in the DHS individual-level analysis** Wealth Gini wealth cluster district index level level active*mine 7,290 -0.004 0.004 (12,849) (0.013) (0.018) mine 9,922 0.011 0.006 (8,676) (0.013) (0.016) active 7,854 -0.006 0.034** (9,016) (0.010) (0.017) Observations 4,909 4,909 4,909 R-squared 0.613 0.227 0.548 _Note:_ Robust standard errors clustered at the DHS cluster level in parentheses. All regressions control for year and district fixed effects, urban dummy, age, and years of education. Active is active status of mine in the survey year. *** p<0.01, **p<0.05, *p<0.1. OLS = ordinary least squares. **6.4 Bottom 40% of the population** To understand the welfare effects of the bottom 40 percent of the population in the income scale, we split the sample according to the wealth score provided by DHS. Given the data structure, which is repeated cross-section, we cannot follow a particular household that was identified as belonging to the bottom 40 percent in the initial time period. Instead, we identify the bottom 40 percent in four", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Table 7: Land values and rental price by ownership status and region** **Region** **Tenure** Total Central Eastern Northern Western _Mailo_ / Customary Freehold **Parcels held under ownership** Self-assessed land value (USD/acre; median) 403.2 430.1 430.1 161.3 536.6 537.6 358.4 Self-assessed land rental (USD/acre; median) 21.5 26.9 21.5 16.1 26.9 26.9 21.5 Number of parcels 8619 1440 2522 2026 2631 1784 6835 **Parcels held under usufruct** Would like to buy full ownership (%) 37.3 42.1 41.0 18.1 45.3 42.5 34.7 If yes, willingness to pay (USD/acre; median) 215.1 215.1 215.1 107.5 322.6 268.8 215.1 Paid rent (%parcels with owner’s consent) 62.1 44.7 68.1 54.6 72.4 52.0 65.4 If yes, rent paid (USD/acre; median) 16.1 17.9 16.1 10.8 21.5 19.1 16.1 Number of parcels 4478 1219 1320 967 972 1519 2959 _Source:_ Own computation from 2005/06 UNHS III 23", "output": {"entities": {"named_data": [{"text": "2005/06 UNHS III"}], "descriptive_data": [], "vague_data": []}}}
{"input": "safety nets were key recommendations from the Climate Change Development Report (2024) for Djibouti. 3. **Low human capital further constrains economic and climate resilience and limits opportunities for inclusive** **growth.** Djibouti’s LMIC status contrasts sharply with its poor human capital outcomes (World Bank, HCR, 2024). Deficiencies are evident throughout the lifecycle, starting with high rates of infant mortality and stunting. In later years, inadequate learning outcomes and skills, a lack of workforce-relevant skills, and low labor force participation – especially among women – present significant barriers to economic productivity. Additionally, poor health outcomes for women, including high rates of female genital mutilation and maternal health challenges, further impede human capital accumulation. Private sector surveys highlight a critical mismatch between labor market demands and the available skills. Women face even greater challenges due to entrenched social norms and structural barriers to self-employment and entrepreneurship, as reflected in Djibouti’s low ranking on the Women, Business, and the Law Index (World Bank 2022a). 4. **Djibouti’s vulnerability to climate-related disasters exacerbates these economic and social challenges.** The country frequently experiences heatwaves, droughts and floods, which take a heavy toll on the population by reducing productivity and disrupting economic activity. Between 1980 and 2019, Djibouti", "output": {"entities": {"named_data": [{"text": "Women, Business, and the Law Index"}], "descriptive_data": [], "vague_data": [{"text": "Private sector surveys"}]}}}
{"input": "services are vital to ensure decent living conditions for some 120,000 people and peaceful coexistence with host communities. **Basic Needs and Livelihoods** With the growing refugee population in Morocco and limited resources, a growing number of refugees are in desperate need of assistance to meet their basic needs. Without additional funding, basic assistance for some 1,600 families will be reduced. Support to promote income-generating activities, vocational training and job placements will also be compromised, further increasing the number of refugees relying on cash assistance to cover their basic needs. **Education** Education assistance to some 1,200 refugee children registered in Moroccan public schools, which plays a key role in reducing school dropouts and negative coping mechanisms such as child labour and/or marriage, will also be compromised. **Health** Pending the inclusion of refugees in the ongoing social protection reform, UNHCR remains a main stakeholder supporting refugees’ access to secondary and tertiary healthcare. Lack of funding will impact UNHCR’s capacity to pay for critically needed medication and lifesaving specialized medical interventions for more than 500 vulnerable refugees. [www.unhcr.org](https://www.unhcr.org/) 5", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "85. **Inclusion and non-discrimination.** E&S documents include specific measures to mitigate the risk of discrimination against or exclusion of any affected individuals or groups in providing or receiving benefits under the project. These measures are described in detail in the Environmental and Social Commitment Plan (ESCP), ESA, and Stakeholder Engagement Plan (SEP). The following are examples of the mitigation measures included in all the aforementioned documents: (a) strengthening the capacity of the PIST, workers, contractors, subcontractors, and service providers, which will include worker training and sensitization on the obligations of project participants to ensure non-discrimination of vulnerable and marginalized individuals or groups; (b) ensuring that contracts, codes of conduct, hiring procedures, whistle-blower protection protocols, and other measures, as needed, are in place to allow remediation of cases of discrimination; (c) designing and implementing a mechanism to receive and report grievances to the World Bank, proposing appropriate remediation, and following up on agreed actions to resolve cases of discrimination reported through a dedicated hotline; and (d) developing a strong data management system and process that secures personal data and information in a manner that is safe, ethical, and confidential. 86. **Furthermore, the ESA and SEP also refer to the GoU’s Circular", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "more frequent flooding rains. 42. **Implementation** . This component will be implemented by MINEMA, supported by the Ministry of Environment and the Rwanda Environment Management Authority. As activities will be in the camps, MINEMA will be responsible for long-term management and maintenance. The activities are expected to improve environmental conditions for 125,000 people (camp-based refugee population and people living in the surrounding villages). **Component 4: Project Management, M&E and Capacity-Building (US$4.02 million equivalent)** 43. This component will support the Single Project Implementation Unit (SPIU) at MINEMA and staff in the target districts to manage the project. [24] This will include project staff at the district level for coordination and oversight. M&E arrangements will include a baseline survey, annual surveys, and endline assessment and continued operation of the Management Information System (MIS). Other activities will include a communications strategy and funds for capacity-building for staff from all project implementing agencies on issues such as community development, fiduciary management, E&S risk management, financial inclusion, climate risk management and development responses to forced displacement. 23 The assessment also identified additional needs that will not be included in the Phase II design due to resource constraints and to avoid overcomplicating the design: (a) reforestation", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "specialists with experience with IDRD-financed operations. Given these constraints, the creation of a PIU dedicated to the implementation of the IBRD Project is the preferred option presented by MEP’s Financial Directorate. [29] . The assessment identified key FM actions that should be undertaken by the MEP that include: (i) the creation and maintenance of a PIU; (ii) recruitment of FM staff with appropriate skills and experience, no later than 6 months after effectiveness; (iii) the MoF granting the PIU with a license to use the SIGAF (Sistema Integral de Gestión Administrativa y Financiera for its name in Spanish); (iv) preparing an FM section in the project operational Manual (POM) satisfactory to the Bank. The creation of the PIU will be a condition of effectiveness (upon satisfactory implementation of the agreed fiduciary action plan, it is expected that MEP’s PIU will have the capacity to ensure adequate FM arrangements are in place for the proposed project implementation). 51. **The PIU to be established at the MEP is expected to undertake the FM aspects of the proposed Project.** These encompass the following main tasks: (i) budget formulation and monitoring; (ii) cash flow management (including processing payments and submitting loan withdrawal applications to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "displaced as a result of the 1948 war, and were under the auspices of the United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), an agency which was established prior to UNHCR. Palestinian refugees and their descendants are now estimated at 4.7 million (UNRWA 2009). _Refugee Survey Quarterly_ has recently published a special issue which provides a detailed historical account of this multifaceted issue (RSQ 2009). 3", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "(Bonte) 1998 2003 Akrokeri-Ashanti Canada Konongo 1990 active LionGold Corp. Singapore Kwabeng 1990 1993 Akrokeri-Ashanti Canada Nzema 2011 active Endeavour Canada Obotan 1997 2001 PMI Gold Canada Obuasi 1990 active AngloGold Ashanti South Africa Prestea Sankofa 1990 2001 Anglogold Ashanti South Africa Tarkwa 1990 active Gold Fields Ghana Ltd. South Africa Teberebie 1990 2005 Anglogold Ashanti South Africa Wassa 1999 active Golden Star Resources USA _Source:_ InterraRMG 2013. _Note:_ Active is production status as of December 2012, the last available data point. 6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**SUMMARY** Previous Ricardian analyses of agriculture have either omitted irrigation or treated irrigation as though it is exogenous. In practice, it is a choice by farmers that is sensitive to climate. This paper develops a choice model of irrigation in the context of a Ricardian model of cropland. We first examine how climate affects the decision to employ irrigation and then how climate affects the net revenues of dryland and irrigated land. This Ricardian ‘selection’ model, using a modified Heckman model, is then estimated across 8400 farmers in Africa. We explicitly model irrigation, but we control for the endogeneity of irrigation that plagues a recently suggested remedy. We find that the choice of irrigation is sensitive to both temperature and precipitation. Simulating the welfare impacts of several climate scenarios, we demonstrate that a model which assumes irrigation is exogenous provides a biased estimate of the welfare effects of climate change. If dryland and irrigation are to be estimated separately in the Ricardian model, irrigation must be modeled endogenously. The results also indicate that African agriculture is sensitive to climate change. Many farmers in Africa will experience net revenue losses from warming. We find that the elasticity of net revenue with", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the surveys of women will be the main source of data. However, we also use the surveys of men, which give us data from the same four survey years, but with a total number of 12,294 individuals, of which 7,491 men live within 100 km of a mine. In addition, the DHS data collect records of all children born within the five years prior to the surveying. Of the 12,174 children born to the surveyed women within the last five years, 6,888 were born to women currently residing within 100 km of a mine. See Appendix table 1 for definition of outcome variables. We complement the analysis with household data from the GLSS collected in the years—1998– 99, 2004–05, and 2012–13. These data are a good complement to the DHS data, because they 6 The first mines were opened in 1990, prior to the first household survey. Ten mines were opened after the first DHS in 1993. There is less variation in the data set using GLSS where the first households were surveyed in 1998, i.e. 8 years after the first mine opened. However, the DHS data include births recorded from 1987, which is prior to all mine openings. 9", "output": {"entities": {"named_data": [{"text": "DHS data"}, {"text": "household data from the GLSS"}, {"text": "GLSS"}], "descriptive_data": [{"text": "surveys of men"}, {"text": "household data from the GLSS"}], "vague_data": [{"text": "surveys of women"}, {"text": "surveys of men"}]}}}
{"input": "normal good, then increased wealth would result in greater insurance demand. [18] Although the BASIX data set does not offer the opportunity to test the direct effects of a cash payment separately from an insurance payout, there are a number of reasons why it is unlikely that wealth or liquidity effects are driving the results. Most important, insurance payouts are given in the context of a rainfall shock, which would most likely result in a loss of income. It may help to recall that the empirical results are being driven by variation in rainfall across locations, not by levels of insurance within a village. Therefore, for wealth effects to be driving the results, one would need to think that experiencing an insurance payout in the context of a rainfall shock resulted in people becoming wealthier than those people who didn’t experience a shock at all. Given the fact that most buyers bought a relatively low amount of insurance coverage relative to their incomes, experiencing a rainfall shock, even when insured, would likely decrease future wealth. Therefore, wealth effects seem like a poor explanation as to why receiving payouts spurs future insurance sales. If people who received insurance payouts had a", "output": {"entities": {"named_data": [{"text": "BASIX data set"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Economics of Disasters and Climate Change Fig. 9 Relative exposure in the Red River Delta for historical 25-year flood (left) and 25-year flood with high climate impacts (right) 2012). For instance, comparing exposure of poor people to average exposure, poor households are 71% more exposed to flooding in the Mithi River Basin in Mumbai, India (Hallegatte et al. 2016). We examine these dynamics in HCMC, using high-resolution local-scale flood maps designed specifically for HCMC (Lasage et al. 2014) and a proxy for poverty using the spatial location of potential slums from the Platform for Urban Management and Analysis (PUMA) data set (World Bank 2015). The results we present below are for all districts in HCMC; results for only districts with slum areas are similar and thus not reported. We find that a relatively high percentage of the potential slum areas are exposed to floods, ranging from 68.9% (for a 10-year return period) up to 83.3% (for a 1000-year return period). When considering all urban areas of HCMC, exposure to flooding is lower: 63% (for a 10-year Fig. 10 Relative exposure in the Mekong Delta for historical 25-year flood (left) and 25-year flood with high climate impacts (right)", "output": {"entities": {"named_data": [{"text": "Platform for Urban Management and Analysis"}], "descriptive_data": [{"text": "high-resolution local-scale flood maps"}], "vague_data": []}}}
{"input": "The Systematic Tracking of Exchanges in Procurement (STEP) system will be used for all procurement activities; and g) The World Bank will carry out regular reviews of project-related procurement activities. 17. **Procurement oversight and monitoring arrangements.** The World Bank exercises its procurement oversight through a risk-based approach comprising prior and post reviews as appropriate. The World Bank sets mandatory thresholds for prior review based on the procurement risk rating of the project. The requirement for a prior or post review is specified in the Procurement Plan. The World Bank will carry out post reviews of procurement activities undertaken by the recipient to determine whether they comply with the requirement of the Financing and Project Agreements. 18. **Terms of reference** for all contracts will be cleared by the World Bank, regardless of whether the assignment is for prior or post review. 19. **Training and workshops** : The project will finance training and workshops, if required, based on an annual training plan and budget, which will be submitted to the World Bank for its prior review and approval. The annual training plan will identify, among other things: (a) the training envisaged; (b) the justification for the training; (c) the personnel to be", "output": {"entities": {"named_data": [{"text": "Systematic Tracking of Exchanges in Procurement (STEP)"}], "descriptive_data": [], "vague_data": []}}}
{"input": "and feedback mechanism will also be established to enable individuals to report concerns or complaints if they feel unfairly treated or adversely impacted by the project. The SEP has been disclosed on the MINEMA and World Bank websites. 88. **To address these E&S risks, the applicable Environmental and Social Standards (ESSs) are** ESS1 (Assessment and Management of Environmental and Social Risks and Impacts), ESS2 (Labor and Working Conditions), ESS3 (Resource Efficiency and Pollution Prevention and Management), ESS4 (Community Health and Safety), ESS5 (Land Acquisition, Restrictions on Land Use and Involuntary Resettlement), ESS6 (Biodiversity Conservation and Sustainable Management of Living Natural Resources), ESS8 (Cultural Heritage), ESS9 (Financial Intermediaries), and ESS10 (Stakeholder Engagement and Information Disclosure). 89. **To ensure compliance with the ESSs, the project will implement the following E&S instruments:** Environmental and Social Commitment Plan (ESCP), ESMF, LMP, Environmental & Social Impact Assessments (ESIAs), ESMPs, SEP and Environmental and Social Audits (ESAs). Measures to integrate E&S specifications in procurement and to manage contractual obligations with construction companies and suppliers will also be enforced. Dedicated, full-time E&S specialists from the MINEMA SPIU from Phase I will oversee these activities to minimize risks. BRD, BDF and RTDA will each appoint their own E&S", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Uganda Development Response to Displacement Impacts Project Phase II (P510476) PROJECT APPRAISAL DOCUMENT (d) sustainable land management practices were adopted on 5,110 hectares of land area (target 4,500). A World Bank strategic review of the Uganda WHR-financed portfolio highlighted the substantial impact of the project, with notable achievements in strengthening the inclusiveness of district level development planning, strong community engagement, and efficient implementation through the community-driven development (CDD) approach and community procurement. The Implementation Completion and Results Report (ICR) for Phase I highlighted that other DRDIP countries drew inspiration from Uganda’s legal and policy framework and operational approaches on issues such as CDD, livelihood, and refugee inclusion in local planning and decision-making. [18] 20. **Phase I introduced innovations for forced displacement preparedness and social cohesion.** The project featured the world’s first displacement risk financing mechanism, the Displacement Crisis Response Mechanism (DCRM). The DCRM provided rapid contingency financing to build resilience in districts experiencing large refugee inflows. A pilot to reduce gender-based violence (GBV) and violence against children (VAC) also contributed to social cohesion. A 2022 World Bank study on forced displacement reinforced the value of projects such as DRDIP, concluding that ‘multi-sectoral development investments directed to refugees", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "if people consider insurance as an investment, as in Karni and Safra (1987). One might think that this type of bias would have spillover effects (which I do not observe), but may also be present at the individual level if people believe recent insurance payouts are a sign of individual luck. Another explanation could be that insurance purchasers behave as if they are “gambling with house money,” as in Thaler and Johnson (1990). If customers exhibit loss aversion, they may not view insurance premiums paid after receiving payouts as true losses, since they are still “in the red” in their relationship with the insurance company. If the assumption is that reference points adjust after receiving insurance payouts, the observed behavior is consistent with this theory. This explanation is bolstered by the fact that the data show negative effects of small payouts, with the effect of payouts becoming positive only 19 [This analysis is available in the supplemental appendix, table S.5. There is no correlation between payouts and a dummy](http://wber.oxfordjournals.org/lookup/suppl/doi:10.1093/wber/lhw045/-/DC1) for our “Marketing Restricted Sample.” However, BASIX is more likely to offer insurance in areas where there were insurance payouts in the previous year. Since all of this paper’s analysis is", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "for all implementing entities, including community-based organizations and seed grants for VRFs, will be described in the FM section of the PIM. The PIM will also include a Community Operations Manual that will detail all steps in the CDD process, including accountability arrangements. 75. **Audit** . The project will have two audit reports that will be submitted to the World Bank by OPM and IG within six months after the end of the financial year. The project will also have interim financial reports submitted to the World Bank within forty-five days after the end of the quarter by both OPM and IG. **Procurement** 76. **Procurement for the project will be carried out in accordance with the World Bank Procurement Regulations** **for IPF Borrowers, dated February 2025 (Procurement Regulations).** The project will be subject to the “Guidelines on Preventing and Combating Fraud and Corruption in Projects Financed by IBRD Loans and IDA Credits and Grants”, dated October 15, 2006, and revised in January 2011 and as of July 1, 2016 (Anti-Corruption Guidelines), and beneficiary ownership disclosure requirements. The project will use the Systematic Tracking of Exchanges in Procurement (STEP) system to provide data on planned procurement activities, establish benchmarks, monitor delays,", "output": {"entities": {"named_data": [{"text": "Systematic Tracking of Exchanges in Procurement"}], "descriptive_data": [], "vague_data": []}}}
{"input": "just outside our 20 km cutoff distance may also be “treated” by the mine, and the investment phase of the mine that precedes initial production can generate substantial employment. Overall, the effects do not change much except making the cash earnings coefficient larger and more significant. The increase in cash earning opportunities is estimated at 7.5 to 7.8 percentage points compared with 5.4 in the baseline estimation. **6.6 Employment and wages using the GLSS** The DHS data do not provide detailed information regarding how much an individual earns for work, or her wage rate, but the GLSS does collect such data. First, we try to replicate the results estimated with the DHS data. Panel A of table 11 indicates that agriculture becomes less important in mining communities for women (statistically insignificant), who mainly shift into services and sales (statistically insignificant, except for strategy 2). Men are more likely to work as miners (statistically significant across all strategies). 29", "output": {"entities": {"named_data": [{"text": "GLSS"}], "descriptive_data": [], "vague_data": [{"text": "DHS data"}]}}}
{"input": "maps, which have a spatial resolution of 20 m, represent the current conditions for five return periods: 10, 25, 50, 100, and 1000 years. Future conditions, again using the five return periods, include a sea level rise scenario of +30 cm in the year 2050 (consistent with the Blow^ sea level rise used for the maps produced for this study) in combination with current river discharge (FIM 2013). Potential peaks in precipitation events and/or river discharges due to climate change are not covered by this data set. The inundation layers for a 10, 25, and 50year return period under current climate conditions and given a sea level rise scenario of +30 cm are shown in Fig. 2. Socioeconomic Data District-Level Poverty and Population Data At the national-level analysis, we overlay the flood hazard maps developed for this study with spatial socioeconomic data. For Vietnam, the World Bank has produced estimates of the Table 2 Hazard map scenarios for which the modeling was conducted for Vietnam Scenario Coastal Fluvial/Pluvial 1 in 25 1 in 25 1 in 25 1 in 25 Future – Low 1 in 25 + 28 cm 1 in 50 1 in 25 Future – Medium 1 in", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "spatial socioeconomic data"}], "vague_data": []}}}
{"input": "Trafficking in Women in Israel. http://www.knesset.gov.il/committees/heb/docs/sachar_final2005.htm. (Hebrew) (Accessed 20.08.2010) MALKKI, L. H. (1995a) _Purity and Exile: Violence, Memory, and National Cosmology Among Hutu_ _Refugees in Tanzania_ . Chicago: University of Chicago Press. ——— (1995b) Refugees and Exile: From \"Refugee Studies\" to the National Order of Things. _Annual_ _Review of Anthropology_ 24, no. 1: 495-523. ——— (2002) News from Nowhere: Mass Displacement and Globalized `Problems of Organization'. _Ethnography_ 3, no. 3: 351-360. MAN, I. (2010) Refugees. _Maftech_ 1, no. 1. http://mafteakh.tau.ac.il/pdf/1-2010-08.pdf. (Hebrew) (Accessed 20.08.2010) MARKOWITZ, F. (1996) Living in limbo: Bosnian Muslim refugees in Israel. _Human Organization_ 55, no. 2: 127-132. MARTINS, B. O.(2009) Undocumented Migrants, Asylum Seekers and Refugees in Israel. EuroMeSCo Paper 81. http://www.euromesco.net/images/paper81eng.pdf. (Accessed 20.08.2010) McCARTHY, R. (2010) Israel to Build Surveillance Fence along Egyptian Border. _The Guardian_, November 1. http://www.guardian.co.uk/world/2010/jan/11/israel-fence-egypt. (Accessed 20.08.2010) MFA. (1948/2010) Israeli Declaration of Independence. http://www.mfa.gov.il/MFA/Peace%20Process/Guide%20to%20the%20Peace%20Process/Decl aration%20of%20Establishment%20of%20State%20of%20Israel. (Accessed 20.08.2010) MORRIS, B. (1997) _Israel's Border Wars, 1949-1956: Arab Infiltration, Israeli Retaliation, and the_ _Countdown to the Suez War_ . USA: Oxford University Press. 18", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "their accommodation in the coming months should there be need for collective accommodation facilities to create additional space for newcomers. Participants also expressed significant financial strain in covering the costs of their accommodation. While only 4% of respondents (17 households) reside in accommodation provided by their employer, it is noteworthy that their information and other priority needs are heightened. While accommodation was indicated as a priority need by only 13% of respondents, employment and information needs were much higher for this group, mentioned by 53% and 27%, respectively, compared to 32% and 12% of respondents overall. This group also highlighted a much higher need for information on legal status (40%), Temporary Protection (27%) and how to claim asylum (20%) than the overall respondents (26%, 15% and 5% respectively). These findings may reflect that Ukrainian Temporary Protection respondents living in employer-provided housing face barriers to accessing information and may be seeking assistance in finding new employment and in relation to their legal status. Finally, out of those who do not have a rental contract (6%), the majority of respondents (92% in comparison to 75% in Q1) are in this situation because the unit is rented by another person or entity. This", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "rural development approach.** The region not only hosts a significant migrant population, primarily from Ethiopia, but also grapples with chronic underdevelopment, reflected in high poverty rates, limited access to basic services (including water, sanitation, healthcare, and education), and high levels of unemployment. The continuous inflow of migrants places additional strain on these already overstretched services, exacerbating the challenges faced by host communities. The region’s arid climate and vulnerability to climate change further intensify these challenges, restricting opportunities for sustainable livelihoods. Poverty in Dikhil is marked by multiple layers of deprivation – economic exclusion, poor social infrastructure, and environmental fragility – compounded by limited access to markets and essential infrastructure. As a result, the region’s socio-economic landscape requires a nuanced, multi-sectoral response that simultaneously addresses these interconnected issues. The project’s integrated approach will create sustainable livelihoods for both local residents and migrant communities while contributing to the 4 World Bank, Gender Portal. 5 UNHCR, African Development Bank Group, IGAD, EAC (2024), Regional Report Draft: Regional Program on Enhancing the Investment Climate for the Economic Empowerment of Refugee, Returnee and Host/Return Community Women in the East and Horn of Africa and Great Lakes Region Page 3", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "confirms that the coefficient for electricity access is negative using the treatment distance 20 km. However, with a treatment distance of 10 km, the effect is marginally positive and insignificant. If we use a treatment distance of 50 km, we no longer see a significant effect. In panel Ab, the results are replicated using a spatial lag model, meaning that we allow for nonlinear effects with distance. In reality, it seems like the electricity rate is much higher before a mine (dashed line) than with an active mine (the blue line). However, when the results are decomposed by migrant status in panel Ac of figure A1 (Annex) we find that migrants are driving the lower electricity rate. In fact, among nonmigrants, the electricity rate is higher 0–10 km from an active mine, although it is slightly lower 10–20 km away. [14] **6.3 Distributional effects on wealth and inequality** Table 9 presents the effects of mining on asset wealth and on asset wealth inequality. Wealth data are available in the form of a wealth index, but only for the two last DHS surveys. Following Fenske (2015) and Flatø and Kotsadam (2014), we calculate inequality by means of a Gini coefficient (recoding", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "the two last DHS surveys"}], "vague_data": []}}}
{"input": "regions. However, all regions (particularly AFR and LCR) include countries that have no lending, despite significant environmental problems. **Figure 5.2: World Bank Environmental Lending by Region** **vs. Overall Environmental Problems (Log Scale)** The number of such zero-lending cases suggests that the Bank's interaction with these countries has been affected by other factors. We introduce broader considerations into our regressions by including the Bank's total country lending and countries' OED project success rates, as well as regional differences. The results in columns 2 and 3 of Table 5.1 suggest that the Bank's overall lending relationship with a country and the country's project success rate are both significant determinants of environmental lending. The results in column 3 also indicate a significant component of environmental lending to two regions (ECA, MNA) that is not accounted for by our environmental problem indicator, project success rates, or other Bank lending. 14", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "renewable energy, that are now covered by other projects; and (b) government needs support to lead coordination of the development response across multiple operations. The project will have five components. **Component 1: Social and Economic Services and Infrastructure (US$191.5 million equivalent)** 23. **This component will support the construction, rehabilitation, upgrading, and maintenance of priority basic** **service infrastructure.** Infrastructure investments will benefit both refugees and host community members, supporting the transition roadmap goal of integrating refugees into national education, health, and water supply systems. Component activities will support improved access to services for three million people (66 percent host community members/34 percent refugees). 18 See ICR Report No. ICR00006388, December 3, 2024. 19 World Bank (2022). _Social Cohesion and Forced Displacement: a Synthesis of New Research_ . Washington DC: World Bank. Page 7", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Integrated Community Resilience Project (P506969) PROJECT APPRAISAL DOCUMENT 13. **Refugee-hosting areas such as Obock, Ali Addeh, and Holl Holl, face difficulties in the delivery of key services,** **such as adequate water supply, sanitation, and electricity.** Access to reliable water sources is particularly limited, contributing to health vulnerabilities in both refugee sites and host communities. Carrying water from wells to houses imposes a heavy burden of work on women and children, reducing education opportunities. Similarly, electricity coverage remains inadequate, with many households and public facilities still dependent on unreliable power supply. Geographic isolation, especially in Obock, further compounds these issues, as the region's remote location and underdeveloped infrastructure inhibit service delivery, especially during extreme weather events. Refugees in Djibouti face high levels of food insecurity and malnutrition [12], and the World Food Program (WFP), in partnership with the MoI and UNHCR, provides unconditional food assistance to more than 22,200 people per month in refugee-hosting areas of Djibouti [13] . 14. **Women are disproportionately affected by socio-economic disadvantages in Djibouti, facing significant gaps** **across different dimensions, including access to basic services, education and employment opportunities** . Multidimensional Poverty Index (MPI) is reported to be higher among women than men", "output": {"entities": {"named_data": [{"text": "Multidimensional Poverty Index (MPI)"}], "descriptive_data": [], "vague_data": []}}}
{"input": "their surrounding environment. For example, it is expected that SLR will have its most pronounced effects on brackish and freshwater marshes in the coastal zone through alteration of hydrological regimes (Burkett and Kusler, 2000; Baldwin et al., 2001; Sun et al., 2002). Similarly, sea-level rise may not lead to loss of saltmarsh areas since these marshes accrete vertically and maintain their elevation relative to sea level where the supply of sediment is sufficient (Hughes, 2004; Cahoon et al., 2006). WMP indicates the potential for wetlands to migrate landward in response to a 1-meter rise in sea level. The migratory potential is based on a few geophysical characteristics of the coastline: coastal type, topography, tidal range, and other information when available (e.g., whether 14 GLWD coastal wetlands is a term used in this paper to distinguish coastal wetlands from the specific coastal wetlands type in the GLWD. GLWD coastal wetlands type is derived from a number of data sources and categories: ‘Lagoon’ from ArcWorld (ESRI, 1992: referenced in Lehner and Döll 2004); ‘Delta’, ‘Lagoon’, ‘Mangrove’, ‘Estuary’, ‘Coastal Wetland’, and ‘Tidal Wetland’ of WCMC wetlands map (Dugan, 1993; WCMC, 1993; referenced in Lehner and Döll 2004) - see Lehner and Döll (2004)", "output": {"entities": {"named_data": [{"text": "WCMC wetlands map"}, {"text": "GLWD coastal wetlands"}, {"text": "ArcWorld"}], "descriptive_data": [], "vague_data": []}}}
{"input": "### Protection Risk III **Access to work:** 10% of respondents who are unemployed reported challenges in accessing employment, mainly due to language barriers, a lack of opportunities, as well as a lack of education recognition, caring responsibilities for dependents, or a lack of information. Focus group discussions conducted by UNHCR [2] ## highlighted challenges with women accessing 61% employment due to a lack of childcare, Face language barriers in accessing kindergarten places and other childcare employment arrangements, including for school-age children. Given the large proportion of single female caregivers, addressing this challenge will be key to increase access to work for this group and to mitigate protection risks including gender-based violence, human trafficking and exploitation. Women also raised challenges related to language barriers in accessing employment. Specific challenges in accessing quality language courses at the correct level were also raised (high demand for quality B1-level courses). The lack of adequate language skills leads to the inability to upscale professional skills and to seek meaningful employment opportunities matching qualifications. When seeking employment through agencies, women reported cases of labour exploitation with jobs that often involve long working hours, no breaks, no social protection coverage, and no annual leave. From protection monitoring,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "no significant differences in either of them. 13 Information on crop output was collected at the crop level, separately for the two main agricultural seasons (July - December 2004 and January - June 2005). A diary was used for continuously harvested crops and prices, in addition to standard socio-economic information, were collected at the community level. 9", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "assistance in finding new employment and in relation to their legal status. Finally, out of those who do not have a rental contract (6%), the majority of respondents (92% in comparison to 75% in Q1) are in this situation because the unit is rented by another person or entity. This may indicate a prevalence of sublease schemes. During UNHCR’s focus group discussions with Ukrainian Temporary Protection holders in Brno and Prague in August, some participants highlighted having encountered challenges with sublease schemes, including facing higher than market-rate rent propositions. 3 Multiple responses were possible. UNHCR / September 2024 3", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "estimation strategy assumes similar trends over time across the treatment (close to mines) and control group (far away from mines), in absence of the gold mining expansion. While this assumption cannot be tested using our dataset, previous analyses have found evidence for parallel pre-trends in infant mortality and night lights (Benshaul-Tolonen, 2019) for gold mining countries in West and East Africa (including Ghana). The baseline differences in observable characteristics – in particular, lower levels of economic development preceding the mine opening - indicate that a cross sectional approach using only the post-period may not be sufficient to understand the impact of gold mining on socio-economic variables. **Table 2 Summary statistics for women’s survey** (1) (2) (3) (4) Before mining During Mining >20 km <20 km >20 km <20 km Mean Coefficient Mean Coefficient _Woman Characteristics_ Age 28.79 0.836 28.95 -0.352 Total children 2.18 0.417* 2.56 -0.035 Wealth 3.85 -0.619** 3.33 -0.028 Nonmigrant 0.32 0.123** 0.33 -0.028 Urban 0.62 -0.300** 0.49 -0.150** No education 0.17 -0.045 0.20 -0.042** <3 years education 0.77 0.035 0.74 0.045** 15", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "impact of property rights insecurity arising from overlapping land rights rather than comparing titled and untitled land. We do so for the case of Uganda, a country where overlapping property rights, many of them established a long time ago, are very common. This, together with the ability to rely on a large nationally representative household survey, allows us to go beyond the existing literature in three respects. First, while the historical genesis of overlapping rights makes it unlikely that such arrangements were chosen based on comparing the cost and benefits of different contractual forms, our ability to apply household level fixed effect estimation techniques to a large sample of (owner-cum-occupant) households who simultaneously operate own and usufruct parcels allows us to avoid many of the biases that have characterized cross sectional estimates in the past. Second, the existence of laws aiming to eliminate investment disincentives arising from overlapping property rights enables us to assess whether, and if yes to what extent, such laws have achieved their objective. This provides lessons on the scope to reduce underinvestment associated with insecure tenure through (legislative) means that stop short of changing the land ownership structure. Finally, information on tenants’ willingness to purchase residual", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "large nationally representative household survey"}], "vague_data": [{"text": "nationally representative household survey"}]}}}
{"input": "scenario as given, and assess the _exposure_ of the present wetland stock for each of the 76 developing countries and five regions. Second, the digital elevation (90m DEM V2) data we use in our analysis gives altitude in 1-meter increments, preventing us from sub-meter SLR modeling. [13] Third, the lack of resolution of spatial data of the wetlands and digital elevation higher than 90 m prevented us from including small islands in our analysis. Fourth, our analysis does not estimate potential destruction of wetlands from 13 One can interpolate the elevation data we have used for sub-meter SLR modeling, but in that case, precision of the estimates would be difficult to justify. The potential use of LIDAR survey (laser-based elevation measurement from low-flying aircraft) was beyond the scope of our analysis. 5", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "spatial data of the wetlands"}], "vague_data": []}}}
{"input": "Jun. (2020). Coastal Development between Opportunity and Disaster Risk: A Multisectoral Risk Assessment for Vietnam. Policy Research Working Paper; No. 9352. World Bank, Washington Bright, E. A., Rose, A. N. & Urban, M. L. _Landscan 2015 High-Resolution Global Population Data Set_ . (Oak Ridge National Laboratory (ORNL), Oak Ridge, TN, USA, 2016). Chakraborty, J., T. Collins, M. Montgomery, S. Grineski. (2014). Social and Spatial Inequities in Exposure to Flood Risk in Miami, Florida. Natural Hazards Review. Vol.15(3) Erman, A., M. Tariverdi, M. Obolensky, X. Chen, R. Vincent, S. Malgioglio, J. Rentschler, S. Hallegatte, N. Yoshida (2019), Wading Out the Storm: The Role of Poverty in Exposure, Vulnerability and Resilience to Floods in Dar Es Salaam. World Bank Policy Research Working Paper No. 8976, Facebook Connectivity Lab and Center for International Earth Science Information Network - CIESIN. (2018). Available at: http://ciesin.columbia.edu/data/hrsl/#acknowledgements. (Accessed: 15 [th] September 2020). Fielding, J. (2012). Inequalities in exposure and awareness of flood risk in England and Wales. Disasters. Vol. 36(3), pp.477-494 Freire, Sergio; MacManus, Kytt; Pesaresi, Martino; Doxsey-Whitfield, Erin; Mills, Jane (2016): Development of new open and free multi-temporal global population grids at 250 m resolution. Geospatial Data in a Changing World; Association of Geographic Information Laboratories", "output": {"entities": {"named_data": [{"text": "Landscan 2015 High-Resolution Global Population Data Set"}], "descriptive_data": [{"text": "open and free multi-temporal global population grids"}], "vague_data": []}}}
{"input": "of Bengal** **3.2 Trend in Maximum Wind Speed, 1877-2016** Maximum wind speed is the consistently-reported measure of storm power in our database. We compute two measures for a trend analysis. First, we order all 525 storms by date and compute the 20-date moving average (MA) for maximum wind speed. This is similar to a conventional moving average, which uses evenly-spaced dates. Storm incidence in our database varies by season and year, but we believe that our MA measure is informative because year-to-year 6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) **ANNEX 1: Implementation Arrangements** **Financial Management** 1. Financial Management tasks for the proposed project will be handled by the PIU to be created, which will be staffed with a seasoned Financial Management Specialist/budgetary an Accounting and Treasury Analyst for carrying out financial management tasks under the project which include: (i) a financial management specialist, (including processing payments and submitting loan withdrawal applications to the WB); (iii) maintenance of accounting records (including the administration and maintenance of an inventory of project assets); (iv) preparation of semi-annual reports and annual financial statements; (v) administration of adequate information systems; and (vi) arranging for execution of external audit. 2. The staff required for the FM positions referred above will be hired under Terms of Reference acceptable to the Bank. 3. **Planning and budgeting** . The PIU will be responsible for preparing and monitoring the annual operating plan and budget. The project’s annual operational plan will be the main input for budget formulation. Budget formulation and execution will follow local procedures and requirements. (i.e., approval of transactions, modifications, issuance of commitments) Its monitoring procedures will be established in the Project Operational Manual POM. The budget", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the radius-buffered storm track polygon at its first coastal intersection. **3. Aggregate Results** **3.1 Trend in Cyclonic Storm Incidence, 1877-2016** Although we focus on the northern coast of the Bay of Bengal, our database includes all recorded tracks for the Bay of Bengal and Arabian Sea. This provides a very large regional sample: 525 cyclonic storms recorded from 1877 to 2016. For a trend analysis, we divide the data into seven periods: 1877-1900, 1901-1920, 1921-1940, 1941-1960, 1961-1980, 1981-2000 and 2001 2016. Table 1 and Figure 1 provide two trend measures for cyclonic storm frequencies since 1877: storms/year for each period, and the two-period moving average of storms/year. The first measure displays no trend through 1960, a large increase during the period 1961-1980, and a decline from 3 Some storm tracks that approach at oblique angles intersect the coastline two or more times. 5", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Despite the possible gains in wages for wage earners, we note a decrease in the regionally deflated total household expenditure (column 5), and a decrease in per capita expenditure on food and nonfood items (column 4). The increase in wages but decrease in total expenditure can possibly be explained by rising prices and wages in mining communities, where everyone has to pay the higher prices but only some (those who earn wages), benefit from a rise in wage rate. Columns 6 through 9 of table 12 look at nondeflated expenditure measures for food, housing, health and education, and household energy. [17] We confirm that total household expenditure on food decreases (compared with the per capita deflated measure in column (4)), but find that households spend more money on housing, transport, and communication, and household energy, such as electricity and gas. The electricity and gas expenditure is only for those who have any positive expenditure on these, and we saw earlier that electricity access changes with the mine. This confirms that, among those who spend anything on electricity, they spend more on it in mining communities. **Table 12 Using GLSS: Household income and expenditure** (1) (2) (3) (4) (5) (6) (7)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "data section for details. 11 The IPCC’s Fourth Assessment Report (AR4) projects increased SLR between 0.18m and 0.59m across various emission scenarios over the next 100 years. However, this range has been criticized by many experts as being too conservative and not sufficiently reflective of the large uncertainty pertaining to SLR (Krabill _et al_ ., 2004; Overpeck _et al_ ., 2006; Rahmstorf, 2007). The most recent evidence suggests that sea-level rise could reach 1 meter or more during this century (Hansen and Sato, 2011; Vermeer and Rahmstorf 2009; Pfeffer et al., 2008). The IPCC itself pointed out that its projections did not include changes within the polar ice sheets. The IPCC noted that the upper values of projected sea level rise presented in its report are not to be considered upper bounds and that higher rises in sea level cannot be ruled out. 12 These being the five regions used by the World Bank: East Asia and Pacific, Middle East and North Africa, Latin America and Caribbean, South Asia, and Sub-Saharan Africa 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the efficiency of disbursement to communities, address payment delays, and improve the timeliness of financial reporting and accountability; (b) MoF and BoU are strengthening internal control mechanisms around TSA payments to ensure the correct beneficiaries are paid; and (c) MoFPED has set up regional centers for local governments to go to if they face network problems and unstable electricity to use the IFMIS to account for project funds. MoFPED has also provided budget to local governments to purchase fuel for generators to manage power cuts. The IFMIS, the use of a consolidated fund, and payments to beneficiaries using the TSA at BoU have significantly enhanced accountability at the local government level. This is reflected in the Auditor General’s report for 2022/23 and 2023/24, where all 22 local governments involved in project implementation had an unqualified (clean) audit opinion except for Ntoroko district, which had a qualified opinion. [24] Accountability measures for all implementing entities, including community-based organizations and seed grants for VRFs, will be described in the FM section of the PIM. The PIM will also include a Community Operations Manual that will detail all steps in the CDD process, including accountability arrangements. 75. **Audit** . The project will have", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**2024 CRITICAL FUNDING NEEDS IN EUROPE** ###### **South Eastern Europe** As of June 2024, some 3,000 refugees and asylum-seekers were present in South Eastern Europe, including 199 unaccompanied and separated children. [5] UNHCR’s [Strategy for engagement in mixed](https://reliefweb.int/report/world/strategy-unhcr-engagement-mixed-movement-western-balkans-revision-october-2021) [movements in the Western Balkans sets a foundation to work with partners to strengthen asylum systems](https://reliefweb.int/report/world/strategy-unhcr-engagement-mixed-movement-western-balkans-revision-october-2021) and identify viable solutions for refugees, as well as to eradicate statelessness, while fostering opportunities for integration and inclusion for those granted international protection. UNHCR is helping to build the capacities of local authorities to gradually assume greater responsibility for their asylum systems, while also improving protection-sensitive migration management across the region, including recognising the importance of effective return mechanisms for those not in need of international protection. **Funding is needed to support these efforts and ensure sustainable programming** for integration and inclusion, and to identify durable solutions for refugees, asylum-seekers and stateless people in the region – which is itself a region of emigration. # 30.7 % 5 Non-Ukrainian nationals; of these, 52 per cent were in Bosnia and Herzegovina; 25 per cent in Serbia; 7 per cent in Kosovo; 6 per cent each in Albania and Montenegro; and 4 per cent in North Macedonia.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "which calls for systematic mainstreaming of adaptation measures in project design and implementation. Jya Mbere II will also align with the GoR’s National Adaptation Plan of Action (2006), Third National Communications to the United Nations Climate Change Conference in 2018 and its Updated Nationally-Determined Contributions (NDC) 2020, in which it commits to mainstream environmental sustainability and climate change adaptation efforts. Rwanda’s Updated NDC includes a conditional commitment to reduce greenhouse gas (GHG) emissions by 16 percent by 2030 relative to a business as usual (BAU) scenario, and an unconditional commitment to reduce GHG by an additional 22 percent by 2030 relative to the BAU scenario. The project does not hinder this mitigation goal by ensuring that all infrastructure subprojects will be subject to climate risk assessments and will comply with climate-resilient standards. Finally, the project will support implementation of key recommendations from the 2022 Rwanda Country Climate and Development Report, such as investing in the water sector (including flood control and water storage), renewable energy sources and climate-smart agriculture. The results framework will track the number of infrastructure subprojects constructed/upgraded to climate-resilient standards. 71. _Assessment and reduction of mitigation risks_ . The project (Component 1) will invest in infrastructure, including", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "assessments, which will include (a) participatory focus groups and (b) semi-structured interviews with refugees and former refugees, host community members, farmers, cooperatives, and agribusinesses. Citizen engagement outcomes will be assessed through the indicator “Stakeholder consultations convened, and priority measures identified”. These beneficiary assessments will help assess the relevance and impact of project interventions. Each of the interventions will be assessed with respect to inclusion, productivity, climate resilience, jobs, incomes, and food security. 55. **The project’s M&E system will disaggregate results by gender and youth wherever possible and for refugee and** **host communities.** This will ensure that differential impacts on vulnerable groups are adequately recorded. **C. Sustainability** 56. **Investing in policy reform and legal identity for refugees will play a massive role in supporting long-term,** **sustained self-reliance for refugees and former refugees.** The project is aligned with the country’s National Refugee Policy and settlement modernization strategy, both of which seek long-term solutions to inclusion and self-reliance. The GRZ is actively promoting integration between refugees and local communities for economic advancement and is seeking enhanced partnerships with local stakeholders and international partners in addressing the issue of forced displacement. 57. **Appropriately assessing the sustainability risk of investment operations in refugee settlements in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "As part of a regional Protection Profiling and Monitoring exercise, UNHCR collects and analyses on a quarterly basis data about the profiles, protection risks, and needs of refugees from Ukraine in Czechia, through individual interviews and focus group discussions with diverse groups. The key findings are highlighted below. #### Protection Risk I **Access to Temporary Protection (TP):** 98% of the respondents are holders of Temporary Protection in Czechia. Only 1% (five individuals) provided that their application for Temporary Protection was pending, whilst also 1% (four individuals) did not apply for Temporary Protection in Czechia. The reasons being, that they applied for refugee status, did not meet the eligibility criteria, did not stay in the country, or had since transitioned to a different legal status. Overall, access to Temporary Protection in Czechia continues to remain high. of respondents (55 individuals) reported facing some challenges with the Temporary ## 13% Protection application or extension process. In line with previous reports, the main challenges related to applying for Temporary Protection were long waiting times to receive a decision (44%), a lack of required documents (such as ID or proof of address) to complete the registration process (40%), and, despite its overall decrease in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "###### **III.2 Country level analysis** The impacts of SLR on coastal wetlands were also estimated for individual countries. Table 2 summarizes our results by presenting the 10 most vulnerable countries. Estimates indicate large effects of SLR on coastal wetlands are much more concentrated in some countries than others. The 5 most vulnerable countries are: Viet Nam, Argentina, Iran, China and Mexico that represent 77% of the total freshwater marshes at risk from a 1 m SLR. Vietnam is by far the most vulnerable country with close to 65% of its freshwater marshes at risk. For vulnerable GLWD Coastal Wetlands, the top-ranked country China accounts for 56% of GLWD Coastal Wetlands” at risk. Of all vulnerable saline wetlands, Libya, Egypt, Mauritania, India and Argentina account for 93%, with Libya and Egypt representing 61%. Also within the regions, vulnerability is clearly far from balanced across countries. Viet Nam represents 85.1% of all vulnerable freshwater marshes and China represents 79.1% of all vulnerable GLWD Coastal Wetlands within EAP. Within MENA, 92.7% of all regional vulnerable saline wetlands are in Libya and Egypt. On the whole, our results suggest a significant asymmetry in the burden of SLR on wetlands: a small number of developing", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) in OECD countries, and few students enroll in tracks in high demand in the labor market, such as STEAM and digital skills. [13] Quality TVET could play a pivotal role in developing skills that are directly relevant to the labor market and in creating an adaptable workforce. 7. **Costa Rica is undergoing a TVET reform to better align it to the needs of the current and future labor market,** **emphasizing skills for the technology sector and green jobs** . The recently initiated reform includes efforts to revitalize entry into the labor market by targeting support for youth and adults. Participants complete their education certification, and a proposed program of micro-credentials promises further improvement on employability, seeking to align skills provision to labor demand through both the secondary level and vocational training courses and dual modality education offered by INA. As the global landscape shifts towards sustainability, there is likely to be a growing demand for a workforce equipped with expertise in green technologies, renewable energy, environmental sciences, and sustainable practices. Accessing skillsets in these areas requires strong foundational learning, cognitive and digital competencies. Possible green jobs in Costa Rica would", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the increasing influx (Kemp and Kritzman 2008). In the past, Israel has recognised groups of refugees and asylum seekers as a gesture of goodwill. Notable examples of such ̳humanitarian anomalies‘ are the decision to grant refuge to a few hundred Vietnamese boat-people in the end of the 1970s and to admit a group of Muslim Bosnian refugees during the 1990s. (Ben-Dor and Adut 2003, 21-22; Markowitz 1996). Following its withdrawal from South Lebanon in 2000, Israel admitted nearly 6,000 members (and their families) of the South Lebanese Army, a sectarian militia who collaborated with Israel during its occupation of South Lebanon. Such precedents, coupled with public pressure, led former Prime Minister (PM) Olmert to grant an exceptional temporary residency to approximately 500 Darfurian asylum seekers in September 2007 (Mualem 2007). Israel historically handled asylum requests by outsourcing the process to UNHCR, using the assistance of the agency‘s honorary correspondent in Israel, which later became an official representative office (UNHCR 2007) It was only in 2001, 50 years 6 Driven by the horrors of the Holocaust in Europe and aiming to protect the Jewish refugees from World War II the young state of Israel was among the first 26 states who", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "sources and vintages of imagery. To guide the identification of slums, previous work has provided information on the appearance and geographical extent of slums in HCMC. Surveys of poverty in the city find the appearance of slums in HCMC to be characterized as densely built small households and shelters that have predominantly semi-permanent character (Habitat for Humanity 2008). In terms of geographic extent, many slums are located in certain districts (districts 2, 3, 4, 6, 8, 11, 12, Binh Thanh, Go Vap, Tan Phu) and along the Saigon River (e.g. Kenh Te, Rach Ben Nghe, Thi NgheNhieu Loc Canal, Kenh Doi, Thi Nghe Canal, Lo Gom, and Canala) (Horsley 2004; De Lay 2011; Habitat for Humanity 2008). Taking into account these spatial and geographic characteristics, the PUMA data set interprets Google Earth imagery to produce two layers of potential slum areas (PUMA 2013): areas with defined borders (polygon-data) and potential slum areas without (point-data) defined borders. In the latter case, we applied a circular buffer of 50 m around each", "output": {"entities": {"named_data": [{"text": "PUMA data set"}, {"text": "PUMA 2013"}], "descriptive_data": [{"text": "Surveys of poverty in the city"}], "vague_data": [{"text": "Surveys of poverty in the city"}]}}}
{"input": "availability of fresh water and sediment, and the salinity of soil and groundwater (Belperio, 1993; Semeniuk, 1994; Blasco et al., 1996; Alongi, 2008). [8] Even though location-specific studies are needed to define the specific details, experts and scientists agree that adaptation of wetlands to future sea-level rise depends on its success in landward progression and is conditioned by the availability of adequate and suitable space for expansion/ migration, and a rate of sea level rise that is not greater than the rate at which wetlands can migrate. [9] This paper is an effort to quantify the coastal wetlands of different types [10] at risk from 1 m SLR [11] in 76 developing countries and territories in the five regions [12] of the world. Our estimates take into account the exposure of wetlands derived from the recent GLWD-3 database to 1 m SLR and the estimated capacity of the coastline to retreat and for coastal wetlands ecosystems to move (or migrate) inland as the coastline is receding. Attempts have also been made to estimate the economic loss, which may be associated with adversely impacted wetlands. Our estimates indicate that a 1 m rise in sea level would lead to a loss", "output": {"entities": {"named_data": [{"text": "GLWD-3 database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "associated with them will lose their services. Wetlands in WMP category 4 are at great risk, but may survive, depending on the effect of flooding behind the coastline. If the flooding is severe enough and persists long enough to seriously disrupt the trapping of the sediment or building upon the peat the sediment creates, the wetlands will be severely degraded and may perish. Hence, the wetlands in WMP categories 3 and 4 exposed to the inundation zone for 1 meter SLR are the estimates of wetlands at inundation risk in a changing climate. ##### **Results** For the 76 coastal developing countries and territories included in this analysis, estimates indicate more than 60% of freshwater marsh, GLWD Coastal Wetlands, and brackish/saline wetlands (henceforth saline wetlands for brevity) might be lost as a result of a 1m SLR. In terms of area estimates, this would translate to a loss of 16,492 square kilometer of freshwater marsh, 17,421 square kilometer of GLWD Coastal Wetlands and 10,969 square kilometer of saline wetlands. Among the four coastal wetland categories, only swamp forests appear less vulnerable to SLR and more capable of migrating as the coast line is receding and henceforth dropped from further analysis [19]", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "University of Kassel, Germany, and the World Wildlife Fund US (WWF-US), Washington DC, USA (Lehner and Döll, 2004). In the generation of the global map of lakes and wetlands from a grid at a spatial resolution of 30 seconds (approximately 1km by 1km at the equator), the GLWD-3 followed the definition of wetlands adopted at the Ramsar Convention, the International Union for Conservation of Nature. Our analysis focuses on freshwater marsh, swamp forests, GLWD Coastal Wetlands [14] and Brackish/ saline wetlands. _Response of wetlands to SLR_ . In order to assess the impact of SLR on wetlands and the potential for adaptation, the wetland migratory potential (WMP) characteristic in the Dynamic Interactive Vulnerability Assessment (DIVA) database from the DINAS-COAST project has been used (Vafeidis et al, 2008). Different types of wetlands are expected to have different migratory potential depending on their own natural characteristics as well as the characteristics of their surrounding environment. For example, it is expected that SLR will have its most pronounced effects on brackish and freshwater marshes in the coastal zone through alteration of hydrological regimes (Burkett and Kusler, 2000; Baldwin et al., 2001; Sun et al., 2002). Similarly, sea-level rise may not lead to loss", "output": {"entities": {"named_data": [{"text": "Dynamic Interactive Vulnerability Assessment (DIVA)"}, {"text": "GLWD-3"}], "descriptive_data": [], "vague_data": []}}}
{"input": "US$ per month, [14] significantly below that by non-agriculturalists (45 US$ per month), pure owners are better off than the rest in terms of total land owned (9.5 vs. 3.2 acres for owner-cum-occupants), the value of own land, livestock, and non-land assets (US$ 4,011, 968 and 1733 vs. 1651, 227, and 1252, respectively), and overall welfare as measured by per capita income (US$ 226 vs. 193). Third, while crop productivity [15] for pure occupants is not significantly different from that for pure owners (US$ 95.3 vs. US$ 96.7 per acre) it is below that achieved by owner-cum-occupants (US$ 110.8/ac.). While pure owners have access to more land than owner-cum-occupants, there is no significant difference in the amount of land cultivated by the two groups during the 2004/5 agricultural season. Pure occupants cultivated significantly less land than any of the two other groups and, as a result, derived a much larger share of their income (42%) from wage employment, as compared to mixed farmers (24%) and pure owners (30%). Finally, with only 16.5% of households and 9.5% of women knowing about the 1998 Land Act, legal awareness remains low. **3.2 Parcel level characteristics** Tables 2 and 3 provide evidence on physical", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Chi Minh City In addition to the flood hazard maps developed for this study as described above, we use an additional set of maps produced specifically for HCMC. 2 These uncertainties largely arise from climate models; global climate models (GCMs) struggle to represent the physical processes that produce extreme rainfall. Indeed even in higher resolution regional climate models (RCMs), heavy rainfall events are poorly represented. As a result the modeled rainfall data must be ‘corrected’, in order to render it realistic. The fact that the underlying models themselves cannot represent flood driving rainfall means that there is little confidence in the projections that they produce. Moreover, at the national scale there is very little river gauge data available in Vietnam. Therefore rainfall-runoff models, required to transform rainfall projections into river discharge values, would be largely un-calibrated. This adds an additional source of significant modeling uncertainty to the model cascade. The combination of poorly represented extreme rainfall in climate models, coupled with uncalibrated rainfall-runoff models, would largely render any projections of future flood hazard impractical, owing to the significant uncertainties that arise.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "flood hazard maps"}, {"text": "maps produced specifically for HCMC"}], "vague_data": [{"text": "river gauge data"}]}}}
{"input": "the wealth of the farmers. If farmers become poorer because of bad rainfall, CRRA utility would suggest that they would be even more risk averse the next year as a second shock would cause greater disutility. I start by examining whether there is actual autocorrelation in the rainfall data. To test for autocorrelation, I create a panel of various rainfall indicators for the period 1961–2004 for each weather station. For each indicator, I run a regression of six lags of the variable on the current value, including weather", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "various rainfall indicators"}, {"text": "rainfall data"}], "vague_data": []}}}
{"input": "between 132 million and 587 million poor people are exposed to flood risks (depending on which poverty definition is used). About 1.2 billion flood-exposed people live in lower- and uppermiddle-income countries. Taking into account the income levels of flood exposed populations is particularly important, as income is a relatively reliable proxy for people’s ability to mitigate, withstand, cope with, and recover from floods. For instance, while a large share of the Dutch population lives in flood risk areas, large-scale investments in flood protection infrastructure have enabled them to mitigate risks. Similarly, flood exposed populations in Canada or Japan are more likely to have access to rapid government support systems in post-disaster situations compared to people in Malawi or Bangladesh. Thus, action to strengthen disaster prevention and recovery capacity is most urgently needed in the hotspots where poverty and flood exposure coincide. References Braese, J., S. De Vries Robbe, J. Rentschler, Jun. (2020). Coastal Development between Opportunity and Disaster Risk: A Multisectoral Risk Assessment for Vietnam. Policy Research Working Paper; No. 9352. World Bank, Washington Bright, E. A., Rose, A. N. & Urban, M. L. _Landscan 2015 High-Resolution Global Population Data Set_ . (Oak Ridge National Laboratory (ORNL), Oak Ridge, TN,", "output": {"entities": {"named_data": [{"text": "Landscan 2015 High-Resolution Global Population Data Set"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Economics of Disasters and Climate Change https://doi.org/10.1007/s41885-018-0035-4 # Exposure to Floods, Climate Change, and Poverty in Vietnam Mook Bangalore [1,2] & Andrew Smith [3] & Ted Veldkamp [4,5] Received: 16 February 2018 /Accepted: 4 October 2018/ # The Author(s) 2018 Abstract With 70% of its population living in coastal areas and low-lying deltas, Vietnam is highly exposed to riverine and coastal flooding. This paper conducts a Bstress-test^ and examines the exposure of the population and poor people in particular to current and future flooding in Vietnam and specifically in Ho Chi Minh City. We develop new high-resolution flood hazard maps at 90 m horizontal resolution, and combine this with spatially-explicit socioeconomic data on poverty at the country and city level, two datasets often kept separate. The nationallevel analysis finds that a third of today’s population is already exposed to a flood, which occurs once every 25 years, assuming no protection. For the same return period flood under current socioeconomic conditions, climate change may increase the number exposed to 38 to 46% of the population (an increase of 13–27% above current exposure), depending on the severity of sea level rise. While poor districts are not found to be more exposed to", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "spatially-explicit socioeconomic data on poverty"}], "vague_data": []}}}
{"input": "**1. Introduction** Recurrent cyclonic storms in the Bay of Bengal inflict massive losses on the coastal regions of Bangladesh and India. Extensive research has investigated the incidence, power and impacts of cyclones in Bangladesh (Ali 1999; Dasgupta et al. 2014; Hoque 1992; Khalil 1992), India (Mishra 2014; Srivastava et al. 2000) and the Bay of Bengal more generally (Bhaskar Rao 2001; Dash et al. 2004; Mandke and Bhide 2003; Mooley and Mohile 1983; Mooley 1980; Muni Krishna 2009; Rao 2002; Yu and Wang 2009). This paper attempts to extend the previous work in several ways. First, we focus on the historical frequency and locations of cyclone strikes to inform household- and community-level research on adaptation to past and expected future cyclones. Previous studies of coastal community adaptation in the region have focused on responses to specific cyclones or generally-defined coastal hazards (Brouwer et al. 2007; Khalil 1993; Khan et al. 2015; Mallick et al. 2011; Mallick and Vogt 2013; Shameem and Momtaz 2014; Siddiqui et al. 2013; Sultana and Mallick 2015). With the notable exception of Dasgupta et al. (2016), these studies have seldom used household-level data to assess the impacts of past cyclones on communities and households, as well", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "household-level data"}]}}}
{"input": "of which will be supported by Jya Mbere II. 9. **Climate change poses risks to Rwanda’s positive economic outlook and refugees are particularly vulnerable** **to climate shocks** . Ranked 112 out of 185 countries in the 2021 Notre Dame-Global Adaptation Index (ND-GAIN), Rwanda is vulnerable to flooding, heat, drought, and landslides, which are expected to increase in frequency and severity. The country has already experienced a temperature increase of 1.4°C since 1970, higher than the global average; and an increase of up to 2.0°C is expected by the 2030s. The need for urgent action to address climate change impacts was highlighted by severe flooding and landslides in May 2023 that claimed many lives, destroyed homes and infrastructure and affected livelihoods. Rwanda’s high dependence on rain-fed agriculture, as well as the need to improve road networks, health facilities and water resource management all contribute to climate vulnerability. [10] The location of Rwanda’s refugee camps on rural hilltops makes them vulnerable to extreme weather events such as flooding and associated landslides. High population density in the camps and the limited capacity of refugees to adapt to the impacts of climate change exacerbates their vulnerability. Despite the protracted nature of displacement, refugee camps", "output": {"entities": {"named_data": [{"text": "2021 Notre Dame-Global Adaptation Index"}], "descriptive_data": [], "vague_data": []}}}
{"input": "(GSS). [2] Point coordinates (global positioning system [GPS]) for the surveyed DHS clusters [3] allow us to match all individuals to one or several mineral mines. We do this in two ways. First, we calculate distance spans from an exact mine location given by its GPS coordinates, and match surveyed individuals to mines. These are concentric circles with radiuses of 10, 20, and 30 kilometers (km), and so on, up to 100 km and beyond. In the baseline analysis where 2 The data was shared by Aragón and Rud (2013) 3 Both the DHS and GLSS enumeration area coordinates have a 1-5 km offset. The DHS clusters have up to 10km displacement in 1% of the cases. 7", "output": {"entities": {"named_data": [{"text": "GLSS"}], "descriptive_data": [{"text": "surveyed DHS clusters"}], "vague_data": []}}}
{"input": "is the World Bank's Country Policy and Institutional Assessment (CPIA) database, which rates environmental policies and institutions on a numerical scale of 1 (the lowest) to 6. For this exercise, we reverse the scaling (1 becomes the highest) and normalize the ratings so that countries with the greatest problems score 100. To proxy the scale of the problems confronted by environmental institutions, we compute the mean value of our five thematic indicators (global emissions, pollution, natural resource degradation, biodiversity threats, water-related problems). [5,6] To assure equal weighting 4 Our index of demand pressure also provides a useful proxy for economic damage from drought conditions. We are indebted to our colleagues in the Bank’s Middle East / North Africa region for this observation. 5 While the CPIA ratings provide useful information for comparing institutional needs, they are not sufficient for judging investment priorities because they do not account for differences in the scale of environmental problems faced by a country's institutions. If Brazil and Bhutan receive the same CPIA rating, for example, ignoring their scale difference will lead to assignment of identical lending in the optimization model. 6 We recognize that an equal-weighted index is only one of numerous plausible indicators", "output": {"entities": {"named_data": [{"text": "Country Policy and Institutional Assessment (CPIA) database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "26.9 percent in Markazi, and 46 percent in Djibouti-Ville. [10] Livelihood opportunities in refugee villages are scarcer than in the capital, exacerbating food security challenges, and even highly educated refugees struggle to find employment, without a command of French. Refugees’ **access to finance** is limited by their lack of inclusion in the national ID system; underdeveloped credit markets; and limited awareness of their right to work. Their self-sufficiency is limited by a lack of access to vocational training, business development support services, and decent jobs [11] . [6 UNHCR (2023), Republic of Djibouti - Country Summary as at 30 June 2023](https://www.refworld.org/reference/countryrep/unhcr/2024/en/147860) 7 UNHCR (2025), Djibouti Education Statistics for Refugees; Ministry of Education and Vocational Training of the Republic of Djibouti (2024), [Annuaire Statistique 2023/2024; World Bank (2024),](http://www.education.gov.dj/index.php?option=com_k2&view=item&id=631:annuaire-statistique-2023-2024&Itemid=784&lang=en) [Djibouti: Giving Refugee Children a Chance to Go To School](https://www.worldbank.org/en/news/feature/2024/01/11/djibouti-giving-refugee-children-a-chance-to-go-to-school) 8 World Bank (2024), [Djibouti: Giving Refugee Children a Chance to Go To School](https://www.worldbank.org/en/news/feature/2024/01/11/djibouti-giving-refugee-children-a-chance-to-go-to-school) 9 The Ministry of Health and UNHCR signed a cooperation agreement in 2018 for the inclusion of refugees in the national health system 10 Government of Djibouti (2024), Stratégie Livelihoods et Inclusion Economique Djibouti 2024 – 2028 11 UNHCR, African Development Bank Group, IGAD, EAC (2024), Regional Report Draft:", "output": {"entities": {"named_data": [{"text": "Djibouti Education Statistics for Refugees"}], "descriptive_data": [], "vague_data": []}}}
{"input": "in housing prices (Daniel, Florax, and Rietveld 2009). In Ho Chi Minh City, for instance, qualitative surveys suggest flood-prone areas can be much cheaper than non-flood-prone areas for the same quality of accommodation (World Bank and Australian AID 2014). Using a household survey in Dar es Salaam, Tanzania, Erman et al. (2019) find that flood-prone dwellings are valued at 30 percent less on average than safe ones. Reduced housing prices, then, make it possible for poor people to access housing opportunities that could be out of reach in the absence of risk (Husby et al. 2015). In developing countries with informal markets, land scarcity can be particularly acute and land markets function poorly (Durand-Lasserve, Selod, and Durand-Lasserve 2013). In these places, it may not be the prices that push poor people into risky places but simply the availability of land with appropriate access to jobs and services. Informal settlements are often located in hazard-prone locations such as on hillsides, close to riverbanks, or near open drains and sewers—Pune (India), Dhaka, Caracas, Rio de Janeiro, and Mumbai have many such settlements (Lall and Deichmann 2012; Lall, Lundberg, and Shalizi 2008). 3", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "household survey in Dar es Salaam"}], "vague_data": [{"text": "household survey"}]}}}
{"input": "farming, either for their own production or as hired workers or sharecroppers on host community land. 4 World Bank (2023). _World Development Report 2023: Migrants, Refugees, and Societies._ Washington, DC: World Bank at p. 208. 5 Poverty rates in refugee-hosting districts during the COVID-19 crisis ranged from 37.7 percent in rural areas to 20.5 percent in urban areas; the overall national poverty rate was 33.2 percent. Headcount poverty rates averaged 39.9 percent in the Northern Region, 26.6 percent in the Western Region, and 20.4 percent in the West Nile. (World Bank. 2022. _Uganda Poverty Assessment Overview – Strengthening Resilience to_ _Accelerate Poverty Reduction in Uganda)._ 6 A study commissioned by the Norwegian Refugee Council revealed that between 2016-2020, 40.3 percent of refugees self-settled in the urban centers of Adjumani, Koboko, Hoima and Mbarara. Steady flows have continued into these locations and Arua, another secondary city, over the last four years: see Office of the Prime Minister and UNHCR (2024) _Uganda Urban Response Strategy 2024-2029_ . 7 The definition used is canopy height >5m. Global Forest Watch 8 Compounded by the fact that refugee settlement population density is typically ten times the national average: World Agroforestry Center, 2024. 9 Gianvenuti, A.,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Economics of Disasters and Climate Change and can be identified from the results of this paper. An important constraint is that for such development to be feasible, they should be paired with transportation investments, which maintain access to the city center where opportunities are presented (World Bank 2015). Despite the potential of risk-sensitive land-use planning, resettlement is the major ex-ante hazard adaptation mechanism employed in Vietnam currently, especially in the Mekong Delta. While such policies can reduce exposure, policy design is critical to ensure the livelihoods of the poor are supported. For instance, surveys in Tan Chau district suggests the resettlement policy enacted in 2002 may have made households worse-off: inadequate financing resulted in households paying for their new settlements out-of-pocket; many households who were farmers and fishers did not have adequate land, transportation and market access, and inadequate livelihood support was provided to them (World Bank 2016). Where resettlement policies are enacted, it is imperative that such policies are paired with livelihood and financing support. Beyond strategies to reduce exposure, other policy options to reduce vulnerability to improve households’ ability to adapt may warrant increased attention. Strategies such as government subsidies for household-level flood protection (like raising of floors),", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "To show the robustness of these results, we have tried three alternative strategies for each of the outcomes. In row 2, we drop the sample that lives 20 to 40 km away, since they might be affected by the mine; in row 3, we drop the sample that was surveyed two years prior to mine opening; in row 4, we add closest mine fixed effects; and in row 5 we cluster on the closest mine. The coefficients do not change much, even if some magnitudes become bigger and the estimates more significant. However, as in the results using DHS data, these estimates are not precisely measured – few are statistically significant because the standard errors appear large. Women are 7.4 to 10.4 percentage points more likely to work in service or sales if they live close to a mine (depending on the estimations in panel A columns 4, only one statistically significant estimate). Women close to mines are 2.5 to 2.6 percentage points more likely to work in mining (only one statistically significant estimate). Men, on the other hand, (results shown in panel B of table 12), are significantly more likely to work in mining, and insignificantly less in agriculture", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "DHS data"}]}}}
{"input": "Middle East & North Africa Latin America & the Caribbean South Asia Middle East & North Africa Latin America & the Caribbean East Asia & the Pacific South Asia Middle East & North Africa Latin America & the Caribbean **Figure 2. Distribution of lost wetlands by types of wetlands across regions, for a 1m SLR** We have also presented the percentage of wetland types at risk by region in Figure 2, which is revealing. Once again, it is apparent that among the various regions, EAP faces the greatest risk of overall loss of wetlands: for a 1 m SLR scenario, 61% and 71% of vulnerable freshwater marsh and GLWD Coastal Wetlands are in EAP. On the other hand, 65% of saline wetlands at risk is in MENA. After EAP, MENA represents the second largest proportion of GLWD Coastal Wetlands at risk (15%). LAC also represents a significant share (18%) of vulnerable freshwater marshes. 12", "output": {"entities": {"named_data": [{"text": "GLWD Coastal Wetlands"}], "descriptive_data": [], "vague_data": []}}}
{"input": "The second distinctive feature of this exercise is its incorporation of compatible data from different sources. For the period since 1960, we use georeferenced track information on major cyclones striking Bangladesh from the Bangladesh Meteorological Department (BMD). Equivalent information for the Indian coastal region comes from the India Meteorological Department (IMD). For cyclones prior to 1960, we add information from the IBTrACS database maintained by the Global Data Center for Meteorology, operated by the US National Oceanic and Atmospheric Administration. The IBTrACS data for the Indian Ocean have been provided by meteorological institutions in the region. We also use them for a few post-1960 cyclones that are not included in the data available to us from BMD and IMD. We ensure cross-source compatibility by using WMO standards for the two commonly-available measures of storm strength: maximum wind speed (measured in knots (kt)) and radial distance from a storm’s center to its zone of maximum wind speed. We employ a standard IMD storm classification based on maximum wind speed intervals in kt: (Cyclonic Storm (CS) [34-47 kt]; Severe Cyclonic Storm (SCS) [48-63]; Very Severe Cyclonic Storm (VSCS) [64-119] and Super Cyclonic Storm (SuCS) [120+]. We have excluded all storms rated as", "output": {"entities": {"named_data": [{"text": "IBTrACS database"}], "descriptive_data": [{"text": "georeferenced track information on major cyclones striking Bangladesh"}], "vague_data": []}}}
{"input": "of forced displacement, covering refugees and host communities. **III.** **PROJECT IMPLEMENTATION** **A.** **Institutional and Implementation Arrangements** 55. **The project will retain the same arrangements as Phase I**, but with enhanced coordination and collaboration mechanisms under OPM’s DoR. OPM will implement DRDIP II at the national level through a PIST, which will provide technical guidance and support to implementing districts and communities. The PIST will comprise technical experts who will be recruited or seconded from government agencies. Additional expertise can be contracted where necessary. In line with GoU objectives to streamline implementation units within IAs, the PIST will share some technical specialists to support DRDIP II and NUSAF IV. This will reduce costs and enhance coordination on the ground. 56. **The PIST will work in collaboration with OPM structures and under the guidance of an inter-agency PSC**, which will include representatives from the following agencies: Ministry of Finance, Planning, and Economic Development (MoFPED), IG, Ministry of Energy and Mineral Development, Ministry of Works and Transport, Ministry of Water and Environment, Ministry of Local Government, Ministry of Gender, Labor, and Social Development, Ministry of Education and Sports, Ministry of Health, National Environment Management Authority, Private Sector Foundation of Uganda, DoR, CRRF Secretariat,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "reflect the same rank-order as the lending opportunities in Appendix 1. **9. Interpretation of Results: Ethiopia vs. Nigeria** We provide an illustrative interpretation of our results by comparing the cases of Ethiopia and Nigeria in Table 9.1. Both have been among the Bank’s top borrowers in Sub-Saharan Africa: From 1998-2003, Nigeria borrowed $912 million and Ethiopia borrowed $1,381 million. Among the 48 Sub-Saharan countries, Nigeria’s overall environmental problem indicator ranks first and Ethiopia’s second. Both countries are in the midrange for the OED project success rate (45% for Nigeria; 65% for Ethiopia). After adjusting for success rates, Nigeria’s optimal lending is $144 million and Ethiopia’s is $128 million. 25", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "assumptions of coastal protection, comparison of the prior research with our estimates proved to be difficult. ##### **Conclusion** Coastal wetlands will decline with rising sea level. In this paper, we have quantified the vulnerable freshwater marsh, swamp forest, GLWD Coastal Wetlands, and brackish/saline wetlands taking into account the exposure of wetlands to 1 m SLR and the estimated capacity of the coastline to retreat and for coastal wetlands ecosystems to migrate inland as the 25 Anthoff et al. (2010) has not reported exposure estimates of coastal wetlands to SLR. 20", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "fuel combustion (CO2), land-use change (CO2) and other sources (methane (CH4), nitrous oxide (N20), hydrofluorocarbons (HFC’s), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6)). We draw our emissions estimates from the World Resources Institute’s Climate Analysis and Indicators database. [3] Our estimate of pollution damage is total DALY (disability-adjusted life year) losses from air and water pollution. We draw our DALY estimates from recent research 2 The supporting database and an accompanying atlas can be downloaded from the Environment Department (lnweb18.worldbank.org/ESSD/envext.nsf/41ByDocName/Environment), or from the Development Research Group (www.worldbank.org/nipr). 3 The World Resources Institute’s Climate Analysis and Indicators database is available online at http://cait.wri.org. 4", "output": {"entities": {"named_data": [{"text": "Climate Analysis and Indicators database"}], "descriptive_data": [{"text": "the supporting database"}], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) days after the end of each semester. The IFRs will contain: a statement of sources and uses of funds (with expenditures classified by category of expenditures, source of funds) and cash balance; a statement of budget execution per component and subcomponent; and a reconciliation of the Designated Account. The formats of the IFRs and annual financial reports will be included in the POM. **Flow of Funds- Disbursement.** 6. The disbursement methods that may be used for the withdrawal of the proceeds of the loan will include reimbursement; advance; and direct payment. Under the advance method, the project will have access to a Designated Account (DA) to be used exclusively for deposits of loan proceeds in the Central Bank of Costa Rica for eligible expenditures. The deposits into the DA will flow to a specific account into the Borrower ́s Treasury Single Account - TSA ( _Sistema de Cuenta del Sector Publico, SCSP_, by its initials in Spanish), assigned to the Project and managed by MEP. As needed, the PIU will request the MoF to transfer funds from the DA to the project operational account which will be opened in the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "age migrant married cohabiting divorced fertility woman partner active*mine 0.263 0.028 0.025 0.018 -0.003 0.030 -0.036 -0.003 (0.510) (0.042) (0.027) (0.029) (0.017) (0.115) (0.031) (0.030) _Note:_ Robust standard errors clustered at the DHS cluster level in parentheses. All regressions control for year and district fixed effects, urban dummy, age (not column 1), and years of education (not columns 6 and 7). Active is active status of mine in the survey year. *** p<0.01, **p<0.05, *p<0.1. **5.1 Employment outcomes** Using the difference-in-differences approach (equation 1), we estimate results on occupation, child health, and inequality. First, panel A of table 4 indicates that women in active mining communities ( _active*mine_ ) are insignificantly more likely to work in service and sales and less in agriculture, and 1.7 percentage points less likely to work as professionals (statistically significant). There is no change in the likelihood that she is not working. These 5 categories stem from the same occupational variable in the DHS data, and are mutually exclusive. The surveyed individual is told to report their main occupation. The coefficients can therefore be interpreted as relative increases of each specific sector. Women are more likely to earn cash for work, and the likelihood increases", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "DHS data"}]}}}
{"input": "future ice-sheet instability and rapid sea-level rise. _Science_, 311,1747-1750. Pfeffer, W. T., Harper, J.T., and S. O’Neel. 2008: Kinematic constraints on glacier contributions to 21st-century sea-level rise. _Science_, 321, 1340-1343. Rahmsdorf, S. 2007. A semi-empirical approach to projecting future sea-level rise. _Science_, 308, 368-370. Semeniuk, V. 1994. Predicting the effect of sea-level rise on mangroves in Northwestern Australia. _Journal of Coastal Research_, 10, 1050-1076. Sun,G., McNulty, S.G., Amatya, D.M., Skaggs, R.W., Swift, L.W., Shepard, P., and H. Riekerk, 2002. A comparison of watershed hydrology of coastal forested wetlands and the mountainous uplands in the Southern US. _Journal of Hydrology,_ 263, 92-104. Titus, J.G. 1988. _Sea Level Rise and Wetland Loss: An Overview_ . [http://epa.gov/climatechange/effects/downloads/toc_wet_chap1.pdf](http://epa.gov/climatechange/effects/downloads/toc_wet_chap1.pdf) Tol, R.S.J. 2007. The Double Trade-off between Adaptation and Mitigation for Sea Level Rise: An Application of FUND. Mitigation Adaptation Strategy Global Change. 12:741-753. Vafeidis, A.T.; Nicholls, R.J.; McFadden L.; Tol, R.S.J.; Hinkel, J.; Spencer, T.; Grashoff, P.S.; Boot, G., and Klein, R.J.T. (2008) A new global coastal database for impact and vulnerability analysis to sea-level rise. Journal of Coastal Research, 24(4), 917–924. 24", "output": {"entities": {"named_data": [{"text": "global coastal database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "to implement the selected subprojects, together with capacity-building measures. 32. **The Phase II design responds to lessons learned from Phase I as follows** : (a) some activities, such as drip irrigation systems and fish ponds, are too technically complex for communities to manage, so they will be dropped; (b) due to sustainability concerns about community-managed woodlots, tree planting activities will only support pre-existing groups with proven management capacity; (c) IP contract payments will be restructured to provide incentives for quality and to ensure they facilitate community-led implementation rather than implement activities themselves; (d) the subproject budget ceiling will be increased to reflect inflation and ensure sufficient scale to generate environmental impacts; and (e) due to the major investments in electricity provision and clean cooking under the World Bank-financed Electricity Access Scale-up Project (P166685), including in RHDs, DRDIP II will discontinue support for access to renewable energy, except for the provision of renewable energy and/or improved cooking systems for public institutions, which will be incorporated into Component 1. Component 2 will be organized around two sub-components, as described below. 33. _Sub-component 2.1: Restoration of Degraded Ecosystems (US$20 million)._ The DRDIP II Environmental and Social Assessment (ESA) carried out in 2024 identified", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "large-scale operations may be geographically correlated. Assuming that the start of a large scale mine does not affect the likelihood or viability of artisanal and small-scale mining, it is not a threat to our identifying assumptions. However, should ASM respond to large-scale activities, either by increasing or decreasing activity in the close geographic area, we will end up estimating the impact of these sectors jointly. In a later stage, should the opportunity arise, we encourage researchers to try to disentangle the effects of small-scale and large-scale mining. **3 Data** To conduct this analysis, we combine different data sources using spatial analysis. The main mining data is a dataset from InterraRMG covering all large-scale mines in Ghana, explained in more detail in section 3.1. This dataset is linked to survey data from the DHS and GLSS, using spatial information. Geographical coordinates of enumeration areas in GLSS are from Ghana Statistical Services (GSS). [2] Point coordinates (global positioning system [GPS]) for the surveyed DHS clusters [3] allow us to match all individuals to one or several mineral mines. We do this in two ways. First, we calculate distance spans from an exact mine location given by its GPS coordinates, and match surveyed", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "survey data from the DHS and GLSS"}, {"text": "dataset from InterraRMG"}], "vague_data": []}}}
{"input": "weather station in this .75°×.75° grid, the observation is given a weight of 1.5. If there is a rainfall station within the .25°×.25°grid, the observation is given a weight of 2. The weighted results do not differ significantly from the unweighted results. 12 Note that while it is reasonable to think that village-specific characteristics (such as village size) may have an effect on village-level insurance take-up, village-level covariates are not included in the regression. When the regressions are run with the village characteristics from the 2005 Indian census, the coefficients of interest do not change significantly. Also, most village-level characteristics had insignificant coefficients, with the exception that a more literate population was correlated with higher take-up. Since village-level coefficients were only available for around 50 percent of the villages, these variables are not included in the main specifications.", "output": {"entities": {"named_data": [{"text": "2005 Indian census"}], "descriptive_data": [], "vague_data": []}}}
{"input": "analyses to improve their capacity to develop climateresilient business plans. Component 3 will also expand adaptation capacity by improving drainage and water harvesting to better manage flooding and landslide risks. It will also enhance septage management to reduce the risk of soil contamination and associated health risks in the event of flooding. 73. **Citizen Engagement (CE)** . The project design builds on existing district planning mechanisms. Component 1 subprojects will be identified through the regular DDS process, while strengthening stakeholder engagement through additional consultations with refugees, host community members and humanitarian partners. CE will be measured through results indicators that track whether Jya Mbere II investments align with the needs and priorities of beneficiaries. A new feature in Phase II will be Iterative Beneficiary Monitoring (IBM), whereby a large sample of project beneficiaries will be surveyed by phone to track, among other things, satisfaction with citizen engagement processes and the project as a whole. MINEMA conducted public and stakeholder consultations across the project target areas to gather feedback on the proposed activities, address concerns, and explore ideas to mitigate potential adverse impacts on socio-economic activities and livelihoods. The project’s stakeholder engagement plan, built on inclusive consultations, incorporates a comprehensive grievance", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Policy Research Working Paper 8316 ### **Abstract** Recurrent cyclonic storms in the Bay of Bengal inflict mas sive losses on the coastal regions of Bangladesh and India. Information on occurrences and severities of cyclones is necessary for understanding household and community responses to cyclone risks. This paper constructs a georeferenced panel database that can be used to obtain such information for Bangladesh, West Bengal, and Odisha. Cyclone strike locations and impact zones are analyzed for several historical periods between 1877 and 2016. The findings indicate that although the median location has shifted eastward, there is a marked variability in location, especially after 1960. Impacts also have varied considerably within and across zones over time, with the highest-impact zones in northern Odisha and the Sundarbans region of West Bengal. The pronounced spatial and temporal variation in cyclone impacts will provide robust controls for comparative research on household and community adaptation to cyclones in the study region. The methodology developed in the paper is general and could be expanded to an arbitrarily large set of coastal locations. This paper is a product of the Environment and Energy Team, Development Research Group and the Environment and Natural Resources Global Practice Group. It is", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "georeferenced panel database"}], "vague_data": [{"text": "georeferenced panel database"}]}}}
{"input": "Japan (HIC) India (LMIC) Germany (HIC) Netherlands (HIC) Vietnam (LMIC) Indonesia (UMIC) Thailand (UMIC) Pakistan (LMIC) South Korea (HIC) 0 500 1000 1500 2000 2500 USD millions _Figure 13. Top 10 countries: Economic value at risk, computed as exposure headcount multiplied by_ _subnational income per capita. Note: no subnational income data are available for several countries,_ _including China._ 17", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "subnational income data"}]}}}
{"input": "quarter confirm that 38% of those having to leave their accommodation was on account of the accommodation closing, compared to only 22% in the last quarter of 2023. ## 39% Consider accommodation an urgent need facilities across seven regions [1] highlighted the challenges in accessing sustainable and affordable housing, including the psychological distress of a relocation to rented housing by some Ukrainian refugees. This was found to be a particular concern amongst elderly persons, persons with disabilities, single mothers, persons with serious medical conditions and their carers. Many expressed reluctance to relocate, citing fatigue and fear of the unknown; some also appreciated their current living conditions and sense of community support, which they prefer over individual housing. The motivation and/or possibility of refugees to relocate to standard housing varied significantly based on income and employment status, Czech language skills, vulnerabilities related to disabilities, age, family size and support from government services or informal networks. The focus group discussions also underscored the precarious financial situation of many refugees, including those engaging in low-paid work below their qualifications, which creates a barrier for relocations to rented housing. 78% of respondents mentioned that they would not be able to cover costs of rented", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "retreat and for coastal wetlands ecosystems to move (or migrate) inland as the coastline is receding. Attempts have also been made to estimate the economic loss, which may be associated with adversely impacted wetlands. Our estimates indicate that a 1 m rise in sea level would lead to a loss of present coastal wetland stocks of 60% or more, depending on wetland type. Human activity is generally 8 Further development in coastal areas may also close off wetland migration. 9 Historically, mangroves have shown considerable resilience to adapt to fluctuations in sea-level rise (Alongi, 2008; Erwin, 2009; Gilman et al., 2006). 10 Coastal wetlands in this analysis are defined as the following wetland types in a low elevation (with elevation 10 m or less from sea level) zone: freshwater marsh, swamp forest, GLWD coastal wetlands and brackish/saline wetlands, as delineated in the Global Lakes and Wetlands (GLWD-3) database. See the data section for details. 11 The IPCC’s Fourth Assessment Report (AR4) projects increased SLR between 0.18m and 0.59m across various emission scenarios over the next 100 years. However, this range has been criticized by many experts as being too conservative and not sufficiently reflective of the large uncertainty pertaining to", "output": {"entities": {"named_data": [{"text": "Global Lakes and Wetlands (GLWD-3) database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "0.127 0.186 0.162 0.154 Organization done by village leaders 0.264 0.237 0.276 0.222 0.165 0.261 0.285 Organization done by village representatives 0.059 0.059 0.053 0.089 0.064 0.061 0.053 Organization done by village assembly 0.121 0.112 0.138 0.111 0.119 0.130 0.132 Organization done by village econ. organizations 0.083 0.059 0.099 0.096 0.064 0.096 0.093 Organization done by township or above 0.472 0.533 0.434 0.481 0.587 0.452 0.437 Actual measurement done by village leaders 0.085 0.086 0.093 0.059 0.111 0.078 0.080 Actual measurement by village representatives 0.554 0.517 0.583 0.615 0.407 0.609 0.567 Actual measurement done by village assembly 0.042 0.033 0.040 0.022 0.056 0.026 0.053 Measurement by village econ. organizations 0.227 0.192 0.252 0.267 0.241 0.209 0.247 Actual measurement done by township or above 0.093 0.172 0.033 0.037 0.185 0.078 0.053 **Disputes** Any disputes encountered 0.549 0.187 0.497 0.348 0.226 0.250 0.300 ... if yes, no. of disputes 14.850 6.429 10.987 9.745 6.292 9.759 8.111 ... disputes could not be resolved by village 1.248 0.074 0.724 0.894 0.042 1.690 0.933 leaders **Results** Contract now longer than 30 years 0.987 0.993 0.980 0.977 1.000 0.983 0.993 Contract now permanent 0.717 0.792 0.497 0.481 0.848 0.861 0.860 _Source:_ Own computation from 2014 Chengdu", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Economics of Disasters and Climate Change There is a significant amount of uncertainty with regard to how much sea level will rise. For that reason we model three future climate scenarios per return period: a low, medium, and high scenario (Table 1), using estimates from the IPCC (IPCC 2014; IPCC 2007). For the fluvial and pluvial hazards, future climate scenarios were not explicitly simulated owing to the complexity and considerable uncertainties that arise (Smith et al. 2014). [2] Although robust modeling of the magnitude of future extreme rainfall is not yet possible, heavy rainfall is expected to increase in a warmer climate, owing to the increased water holding capacity of the atmosphere. Therefore instead of a direct modeling approach, future climate scenarios were inferred by taking flood hazard maps derived under current climate conditions for different return periods, and using them as a proxy for future climate scenarios. The return period hazard maps used for each of the future scenarios are outlined in Table 2. Although simplistic, this method allows areas that may be impacted by increasing riverine and extreme rainfall driven flooding to be identified. Clearly there are some significant assumptions and uncertainties arising from this method. However, given", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "flood hazard maps"}], "vague_data": []}}}
{"input": "financed under DRDIP II and ensure they are aligned with and incorporated in the District Development Plan. 59. **DRDIP II will be implemented using the CDD approach, whereby communities identify, prioritize, and** **implement subprojects themselves,** guided by the Sub-County Implementation Support Team, Sub-County Executive Committee, Sub-County Technical Planning Committee, Parish Development Committee, and Assistant Commandant. At the community level, implementation will be carried out by committees that the project will establish and train, including a Community Project Management Committee (CPMC), Community Procurement Committee (CPC), Community Monitoring Group, Grievance Redress Committee (GRC), and Refugee Welfare Committee (RWC) in the settlements. The project will ensure gender equity in the membership of the various committees. Implementing Partners (component 2) and TSPs (component 3) will be hired to support community capacity for subproject identification, planning and implementation. A Community Operations Manual will be incorporated into the PIM to detail all steps in the CDD process. 60. **The Inspectorate of Government (IG) will remain engaged in implementation arrangements** at the national and local government level to strengthen transparency and accountability and to prevent and respond to corruption. **B. Results Monitoring, Evaluation, and Verification Arrangements** 61. **M&E System.** OPM will have overall responsibility for M&E, including", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Socio-economic Inclusion of Refugees & Host Communities in Rwanda Project Phase II (P509677) 33. _Sub-component 2(c): Partial Credit Guarantee Scheme (US$860,000)._ Despite the financing provided through the MG scheme, many financial institutions in Rwanda remain hesitant to lend to creditworthy refugees due to the lack of an established credit history and insufficient collateral. The GoR’s Business Development Fund (BDF) has a partial credit guarantee (PCG) scheme to respond to the collateral challenge. While refugees are eligible for the scheme, few either access it or are aware that it exists. Building on the experience of the ongoing Access to Finance for Recovery and Resilience project (P175273) in Rwanda, which is partly implemented by BDF, the sub-component will support and facilitate the provision of individual PCGs to refugees to offset PFI collateral requirements or portfolio guarantees to cover credit losses associated with loans made to refugees. 34. **BDF will implement the sub-component.** A full Financial Intermediary Assessment of BDF was conducted as part of project preparation, full details of which will be included in the Project Implementation Manual. [22] Given that capital needs will be provided by BDF, funding from Jya Mbere II will only be required for BDF’s", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "# **PROTECTION BRIEF** **CZECHIA** ### JULY- SEPTEMBER 2024 ## Operational Context Based on the number of Ukrainian refugees who applied for an extension of Temporary Protection in 2024 (320,000), the figures of Temporary Protection holders in Czechia, including new arrivals, were updated to **384,558** people as of **29 September 2024**, compared to 373,745 at the end of 2023 (source: Ministry of the Interior). This report presents an overview of refugees’ profiles as well as main findings regarding protection risks and priority needs of refugees from Ukraine in Czechia. The brief is based on the analysis of **438 Protection Monitoring interviews** conducted with refugees from Ukraine in all the 14 regions as well as findings from focus group discussions in the third quarter of 2024. ## Key Figures 384,558 71% Temporary Protection holders in Czechia as of 29 September 2024 [1] Temporary Protection holders in Czechia of Temporary Protection holders are women as of 29 September 2024 [1] and children [2] ## 98% 34% of Protection Monitoring respondents are Temporary Protection holders ## 34% of Protection Monitoring respondents are of respondents consider accommodation as Temporary Protection holders their highest priority need ## 67% 29% ## 29% of working age respondents are", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "UNHCR Czechia continued to conduct Protection Monitoring while also consulting different groups of refugees though focus group discussions on protection risks and priority needs. Specific challenges in accessing rights were reported. The key findings are highlighted below. ### Protection Risk I The number of respondents reporting a lack of critical documentation increased from 28% to 32% in the first quarter of 2024 compared to the last quarter of 2023. The increase was mainly in relation to obtaining or renewing biometric passports (85%) and internal passports (19%), which impacted the possibility to move freely, to access basic services as well as work and education. Various factors hinder refugees’ access to documentation, including associated processing fees, long waiting periods, unavailability of services or lack of information on procedures. 10% of the respondents also reported facing challenges in registering births, deaths, marriages, and divorces, and obtaining corresponding documents. UNHCR / March 2024 2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "1.7 **Labor inputs** Male family labor dummy 68.6 71.0 63.4 67.4 69.8 64.3 Female family labor dummy 92.1 92.0 92.3 94.1 94.3 93.7 Hired labor dummy 30.2 30.5 29.7 27.7 25.0 31.1 Exchange labor dummy 17.6 16.9 19.3 16.4 13.6 20.1 Number of male family labor days per acre 20.4 19.7 21.8 20.2 19.2 21.4 Number of female family labor days per acre 44.5 40.1 54.7 48.9 42.4 57.2 Total family labor days per acre 64.9 59.8 76.5 69.0 61.6 78.6 Total exchange labor days per acre 2.7 2.4 3.3 2.5 1.6 3.6 Total family and exchange labor days per acre 68.1 63.0 79.8 72.3 64.6 82.3 Hired labor days per acre 3.2 3.2 3.4 3.3 3.0 3.7 Total labor days per acre 70.8 65.4 83.2 74.8 66.2 85.8 Number of observations (parcels) 18220 12658 5562 6628 3720 2908 _Source:_ Own computation from 2005/06 UNHS III _Note:_ Unit of observation is a parcel (under crop) in a given season. Thus the same parcel could provide two observations if cultivated in both seasons in the reference period (July 2004 – June 2005). 19", "output": {"entities": {"named_data": [{"text": "2005/06 UNHS III"}], "descriptive_data": [], "vague_data": []}}}
{"input": "from the national level to higher local governments (districts, cities, urban centers), to lower local governments (sub-counties), and to the communities. The FM assessment indicated that the arrangements satisfy the World Bank’s minimum requirements under Investment Project Financing (IPF) policies and directives. The FM residual risk rating is Substantial. 73. **Successful implementation of the project requires strong FM arrangements at the national, district, urban** **center (local government), and community levels.** CAOs and Town/City Clerks and CFOs are the key players for districts and urban centers in managing and disbursing funds to communities and ensuring accountability of project resources. DRDIP I established robust accountability mechanisms and operated a ring-fenced FM system. Phase II will use the same systems, including the existing MIS to record project data, processes, accounting, and reporting. Key risks identified Page 21", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "comments. All remaining errors are my own. A supplemental appendix to this article [is available at https://academic.oup.com/wber.](https://academic.oup.com/wber) 1 CIA World Factbook: India; Indiastat.com. © The Author 2016. Published by Oxford University Press on behalf of the International Bank for Reconstruction and Development / THE WORLD BANK. All [rights reserved. For Permissions, please e-mail: journals.permissions@oup.com](mailto:journals.permissions@oup.com)", "output": {"entities": {"named_data": [{"text": "CIA World Factbook"}], "descriptive_data": [], "vague_data": []}}}
{"input": "infiltrators‖ ( _mistaneniavoda_ ) in an effort to associate refugees with a threat to the employment prospects of Israelis. As one academic interviewee observed, the ongoing primacy of this term demonstrates ―the success of agents within the [governmental] institutions to inject this discourse and create a sort of panic‖ characterised by a ―takeaway feeling – they will come here, take what we have, and change this place‖. This ―takeaway feeling‖ partly explains the urgency of an MK who suggested various security technologies that allowed Israel to act in a middle zone between violence and doing nothing: ―...preventing entrance, a fence, guard dogs, sensors...arrivals will not be answered and received, we will not let them in‖...‖Between killing and not acting there is prevention, [and the state should act upon it] if Israel wishes to survive‖. However, any discussion which touches upon security-related issues must also consider the close triangular relationships between African refugees, Palestinian refugees and Israeli security considerations. In the Israeli context, the term ̳refugee‘ is traditionally associated with two types of refugee: Jewish holocaust survivors who fled Europe and the Palestinian refugees who were displaced as a result of the 1948 War. The state fears that recognizing African asylum", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "accordance with the Ministry of Interior’s decision. So far, authorities have registered and issued 30,000 cards, but their resources have quickly depleted and they are running out of resources to continue registration. UNHCR has been requested to support this initiative, as resource shortages risk preventing further registration, exposing refugees to potential deportation and increased GBV risks. Approximately 40,000 vulnerable individuals will be directly impacted, including women, children, and other vulnerable groups among the Sudanese refugee population. **Shelter and Core Relief Items** Overcrowded and inadequate shelters heighten the risk of disease transmission and compromise the safety and dignity of refugees, with current shelter solutions falling below minimum humanitarian standards. In-kind support will be provided to Sudanese refugees with heightened risk and vulnerability if funding is available. **Education** Only one-third of primary school-aged children and 5% of secondary school-aged children in Mbera refugee camp are enrolled due to lack of financial means, documentation, and schools. The situation is equally dire outside of the camp in Hodh Chargui, where the enrolment rate is only 6%. School kits, capacity building and salaries for teachers, and support to transition from the Malian to Mauritanian curriculum will all increase access to education for some 45,000 refugee", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "limited understanding of the importance of climate adaptation for their livelihoods and there is a need for better government aid after flood events (Le Dang et al. 2014; McElwee et al. 2017). In urban areas, private adaptive capacity may be even lower, resulting in an increasing need for urban planning to incorporate climate risk dimensions (Liao et al. 2016). While adaptation is not a focus of this paper, the uncertain and growing impacts of flood risk found in this paper indicate more attention is warranted to design effective adaptation policies. Data To examine population and poverty-specific exposure to floods, we employ spatial data defining flood hazard and a number of socioeconomic characteristics representing poverty and population density. Flood Hazard Data Flood Hazard Maps for Vietnam Developed for this Study For this study, we developed flood hazard maps representing riverine, flash-flood and coastal flood hazards for Vietnam. These flood hazard maps estimate the inundation depth at a grid cell level of 3 arc-seconds, (~ 90 m) and provide coastal surge hazard layers, along with pluvial and fluvial layers. The maps provide information on the extent and depth of flood hazard for a specific location. For the coastal component, we explicitly model", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "spatial data defining flood hazard"}], "vague_data": [{"text": "spatial data"}]}}}
{"input": "The audit reports for 2022/2023 that had an unqualified (clean) audit opinion were for Isingiro, Kamwenge, and Obongi districts. 2023/2024 audit reports were not available on the Auditor General’s website. The audit reports for 2023/2024 that had an unqualified (clean) audit opinion were for Adjumani, Kikuube, Kiryandongo, Koboko, Kyegegwa, Lamwo, Madi Okollo, Obongi, Terego, Yumbe, Amuru, Bundibugyo, Kanungu, Kisoro districts. Others were Arua City, Gulu City, Kitgum Municipality, Koboko Municipality, and Mbarara City. In the case of Ntoroko, this was due to understating value-added tax receivables, unrecognized prepayments to contractors, and not recognizing advance payments. Page 22", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Figure 21. Share of total population that is exposed to significant flood risk and living in poverty at_ _$5.50/day_ **Relationship between population exposure and other variables.** The relationship between poverty and flood risk exposure is driven by multiple partly opposing forces. As section 2 has outlined, country-level evidence has demonstrated that areas with higher flood risks (such as coastal zones) can offer economic opportunities, thus resulting in lower poverty rates; yet at the local level (e.g. within coastal towns), lowincome households can be driven into low-cost and high-risk neighborhoods. This means that – depending on the resolution of analysis and country-specific geographic and economic characteristics – the relationship between poverty and flood exposure could be either positive or negative. The global-level data used in this study only offer a limited view on this question. Figure 22 illustrates the relationship between average income levels and flood exposure rates for the 2,260 sub-national regions for which data are available. The figure suggests that regions with high flood-exposure tend to have lower income levels on average, only dedicated country-level analysis can assess this question conclusively – for instance based on household survey data. 22", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "household survey data"}]}}}
{"input": "South Asia Middle East & North Africa Latin America & the Caribbean **Figure 3. Regional distribution of economic losses** ###### **III.4 Prior research on impacts of SLR on coastal wetlands** The papers most immediately related to this analysis are those of Nicholls at al. (1999), Nicholls (2004), McFadden et al. (2007) with estimates of exposure of coastal wetlands to SLR, and Tol (2007), Anthoff et al. (2010) on valuation of wetland losses due to SLR. It should be noted that Nicholls (1999) and Nicholls (2004) are based on wetland losses derived from the Global Vulnerability Analysis (Hoozemans et al. 1993) [23] - “a first-order perspective on wetland loss rates with incomplete coverage and wetland losses controlled only by tidal range and accommodation space” - as pointed out by McFadden et al. (2007). Nicholls et al. (1999) estimated that a 38 cm rise in global sea level from 1990 to the 2080s will lead to an approximate 22% loss of the coastal wetlands, [24] and 46% of the coastal wetlands would be lost if the sea level rises by 1 m. Nicholls (2004) further estimated losses of wetlands under various greenhouse emissions scenarios and found that a 34 cm rise in", "output": {"entities": {"named_data": [{"text": "Global Vulnerability Analysis"}], "descriptive_data": [], "vague_data": []}}}
{"input": "through the project grievance redress mechanism that are resolved (Percentage). **Economic and Financial Analysis** 69. **Results of Economic Analysis without Greenhouse Gas (GHG) Accounting.** The results of the economic analysis indicate that DRDIP II is economically viable, as it is projected to yield a baseline Economic Internal Rate of Return (EIRR) of 22 percent, which is above the prevailing discount rate of 16.7 percent adopted for economic analysis. The Economic Net Present Value (NPV) is estimated at US$62.7 million, equivalent to UGX 231 billion. The benefit-cost ratio (BCR) is estimated at 1.12 percent. 70. **Results of Economic Analysis, with GHG Accounting.** The overall economic analysis has been rerun to assess the economic viability of the project taking into account benefits from reduction of carbon gas emissions. The GHG accounting analysis done using the Environmental Externalities Accounting Tool (EX-ACT) shows that over 20 years, the project will result in a carbon emission savings of 2,056,927 tCO2e (102,846 tCO2e per year). The savings in GHG emissions further enhance the viability of the project, as they contribute to overall net revenue and ultimately to the EIRR. After considering all project costs and benefits from reduction of carbon gas emissions, the overall EIRR is", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "financial statements which will be audited under terms of reference and by an external firm, both acceptable to the World Bank, will be produced for the project. Basic arrangements to ensure control, recording, and reporting are further described in Annex 1. 52. **Procurement** . Procurement for the Project will be carried out in accordance with the World Bank’s Procurement Regulations for IPF Borrowers for Goods, Works, Non-Consulting and Consulting Services, dated September 2023. The Project will also be subject to the World Bank’s Anticorruption Guidelines, dated October 15, 2006 (revised July 2016). The World Bank's Standard Procurement Documents will be used in World Bank-financed Open International Competitive Procurement. The World Bank completed a procurement capacity assessment of MEP in April 2024. The assessment reviewed the organizational structure for implementing the Project and assessed the experience of the existing staff. A Project Procurement Strategy for Development (PPSD) was prepared by the executing agency, which describes how procurement in this Project will support the PDOs and deliver value for money under a risk-based approach. The PPSD will provide adequate supporting market analysis for the selection methods detailed in the Procurement Plan. Mandatory 29 MEP implemented the Equity and Efficiency of Education Project", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "across competing priorities and are fully aligned with the Local Area Development plan for Meheba prepared by Kalumbila Town Council. The project’s three components will contribute to the building of a future policy framework and an operational model for use of WHR resources that could be extended to assist refugees and host communities in other parts of the country in potential future phases of the project. **Component 1. Strengthening the Enabling Environment (US$7 million)** 24. The objective of this component is two-fold. First, it is to build an enabling legal framework for refugees related to documentation, basic services, and livelihoods and self-reliance. Secondly, it aims to support the rollout of new national ID cards to refugees in all three of the refugee hosting district. _Subcomponent 1.1. Building an enabling legal framework (US$1 million)_ 25. In November 2023, the Cabinet approved Zambia’s new National Refugee Policy. The GRZ has set five key objectives for its revised Refugee Policy: (a) strengthened refugee protection, (b) improved access to basic services, (c) better livelihoods and self-reliance, (d) progress on long term solutions including local integration, and (e) enhanced government coordination of refugees and their inclusion in national development processes. Under this subcomponent, a national", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Single Account (TSA) to make payments. Subproject payments will be made to a community bank account in a commercial bank. The CFO of the local government will authorize the opening of community bank accounts in local governments and monitor payments made through the account to ensure they are used for project purposes. Each community will have a Community Project Management Committee, and the authorized signatories for their bank account will be the Chair, Secretary, and Treasurer. All payments by districts, cities, and urban centers will be accessible online in the IFMIS by MoFPED and OPM (that will have read on rights authorized by MoFPED) for monitoring, accountability, and audit purposes. **Figure 3: Funds flow overview** 63. **The report-based disbursement method will be used by OPM and IG to receive advances from the** **World Bank.** Advances to project’s Designated Accounts will be based on six-month cash flow forecasts supported by the Page 17", "output": {"entities": {"named_data": [{"text": "IFMIS"}], "descriptive_data": [], "vague_data": []}}}
{"input": "observed in PISA data. Looking at graduates of pre-university technical education (mainly technical stream secondary education) one finds an interesting pattern comparing three specializations (Figure 1b). Gender disparities are high in Electronics and Automation, less in Software Development and were recently eliminated in Network and Database Design. The final example of Network and Database Design in Figure 1b shows that gender disparity can be overcome in a short period of time. Two recent studies provide a detailed general analysis of policy options. [18] For STEAM courses, the causes relate to: (i) enjoyment of reading and preference for mathematics; (ii) self-efficacy or belief in own capabilities, often reinforced by teachers; (iii) parental support or lack thereof due to low socioeconomic status; (iv) teacher preparation to deal effectively with diversity. 16 Source: Government Budget for 2024 and MEP School Census data from 2023. 17 Program-Based budgeting at a government-wide level is being implemented under the Fiscal Management Improvement Project (P172352, Loan 9075-CR), known as _Hacienda Digital_ . Investing in readiness to implement program-based budgeting at MEP, the biggest Ministry (in terms of budget and staff) is a priority for the Government of Costa Rica. 18 [Desigualdades por género en Primaria y Secundaria,", "output": {"entities": {"named_data": [{"text": "PISA data"}, {"text": "MEP School Census data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "of different tenure in cases where the same crop was grown on owned and occupied ones, we drop parcels if, in the same household, there is another parcel of different tenure devoted to the same crop, either as a pure or mixed stand. This implies that, for the case of output, our sample contains owner-cum-occupants who cultivated different types of crops on at least one of their owned and their occupied parcels. [12] **3. Data and descriptive evidence** Descriptive evidence from a large and nationally representative household survey at household and parcel levels illustrates the large number of owner-cum-occupants who differ from pure owners and, to a lesser degree, occupants, in few of the variables of interest. At the same time, it points towards presence of systematic differences in investment between owned and occupied parcels which provide the motivation for more detailed econometric analysis. **3.1 Data sources and household characteristics** The data for our study come from the 2005/2006 Uganda National Household Survey (UNHS), fieldwork for which was conducted by the Uganda Bureau of Statistics from May 2005 to April 2006. The survey collected information at the community, household, and parcel level for about 7,500 households in 753 EAs including", "output": {"entities": {"named_data": [{"text": "2005/2006 Uganda National Household Survey"}], "descriptive_data": [{"text": "large and nationally representative household survey"}], "vague_data": [{"text": "household survey"}]}}}
{"input": "sub-component includes US$1.69 million in operational costs for BRD to manage component activities. 28. _Sub-component 2(b): Access to finance (US$5.7 million)._ This sub-component will provide finance to Rwandan and refugee entrepreneurs. The MG scheme will be retained, though with refinements based on lessons from Phase I, including: (a) detailed communication strategy will be prepared with districts, PFIs, UNHCR and refugee representatives and will be launched before funds are released to beneficiaries; (b) linkages will be made to TVET graduates (including from TVET centers financed by Jya Mbere) to help them access financial support for their business ideas post-training; (c) BRD will have more autonomy in Phase II, with separate funds flow and decisionmaking capacity, which is expected to improve efficiency; and (d) performance agreements for BRD project staff will include incentives to improve TAT. Page 9", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "of renewable energy and/or improved cooking systems for public institutions, which will be incorporated into Component 1. Component 2 will be organized around two sub-components, as described below. 33. _Sub-component 2.1: Restoration of Degraded Ecosystems (US$20 million)._ The DRDIP II Environmental and Social Assessment (ESA) carried out in 2024 identified various types of sensitive and degraded ecosystems within the project area, including riverbanks, wetlands, bare and steep sloping hillsides, forest reserves, gully erosion sites, and other sites at risk due to climate change. Such areas serve as water catchments, biodiversity hotspots, and sources of ecosystem services to the communities and will inform the selection of watersheds for restoration activities. Subproject selection within those watersheds will be guided by local needs and community priorities that will respond to climate change impacts. Measures to be supported will include: (a) construction of soil and water conservation structures, such as terraces, bunds, check dams and trenches to build community resilience to climate change-induced water scarcity; and (b) planting of ground cover and indigenous trees to reduce run-off, tackle erosion and landslides, enrich the ecosystem, re-stabilize the environment, and strengthen resilience to drought. These time-limited interventions are expected to directly respond to climate change impacts", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Israel would ―open the gates...wide to every Jew and confer upon the Jewish people the status of a fully privileged member of the comity of nations‖ (MFA 1948/2010). Established to express the right of the Jewish people to self-determination and grounded in the Zionist ideology, Israel‘s Jewish and democratic character is underlined by the 1950 Law of Return which constructs a distinctive migration regime. The law establishes the ―natural right‖ of every Jew to return to the homeland and become a citizen, based on ethno-religious ancestral ties which are represented in the modern nation, and in the ideological commitment to Jewish immigration (Sachar 2000; Shuval 1998). The law constructs a migration regime that defines the particularities of membership claims while excluding those who do not meet its demands, creating varying degrees of a much-debated structural discrimination against non-Jews, and in particular Palestinians (cf. Carmi 2003; Yiftachel 2006; Gavison 2010). The state actively seeks, via a range of institutions, to encourage Jewish ̳homecoming‘ and sustain a Jewish demographic majority. Israel‘s self-defined ―Jewish and democratic‖ character creates inherent tensions for non-Jewish migrants (amongst others) who are conceived by some as an existential threat (Kritzman-Amir 10", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "years old) on off-farm work and similar shifts, though no change in aggregate labor supply, by females. 14 With a mean cultivated area of 3.45 mu, the estimated benefit per mu in terms of consumption and income is 3,150*0.077/3.45 and 4,928*0.067/3.45, respectively. . 15 As we have information on time use at individual level, analyzing this aspect also allows us to obtain gender- and age-differentiated estimates of reform impacts, in line with evidence that such differences could be important (Wang 2014). 16 The age brackets of 16-60 years (or 55 for females) are in line with the age for participation in formal labor markets. 12", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "It should be noted that the choice of population density map is important for the purpose of this study. Smith et al. (2019) provide a sensitivity analysis for flood exposure assessments using different population density maps, including GHSL-POP 2015 (3-arc second, ~90 m resolution). They show that high-resolution population density maps perform best in capturing local exposure distribution, in particular the HighResolution Settlement Layer (HRSL) with 1 arc second, or ~30 m resolution, produced jointly by Facebook, Columbia University and the World Bank (2018). While HRSL is only available for a limited number of countries, GHSL-POP is shown to perform better than alternatives with global coverage, such as LandScan data (30-arc second, ~900 m resolution; Bright et al. 2016). **3.3.** **Administrative boundaries** The definition of national administrative boundaries follows the standard World Bank global administrative map. However, national boundaries are further disaggregated into subnational units for all countries where World Bank household surveys are available with subnational representativeness. These subnational units are typically provinces or states (i.e. admin1) but can also include custom groupings of subnational regions determined by the sampling strategy of household surveys. Overall, this study covers 189 countries, which are disaggregated into 2,260 subnational units. **3.4.** **Poverty", "output": {"entities": {"named_data": [{"text": "GHSL-POP 2015"}, {"text": "HighResolution Settlement Layer (HRSL)"}, {"text": "LandScan data"}], "descriptive_data": [{"text": "household surveys"}, {"text": "World Bank household surveys"}], "vague_data": []}}}
{"input": "**The World Bank** Uganda Development Response to Displacement Impacts Project Phase II (P510476) PROJECT APPRAISAL DOCUMENT World Bank GEMS system. Project results will be captured through baseline, annual, and endline surveys. Regular phone surveys will also be conducted for beneficiaries under the economic opportunity component to gather data on business sustainability and profitability to allow for real-time learning and course correction as necessary. Where appropriate, results indicators will be disaggregated by gender and by refugee/host community status. **C. Disbursement Arrangements** 62. **The project will receive disbursements from the World Bank in a holding account under the consolidated fund** **in United States Dollars (US$) in the Bank of Uganda (BoU) managed by the Office of the Accountant General under** **MoFPED.** Funds from the holding account will be transferred to two accounts for OPM and IG in US$ held at BoU. To implement the project, funds will be transferred from the US$ accounts for OPM and IG into the OPM operations and implementation account and IG’s operations account, both denominated in Uganda Shillings (UGX). Payments for eligible expenditure by OPM and IG can be made from either their US$ or UGX accounts. Transfers by OPM to districts, cities, and urban centers will", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "refugees have obtained residence permits enabling them to live in and around Lusaka, Ndola, and other urban centers. [11] **(** Figure 1). **Figure 1. Location of Refugees in Zambia** _Source:_ June 2024, Ministry of Home Affairs and Internal Security (MoHAIS). 10. **Socioeconomic conditions for refugees in the designated settlements are challenging.** Notwithstanding, the Government’s long-standing efforts to support the three main refugee settlements and adjacent areas, achieving selfreliance for refugees in these settlements has proven elusive. Refugees face restrictions on freedom of movement and, while by law they have the right to employment and education, the cost of residence and work and study permits places severe restrictions on their ability to attain self-reliance. While many refugees are in practice living outside the settlements, they are prone to arrest and extortion in the absence of legal identity and full mobility rights. Female refugees experience additional vulnerabilities to gender-based violence (GBV) and sexual exploitation both within and outside the settlements. The situation is compounded by the remote rural locations of settlements, underdeveloped local infrastructure and services, and limited opportunities to develop sustainable livelihoods. [12] Changing weather patterns are having a disproportionate impact on refugees and host communities as they struggle to adapt", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the following year), the balanced sample (where insurance was offered all years), and the balanced marketing sample (where insurance was purchased in all years). One may be concerned that the linear probability model may give biased estimates, especially since such a small percentage of the sample were repeat buyers. Therefore, the results from a probit model are also presented in the supplemental appendix and give similar results to OLS. As mentioned earlier, the dependent variable in this regression was generated by manually matching customers from one year to another, and therefore it is likely measured with some error. Although there is no reason to believe that this measurement error is correlated with any independent variables in the regression, since the dependent variable in the regression is a dummy variable, this can lead to downward bias on the estimated coefficients. In order to get a feel for the potential magnitude of this error, I run simulations where I assume that the BASIX data has been matched completely correctly and then induce “measurement error” by randomly changing the dependent variable of whether people purchased the following year or not. With the introduction of 10 percent matching errors (with an equal probability of", "output": {"entities": {"named_data": [{"text": "BASIX data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "represent riverine and coastal flood hazard for Vietnam considering climate change. Second, we examine how exposure to floods differs based on socioeconomic characteristics, with an explicit focus on poverty. Our results indicate that climate change is likely to increase the number of people exposed to floods, especially in the Mekong and Red River Deltas. For the same return period flood under current socioeconomic conditions, climate change may increase the number exposed to 38 to 46% of the population (an increase of 13–27% above current exposure), depending on the severity of sea level rise. Regarding poverty and exposure, while we do not find evidence of a differential exposure at the national level, we find at the city level that poor people are relatively more exposed to floods. Within HCMC, potential slum areas are 10–20% more exposed to floods compared to the rest of the city, with the exposure differential increasing with climate change. Nevertheless, the findings presented in this paper should be interpreted considering a number of caveats. While we use current and future flood data, we only use current population and poverty data, as reliably projecting these socioeconomic trends spatially into the future is almost impossible. Changes in these trends", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "current population and poverty data"}], "vague_data": [{"text": "current and future flood data"}]}}}
{"input": "**The World Bank** Zambia Refugee and Host Communities Project (P503941) **ANNEX 1: Implementation Arrangements and Support Plan** 1. **Overall project implementation will be managed by the MoHAIS.** As the lead implementing agency, the MoHAIS has both an important implementation role—specifically on Component 1—and a coordination role which includes mobilization of the PSC and PSG and monitoring the implementation performance of the devolved responsibility to the SPMU in Kalumbila District. MoHAIS will help resolve any technical or political bottlenecks which may arise across the project. The MoHAIS has already assumed an important leadership role in the development of the GRZ’s Refugee Policy and the MORHCSA. The implementation arrangement is presented below. **Figure 1.1. Project Implementation Arrangements** 2. **Project activities under Components 2 and 3 will require specialist technical service providers.** The SPMU will be responsible for contracting appropriate providers and overseeing implementation progress of selected providers. - **Component 2: Climate Resilient Community Infrastructure.** All designs and supervision activities will be undertaken by respective implementing government ministries, except for the road improvement activities which will be designed and supervised by a firm selected from the market. Construction activities will also be by private sector firms to ensure higher build and climate-resilient standards.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**are people with disabilities** and **17% are older people** . Among older people around 50% are persons with disabilities which exacerbate the risks that this category of refugees faces. This briefing note aims to provide an overview of the situation of older refugees in Moldova and the gaps and needs they face, as well as the current efforts being made by humanitarian stakeholders to address these challenges. From the **Socio-Economic Insights Survey** (SEIS) conducted by the IMPACT Initiative in1 August 2024, the following **four main areas** were identified as significantly impacting **older refugees** compared to other groups: **Access to Information:** Older refugees face significant challenges in accessing information compared to other refugee groups. Many lack the necessary devices to connect online, and the available information is often not presented in formats that accommodate their needs. **Healthcare Access:** Access to healthcare and to medicines emerged as urgent priorities for older refugees, with a significantly higher proportion identifying these needs as compared to younger refugee groups. **Support Channels:** Refugees aged 75 and above are less likely to have access to secure and private channels for seeking support, or reporting concerns, including sensitive community issues (only 75% reported access compared to an average", "output": {"entities": {"named_data": [{"text": "Socio-Economic Insights Survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "to control for time effects. Also, I only include purchasers who have weather insurance contracts available in their area in the following year. [9] These results are presented in table 3, and column 1 reports the baseline OLS results. It shows that receiving a payout is associated with a 9 percent increased chance of repurchasing insurance the following year, which means that those who receive an insurance payout are more than twice as likely to purchase insurance the following year than those who did not receive a payout. [10] However, this coefficient is not statistically significant at standard levels ( _p_ = .18). The effect on repurchasing may depend on the size of the payout as well. In column 2 I add two new continuous variables to the regression: the ratio of the payout received to the premium paid (which I will call the “payout ratio”) and the payout ratio squared. In this specification, the dummy on receiving 5 [APHRODITE’s water resources project; http://www.chikyu.ac.jp/precip.](http://www.chikyu.ac.jp/precip) 6 25° latitude equals about 27.5 kilometers. .25° longitude varies by latitude; over the range of latitudes in this survey it equals roughly 26 kilometers. 7 It is not clear if ICICI-LOMBARD used APHRODITE or another", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Note:_ Panel A shows the location of the gold mines that were active during the study period. Around each circle, a 20-km radius is marked. These 40-km-wide areas are the baseline treatment areas in the analysis. Panel B shows the 100-km treatment areas and the distribution of the DHS clusters. Road data is an alternative way of defining distance from mines, but time series data on roads is not available. **3.2 Household data** We use microdata from the DHS, obtained from standardized surveys across years and countries. We combine the respondents from all four DHS standard surveys in Ghana for which there are geographic identifiers. The total data set includes 19,705 women (of which 12,392 live within 100 km of a mine) aged 15–49 from 137 districts. They were surveyed in 1993, 1998, 2003, and 2008, [6] and live in 1,623 survey clusters. Since the DHS surveys focus on women, the surveys of women will be the main source of data. However, we also use the surveys of men, which give us data from the same four survey years, but with a total number of 12,294 individuals, of which 7,491 men live within 100 km of a mine. In addition,", "output": {"entities": {"named_data": [{"text": "DHS standard surveys"}, {"text": "microdata from the DHS"}], "descriptive_data": [{"text": "surveys of men"}, {"text": "surveys of women"}, {"text": "microdata from the DHS"}], "vague_data": [{"text": "surveys of men"}]}}}
{"input": "estimated at US$57,000 at a 12 percent discount rate, with an ERR of 12 percent. **Gender** 67. **Building on the gender assessment conducted during the Phase I MTR, Phase II will address the gender** **gaps outlined in Table 10 below.** The project results framework will also track gender data. The key gaps identified in the MTR assessment are: (a) fewer women access loans from financial institutions to start their own businesses; (b) fewer women are starting businesses due to time poverty and capacity gaps; and (c) fewer women are in employment than men. Social gender norms and household dynamics play a critical role in causing these gaps. According to a 2022 study by Access to Finance Rwanda, deeply ingrained societal expectations shape how women participate in economic life and influence their capacity to leverage assets—particularly land and property—as collateral. _[34]_ One pervasive norm is that women should prioritize family and caregiving responsibilities over business activities. This norm restricts their time and engagement in income-generating pursuits and weakens their perceived legitimacy as entrepreneurs, reducing their chances of qualifying for credit. Additionally, women are often expected to rely on family support, especially from spouses, instead of seeking independent financial solutions, distancing them", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "gender data"}]}}}
{"input": "System support, administration, and M&E (US$12 million)_ . This sub-component will support the operational costs of the PIST at the national, regional, district, and sub-county levels. These project structures will work in collaboration with the existing OPM structures at the various levels. The sub-component will also fund a robust M&E system that will include regular monitoring from the field using the World Bank GEMS system, as well as baseline, midline, and endline assessments. Beneficiary phone surveys will be conducted regularly to gather information from the field. The sub-component will support capacity building for the project IAs on issues such as financial management, procurement, project management, M&E, and environmental and social risk management. 48. _Sub-component 4.2: Strengthening Transparency, Accountability, and Anti-corruption (STAAC) (US$2.5 million)_ . Led by the IG, the GoU’s peak anti-corruption body, the sub-component will establish and build the capacity of Community Monitoring Groups in all DRDIP II locations to operate as frontline agents for corruption prevention, corruption risk monitoring, awareness raising and to receive corruption complaints. Project financing will also support the IG to respond to allegations of corruption made against the project. Page 13", "output": {"entities": {"named_data": [{"text": "World Bank GEMS system"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Bank. [43] Multifaceted challenges such as refugee impacts on host communities and assisting of refugees to achieve self-reliance require a combination of policy and investment. The approach is aligned with lessons from the 2023 World Development Report which highlighted that “policies should be geared toward financial and social sustainability by means of internal mobility, self-reliance, and inclusion in national services.” [44] Durable solutions require a combination of both legal and development perspectives, which is precisely what this project does. Such an approach needs to be coupled with a long-term development horizon as the typical World Bank project life cycle is not well suited to addressing such massive development deficits over typically short project cycles. 47. **The viability of agribusiness is crucial for project sustainability beyond World Bank assistance.** The TA and financial support provided under the project will build on the successful World Bank financed Zambia Agribusiness and Trade Project (P156492) model. The aim will be to provide cooperatives and farmers sufficient TA and grant financing to 43 World Bank. 2022. _Social Cohesion and Forced Displacement: A Synthesis of New Research_ . 44 World Development Report 2023. Page 22", "output": {"entities": {"named_data": [{"text": "Zambia Agribusiness and Trade Project"}], "descriptive_data": [], "vague_data": []}}}
{"input": "adolescent clubs, community community-based child protection structures volunteers, sports and the establishment of child (Children Clubs and Child Welfare Committees) friendly spaces, and life-skills education groups. through WhatsApp and other online platforms to Operations and partners map the community disseminate referral pathways updates and key actors to further facilitate and enhance their roles protection messages. vis-a-vis the aforementioned mechanisms to protect children and their communities. In Ukraine, UNHCR shared important information on its online refugee youth platform, including In Mexico, UNHCR, in collaboration with IOM and useful links for free online courses that was used UNICEF, developed child-friendly information for social interactions and peer-to-peer support. materials on COVID-19 and supported UNHCR / July 2020 2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Uganda Development Response to Displacement Impacts Project Phase II (P510476) PROJECT APPRAISAL DOCUMENT 7. **Degradation of the natural environment is placing refugees and host communities at higher risk from climate** **change effects.** Uganda’s economy is highly dependent on ‘climate-sensitive’ sectors such as agriculture, fisheries, tourism, and forestry. Ranked 163 [rd] out of 187 on the Notre Dame Global Adaptation Initiative index, urgent action is required to address climate vulnerability in Uganda. Key trends over the last 60 years include temperature rises (1.3degree Celsius average temperature increase, expected to reach 1.8 degrees by 2050) and a statistically significant reduction in rainfall. Droughts have become more frequent and longer-lasting, especially in the western, northern, and north-eastern regions, which cover most of the DRDIP II target areas. [10] This is causing more frequent crop failure, threatening livelihoods, increasing food insecurity, and aggravating water scarcity. In the future, rainfall is expected to decrease further in the north and north-eastern regions and increase in the west. As the climate crisis intensifies, the country faces rising incidents of extreme weather, leading to disasters such as floods, droughts, and landslides. [11] Between 2018 and 2023, over 455,000 people were displaced due to weather-related disasters,", "output": {"entities": {"named_data": [{"text": "Notre Dame Global Adaptation Initiative index"}], "descriptive_data": [], "vague_data": []}}}
{"input": "the Women, Business, and the Law Index (World Bank 2022a). 4. **Djibouti’s vulnerability to climate-related disasters exacerbates these economic and social challenges.** The country frequently experiences heatwaves, droughts and floods, which take a heavy toll on the population by reducing productivity and disrupting economic activity. Between 1980 and 2019, Djibouti recorded ten major droughts, with the 2008-2011 drought alone shrinking GDP by four percent and affecting over 100,000 people, leading to the loss of half of Djibouti’s livestock. More recent flooding events between 2018 and 2020 caused substantial damage, impacting 250,000 people and requiring an estimated US$25 million for recovery and reconstruction. The increasing frequency and intensity of these extreme weather events place additional pressure on rural communities, which are already struggling with poverty, underdeveloped infrastructure, and limited access to essential services. In 2021, 89 percent of Djibouti’s population was exposed to climate hazards, with extreme heat affecting more people (82.8 percent) than any other 1 In Djibouti less than 1,000 square kilometers of land is arable and annual rainfall is extremely low (130 mm). Page 1", "output": {"entities": {"named_data": [{"text": "Women, Business, and the Law Index"}], "descriptive_data": [], "vague_data": []}}}
{"input": "a broader range of interventions including the financial services and SBCCs. **C. Disbursement Arrangements** 65. **Given the high-risk environment, the report-based disbursement will not be applicable.** Therefore, upon project effectiveness, transaction-based disbursements will be used. An initial advance up to the ceiling of the Designated Account (DA) will be made into the DA and subsequent disbursements will be made monthly against submission of Statements of Expenditures or records as specified in the DFILs. The other methods of disbursing the funds (reimbursement, direct payment, and special commitment) will also be available to the project. The minimum value of applications for these methods is USD100,000 equivalent. The project will have the option to sign and submit withdrawal applications electronically using the eSignatures module accessible from the World Bank’s Client Connection website. The flow of funds arrangement chart is shown in Figure 1.1 here under. **Figure 1.1. Flow of Funds and Disbursement Arrangements** Page 18", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Table 1: Sample of farms** **No. of** **Irrigated** **Dryland** **Country** **plots** **plots** **plots** Burkina Faso 1141 59 1082 Cameroon 1013 145 868 Egypt 1030 1030 0 Ethiopia 932 67 865 Ghana 1210 49 1161 Kenya 862 95 767 Niger 1133 52 1081 Senegal 1362 34 1328 South Africa 283 83 200 Zambia 1009 13 996 Zimbabwe 958 123 835 **Total** **10933** **1750** **9183** 14", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) 35. **Component 4: Project Management and Operational Analytical Support (US$10 million).** Component 4 will finance project management costs and technical assistance. A PIU will be financed by the World Bank with adequate fiduciary procedures in place to ensure the efficient and transparent use of loan proceeds. Staff and activities financed under this Project will be clearly delineated in the Project Operations Manual. 36. _Subcomponent 4.1. Project Management_ (US$5 million). This subcomponent will support project management, through: (i) operating a PIU in MEP; (ii) strengthening MEP’s supervision, monitoring, and evaluation capacity for specific Project activities; (iii) carrying out technical and Project audits; and (iv) environmental and social management activities. The subcomponent will finance project operating costs and acquisition of goods and services related to overall project activities, such as impact evaluation studies and communication activities. 37. _Subcomponent 4.2. Operational Analytical Support_ (US$5 million). This subcomponent will finance just-in-time analytical work, as needed, in relation to the Project’s areas of activity. These include the preparation of analytical policy work and related policy and operational support activities regarding the following topics, _inter alia_ : (i) International Baccalaureate program; (ii) Non-University Colleges ( _Educación", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Integrated Community Resilience Project (P506969) PROJECT APPRAISAL DOCUMENT 24. **The proposed PDO-level indicators are:** - Direct project beneficiaries, of which female, refugees, host community residents, and vulnerable to climate change (number); - Beneficiaries of cash for nutrition transfers under the project, of which female, refugees, host community residents (number); - People provided with improved access to basic infrastructure and services, of which female, refugees, host community residents (number); - People supported to enhance their livelihoods and income generation, of which female, refugees, host community residents (number **).** **C. Project Beneficiaries** 25. **The project will have a holistic approach that will benefit underserved communities in Dikhil region, two** **refugee-hosting regions of Obock** **and Ali Sabieh (including Ali Addeh and Holl Holl refugee villages), and expand across** **the country including Djibouti-Ville for the social safety nets.** The project is expected to reach 74,800 direct beneficiaries, including 12,860 refugees (39.4 percent of the total refugee population) and 35,900 host community residents (4.5 percent of the total host population). Beneficiary targets have been set in consideration of the size of the refugees and host community populations. 26. **Intervention areas.** Under component 1, safety net support will be provided across all regions", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "2019, nine safety net programs covered different groups), inadequacy, and unpredictability. Djibouti’s social protection system is currently inadequate to shield poor and vulnerable people from adverse lifecycle impacts or encourage desirable investment in human capital and provides limited coverage. In 2012, social safety net coverage was 9.5 percent, well below regional averages, with government social safety net spending 0.18 percent of GDP, compared with the Middle Eastern and North African average of one percent and the world average of more than 1.5 percent. Social safety net systems are critical in protecting and building the human capital of children threatened by adverse impacts on livelihoods such as environmental shocks. This support is particularly important for the 21 percent of Djiboutians who are extremely poor and have no capacity to smooth consumption and protect their human capital. 9. **Development indicators in Djibouti highlight significant service delivery challenges and multidimensional** **poverty, particularly in rural areas** . Maternal mortality remains high (234 deaths for 100,000 births) with rural areas driving the trend [4] . According to the **Human Capital Review for Djibouti (World Bank, 2024)**, access to basic services such as targeted social safety nets, education and healthcare remains limited, with rural areas experiencing", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "a setting that is more likely to mirror commercial-level insurance operations; therefore, it provides a higher level of external validity. The paper will proceed as follows: Section I explains the insurance policies and data that will be studied in the empirical section. Section II provides the main empirical evidence, and shows that recipients of insurance payouts are more likely to purchase insurance the following year. Section III searches for evidence of a number of mechanisms by which this could take place. Section IV discusses a number of behavioral explanations for the results. Section V concludes and offers policy recommendations. **I.** **Index Insurance and Customer Data** In this analysis I study monsoon rainfall index insurance policies underwritten by the insurance company ICICI-LOMBARD and sold by BASIX, a microfinance institution based in Hyderabad. The policies insure against excess or deficit rainfall; they are calculated based on rainfall measured at a stated weather station. By basing payoffs on just rainfall, the policies have low monitoring and verification costs and also should be free of adverse selection and moral hazard (Collier, Skees, and Barnett 2009). These attributes make policies inexpensive to create and administer, which allows them to be sold in small quantities and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "invest in economic opportunity and access to services in the hosting districts; and (b) at the same time, facilitate refugee mobility out of the camps and rural areas into urban centers, where more opportunities are available and self-reliance is more achievable. 8. **Building on the ongoing Phase I of Jya Mbere, Phase II aims to assist refugees and host communities to** **achieve self-reliance.** Compared to when Phase I commenced, there is now greater understanding conceptually and in practical terms of what it takes to achieve self-reliance. The Rwanda RSRI has seven domains: education, health, labor, income, food security, ID/social capital, and housing, with the first four to be supported by Phase II (plus environmental management). Complementing the RSRI, the 2022 _National Graduation Strategy_ provides guidance on the characteristics of those who have “graduated” out of long-term poverty into self-reliance, including livelihood diversification, savings, and access to markets and services, all of which will be supported by Jya Mbere II. 9. **Climate change poses risks to Rwanda’s positive economic outlook and refugees are particularly vulnerable** **to climate shocks** . Ranked 112 out of 185 countries in the 2021 Notre Dame-Global Adaptation Index (ND-GAIN), Rwanda is vulnerable to flooding, heat, drought, and", "output": {"entities": {"named_data": [{"text": "2021 Notre Dame-Global Adaptation Index"}], "descriptive_data": [], "vague_data": []}}}
{"input": "the basis for improved skills in a transition towards lower-carbon economies. On mitigation, the activities supported by the Project are expected to generate negligible Greenhouse Gas (GHG) emissions, and as such, do not pose material risks of having a negative impact on the country’s low emission targets. **II.** **PROJECT DESCRIPTION** **A. Project Development Objective** **PDO Statement** 19. The Project Development Objective is to enhance MEP efficiency and improve foundational learning, digital competencies, and employability skills of students in MEP administered schools. **PDO Level Indicators** i. **PDO 1: Enhancing MEP Efficiency:** Indicator 1: Reduction in processing times for selected administrative and management processes within MEP. ii. **PDO 2: Improving foundational learning, digital competencies and employability skills** : Indicator 2: Percentage of Grade 3 students who surpass Basic level in National Assessments for Reading and Mathematics; Indicator 3: Percentage of students who have met the Intermediate achievement level of digital instruction corresponding to their Grade; Indicator 4: Percentage of technical stream secondary education students with micro-credentials registering English proficiency (all these indicators will be disaggregated by gender and by indigenous and refugee/migrant status). [23] 23 The Project will support block-chain backed micro-credentials (these are authenticated digital certificates, with the block-chain ensuring the", "output": {"entities": {"named_data": [{"text": "National Assessments for Reading and Mathematics"}], "descriptive_data": [], "vague_data": []}}}
{"input": "registration plan that includes vulnerable people within the refugee and host population, for example, single women and people with disabilities. Specific activities to be supported include the following: (a) Procurement of approximately 150,000 paper-based cards or polycarbonate cards (out of the 20 million that the Government will buy for citizens) (b) Transfer of the UNHCR ProGres [22] database to the MoHAIS (separate servers and peripheral equipment) (c) IT upgrading at MoHAIS offices in the three refugee settlements to enable all future documentation requests to be done locally and digitally, eliminating the need for travel to Lusaka (d) Community-level customized campaigns for refugees in three districts, including mobile registration camps targeting women and girls (e) Biometric registration kits. 30. The project will uphold approved operating procedures applied by the Department of National Registration within the MoHAIS in safeguarding personal data, aligned with the GRZ’s Data Protection Act of 2021. MoHAIS officials will benefit 20 Refers to refugees, asylum-seekers, refugee returnees, stateless people, and the internally displaced. 21 Statelessness and Climate Change Factsheet, UNHCR, 2021. 22 UNCHR’s registration and case management system Page 15", "output": {"entities": {"named_data": [{"text": "UNHCR ProGres"}], "descriptive_data": [], "vague_data": []}}}
{"input": "physical assaults, kidnappings, murders, sexual violence but also incidents related to explosive devices (ED). The security situation and military operations in neighboring countries (Mali, Burkina Faso, Nigeria), the continuation of NSAG incursions into Niger, the intensification of operations by the Defense and Security Forces (DFS) are all factors that predict the persistence of ED threats in Niger. Indeed, since 2022, the threat of ED has continued to rage in the regions of Tillabery and Diffa. The Protection Cluster recorded approximately 55 ED-related incidents in 2022 (a 34% increase compared to 2021). From January to June 2023, 32 ED incidents were reported, representing more than half of the total number of incidents reported in 2022. It is also worth highlighting the problem of food insecurity which affects several departments, including those affected by ED threats. In fact, faced with the effects of food insecurity, communities could resort to negative coping strategies, in particular that of venturing into areas affected by ED in search of means of subsistence or even collecting scrap metal found on explosive remnants of war for resale. In the face of a growing threat from ED, mine action capacities remain limited in Niger. Considerable challenges exist both in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "at the country level. Our overall environmental indicator is the mean of the five thematic indicators. [9] We use log values for the analysis because the size distributions of country indicators and resource allocations are extremely 8 For biodiversity, our data include only Bank lending. Grants by the Global Environment Facility (GEF) for biodiversity conservation are not included in this analysis, but the GEF is currently conducting a parallel analysis of its own resource allocation. 9 All indicators are normalized to the range [0-100], so they have equal weight in determining the mean indicator. 11", "output": {"entities": {"named_data": [{"text": "Bank lending"}], "descriptive_data": [], "vague_data": []}}}
{"input": "in 2020 (only 49 percent of needs) to US$37 million in 2023 (41 percent of needs), despite almost no change in refugee numbers. 6. **Progress towards achieving refugee self-reliance is hampered by a lack of employment and income-** **generating opportunities.** A tailored Refugee Self-Reliance Index (RSRI) prepared by the GoR, the World Bank and UNHCR measures refugee self-reliance in Rwanda. As noted above, the 2022 census and the first round of RSRI data showed that most refugees have good access to basic services, but fare poorly with respect to employment and income. The employment to population ratio for refugees is 15 percent as against 46 percent for the total population. According to the RSRI survey, just 24 percent of refugees reported doing paid work in the previous seven days (though this increases to 45 percent for refugees living in Kigali) and only eight percent run a business or are engaged in farming. Low income is reflected in poor food security, with almost 60 percent of refugee households reporting that they typically eat only one meal per day. The main reasons provided for the low employment levels were lack of skills (44 percent) and lack of information about the local labor", "output": {"entities": {"named_data": [{"text": "tailored Refugee Self-Reliance Index"}, {"text": "2022 census"}, {"text": "RSRI survey"}], "descriptive_data": [], "vague_data": [{"text": "first round of RSRI data"}]}}}
{"input": "The choice of district – rather than cluster – fixed effect is informed by the understanding that meaningful time-invariant factors - such as mining laws, level of development, local political institutions, norms regarding environment, women’s participation in the labor market, etc. - that influence exploitation of the mine happens at the district level. Including district fixed effects, we control for various institutional and cultural factors at the district level that are stable over time. Including district fixed effects also ensures that we are not only capturing effects from transfers or the fiscal system as we compare individuals within the same districts. With this method we capture the geographic spillover effects in the vicinity of the mine. Moreover, cluster fixed effects are not possible because of clusters are not repeatedly sampled over time. However, since the estimation is at individual level, all standard errors are clustered at the DHS cluster level. The sample is restricted to individuals living within 100 km of a deposit location ( _mine_ ), so many parts of Northern Ghana where there are few gold mines are not included in the analysis. The sample restriction is created by using the time-stable continuous distance measure that we calculate", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "this error, I run simulations where I assume that the BASIX data has been matched completely correctly and then induce “measurement error” by randomly changing the dependent variable of whether people purchased the following year or not. With the introduction of 10 percent matching errors (with an equal probability of a mismatch for buyer or nonbuyers), the coefficient on receiving a payout in the full sample (column 1) falls from .090 to an average of .072 over 1,000 simulations. For the marketing restricted sample in column 2, it drops from .222 to .178. In other words, if one assumes 10 percent matching errors, then the estimated coefficients are likely to be underestimated by around 20 percent. It also may be possible that most of the error came from being unable to identify positive matches, possibly due to different members of a household signing the insurance contract from year to year. Repeating the above simulation but assuming that only people who were found not to have bought the next year could have been errors, the coefficients become underestimated by around 10 percent. Although the exact form and structure of the matching errors cannot be known, it is possible that the reported", "output": {"entities": {"named_data": [{"text": "the BASIX data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "prioritize on-farm value chains such as cassava, maize, soybeans, sunflowers, groundnuts, sorghum, sesame, as well as aquaculture. Off-farm livestock activities could consider trading, baked goods, agro-technology (milling), apiary, piggery, and cattle-rearing for milk and beef value chains. In refugee settings, where land access is relatively limited, non-farm enterprises and small livestock (e.g., poultry) will be encouraged. Utilizing existing diagnostics, a list of high potential value chain options by order of priority for the targeted regions has been developed. Each district will target two-three of these key value chains to ensure scale, impact, and synergy with ongoing investments. Priority value chains will inform group-based investments through the CDD model, where a positive list will be presented to beneficiaries for informed choice. 38. **For selected value chains, the sub-component will strengthen coordination efforts at the national and district** **levels to avoid duplication.** The project will support the development of a District Economic Opportunities Plan (DEOP) that will outline existing efforts in the chosen value chains, identify private sector players and off-takers, and compile a catalogue of assets and infrastructure requiring construction or maintenance. The DEOP will serve as a framework for DRDIP II investments to collaborate effectively with activities under the Uganda", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "with World Bank-funded projects applying the ESF; (b) multiplicity of stakeholders with a fragmented coordination mechanism, coupled with weak institutional capacity; (c) potential risk of exclusion, which could exacerbate existing tensions of inequality among refugees and host communities; (d) disproportionate impacts of planned activities on vulnerable groups, (e) risk of labor influx leading to increased incidences of GBV, sexual exploitation and abuse (SEA), and sexual harassment (SH) based on the contextual environment; (f) lack of privacy in the use of personal data; and (g) potential physical and economic impacts. 71. To mitigate identified environment and social risks, an Environmental and Social Management Framework (ESMF) has been prepared, with guidelines for site-specific Environmental and Social Impact Assessments (ESIAs), corresponding Environmental and Social Management Plans (ESMPs), and other relevant instruments when applicable. A SEP has been prepared, which outlines the process of consultations to be conducted throughout the project cycle with identified stakeholders (particularly women, youths, persons with disability, and the elderly), using culturally appropriate methods for provision of accurate project information. The SEP also describes the grievance process which is responsive to GBV/SEA/SH. Agreed actions for monitoring project risks are specified in the Environmental and Social Commitment Plan (ESCP). The ESCP,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "in active mining communities are marginally older, more likely to never have moved, and more likely to be or have been in a cohabiting relationship or married. Given the women’s slightly higher age, it is not surprising to find that they have higher fertility and lower schooling (assuming that schooling has increased over time in Ghana). All these estimates are, however, insignificant. **Table 3 Observable characteristics in the DHS individual data** non- ever currently ever total any schooling 16", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Policy Research Working Paper 9447 ###### **Abstract** Flooding is among the most prevalent natural hazards affecting people around the world. This study provides a global estimate of the number of people who face the risk of intense fluvial, pluvial, or coastal flooding. The findings suggest that 1.47 billion people, or 19 percent of the world population, are directly exposed to substantial risks during 1-in-100 year flood events. The majority of flood exposed people, about 1.36 billion, are located in South and East Asia; China (329 million) and India (225 million) account for over a third of global exposure. Of the 1.47 billion people who are exposed to flood risk, 89 percent live in low- and middle-income countries. Of the 132 million people who are estimated to live in both extreme poverty (under $1.9 per day) and in high flood risk areas, 55 per cent are in Sub-Saharan Africa. About 587 million people face high flood risk, while living on less than $5.5 per day. These findings are based on high-resolution flood hazard and population maps that enable global coverage, as well as poverty estimates from the World Bank’s Global Monitoring Database of harmonized household surveys. This paper is a product", "output": {"entities": {"named_data": [{"text": "Global Monitoring Database of harmonized household surveys"}], "descriptive_data": [{"text": "high-resolution flood hazard and population maps"}], "vague_data": []}}}
{"input": "9.745 6.292 9.759 8.111 ... disputes could not be resolved by village 1.248 0.074 0.724 0.894 0.042 1.690 0.933 leaders **Results** Contract now longer than 30 years 0.987 0.993 0.980 0.977 1.000 0.983 0.993 Contract now permanent 0.717 0.792 0.497 0.481 0.848 0.861 0.860 _Source:_ Own computation from 2014 Chengdu village survey for three counties inside Chengdu based on 153 villages. . 18", "output": {"entities": {"named_data": [{"text": "2014 Chengdu village survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Local 27 UNDP. 2022. _Needs Assessment Report for the Promoting Human Security through Sustainable Resettlement_ _Programme._ 28 UNHCR. 2023. _Socioeconomic Survey Report: Zambia_ . 29 UNHCR. 2022. _Working towards One Meheba - GAP Analysis_ . 30 The low population density, lack of any obvious farming activity, and absence of markets to the south of the Mwafwe River mean that upgrading the second portion of the road past the Mwafwe bridge is deemed not economically viable at this time and not a priority for the project. 31 The REA project involves electricity supply to Maheba C Primary School, Maheba D Primary School, Maheba D RHC, Maheba Markets 1 and 2, Maheba E Community School, Maheba F Primary school, Maheba F RHC, Maheba G Primary School, Brave Heart RHC, Kamiba Primary School, Kamiba RHC, and surrounding areas. The work involves construction a total of 36.471 km 33 kV of overhead lines (OHL) from an existing 33 kV OHL at Maheba B and 23.315 km of 400 V OHL. 32 There are a total of 15 schools in the settlement—2 secondary schools, 8 primary schools, and 5 providing early childhood education (ECE). 33 Ministry of General Education, Zambia, 2020. Page 17", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "are at approximately 90m spatial resolution, the global wetlands data are compiled from a range of sources resulting in generalized areas. Also, the correspondence 20 Tol 2007 drew on the Global Vulnerability Analysis and other country studies for quantification of wetland loss from 1 m SLR for a global analysis including small island nations. 13", "output": {"entities": {"named_data": [{"text": "Global Vulnerability Analysis"}], "descriptive_data": [], "vague_data": [{"text": "the global wetlands data"}, {"text": "global wetlands data"}]}}}
{"input": "for CBI TWG meetings and participate in CBI TWG meetings on a regular basis. They are responsible for sharing programmatic information and updates, technical inputs, lessons-learnt, and actively participating in setting the strategic direction of the CBI TWG. **Secretariat:** UNHCR acts as secretariat and is responsible for information and knowledge management which includes gathering of information from partners, and publishing on the dedicated page of the interagency data portal managed by UNHCR for CBI TWG. **Information Management Officer (IMO):** This role is held by UNHCR, and it carries responsibility of managing and facilitating efficient data-related processes including overseeing the collection and analysis of data in the CBI Mapping process, as well as the production and dissemination of CBI TWG dashboards and relevant analyses to platform partners. The IMO is tasked with identifying the information needs of the platform and its partners, encouraging a culture of structured and secure information sharing among all stakeholders through well-defined sectoral mechanisms. Additionally, the IMO supports partners in continuously updating their CBIs on the Services Advisor. A key aspect of this role involves the development, collection, processing, analysis, storage, and sharing of data within the CBI TWG. **Technical Advisory Group:** Comprising a group of CVA", "output": {"entities": {"named_data": [{"text": "interagency data portal"}], "descriptive_data": [], "vague_data": []}}}
{"input": "presents the effects of mining on asset wealth and on asset wealth inequality. Wealth data are available in the form of a wealth index, but only for the two last DHS surveys. Following Fenske (2015) and Flatø and Kotsadam (2014), we calculate inequality by means of a Gini coefficient (recoding the wealth variable to be positive only, and using the command 13 It is also possible that mining companies compete with households for electricity if supply cannot be increased in the short run. 14 In panels Ba, Bb, and Bc of Appendix figure A1, we analyze access to radio. We learn that access to radio is higher close to active mines, and that this seems true according to both the first method (Ba), according to the spatial lag model (Bb), and for both migrants and nonmigrants (Bc). The difference in effects between electricity and radio access might be due to electricity being more dependent on public infrastructure, and that electricity access may come with a time lag to other development indicators such as employment and access to radio, since a battery radio can be bought and used instantly, and easily moved. 26", "output": {"entities": {"named_data": [{"text": "the two last DHS surveys"}], "descriptive_data": [{"text": "a wealth index"}], "vague_data": [{"text": "Wealth data"}]}}}
{"input": "use two complementary geocoded household data sets to analyze outcomes in Ghana: the Demographic and Health Survey (DHS) and the Ghana Living Standard Survey (GLSS), which provide information on a wide range of welfare outcomes. The paper contributes to the growing literature on the local effects of mining. Much of the academic interest in natural resources is focused on country-wide effects, and this research discusses whether the discovery of natural resources is a blessing or a curse to the national economy. Natural resource dependence at the national level has been linked to worsening economic and political outcomes, such as weaker institutions, and more corruption and conflict (see Frankel 2012 and van der Ploeg 2011 for an overview). While all these effects can have household-level implications, fewer analyses have, thus far, analyzed the geographic dispersion of such impacts. A recent literature on the local and subnational effects of natural resources contributes to the understanding of such effects (for example Aragón and Rud 2013, 2015; Axbard et al., 2016; Benshaul-Tolonen 2018, 2019; Caselli and Michaels 2013; Corno and de Walque 2012; Fafchamps et al. 2016; Kotsadam and Tolonen 2016; Loyaza et al 2013; Michaels 2011; von der Goltz and Barnwal 2019; Wilson", "output": {"entities": {"named_data": [{"text": "Demographic and Health Survey (DHS)"}, {"text": "Ghana Living Standard Survey (GLSS)"}], "descriptive_data": [], "vague_data": [{"text": "geocoded household data sets"}]}}}
{"input": "this study, we consider hundreds of thousands of such locations. This means that, globally, hundreds of 1-in-100 year flood events happen every year. **3.2.** **Population density** This study estimates the location of people using the Global Human Settlement Layer (GHSL), produced by the EC JRC. It offers global coverage and is available for the years 1975, 1990, 2000, 2015, and 2020. While GHSL provides several layers (including those specifying built-up areas, population, and settlements), this study uses the population density map (GHSL-POP 2020). In a raster format, this data set provides the number of inhabitants per cell, with a resolution of 3 arc seconds (approximately 90 by 90 meters), thus specifying the distribution of population. This information is based on administrative or census-based population data, which is then disaggregated to grid cells based on distribution and density of built-up area, which in turn is derived from satellite imagery. For details of the methodology, see Freire et al. (2016). 6", "output": {"entities": {"named_data": [{"text": "Global Human Settlement Layer (GHSL)"}, {"text": "population density map (GHSL-POP 2020)"}], "descriptive_data": [], "vague_data": [{"text": "administrative or census-based population data"}]}}}
{"input": "and grievances management. By implementing these measures, the project aims to create a robust and dynamic social registry that will not only address current needs but also adapt to future challenges. **Component 2: Access to Socio-Economic Infrastructure and Development of Economic Opportunities (** _**total IDA**_ _**US$14 Million equivalent, including WHR US$4.5 Million**_ **)** 40. **This component will finance basic socio-economic infrastructure to increase access to services (e.g.,** **electrification, water and sanitation, renewable energy, health and education facilities, roads and utilities) for** **vulnerable communities, including refugees and hosts, in addition to productive economic assets (US$11 Million).** Additionally, it will provide targeted support to facilitate or enhance access to economic opportunities and sustainable livelihoods in target rural areas (US$3 Million). As such, activities under this component will aim to create social and economic development opportunities for the populations in underserved areas, and for refugees and host communities in refugee-hosting areas, and facilitating sustainable solutions to protracted refugee situations. 41. **Supporting an integrated service delivery platform to foster economic growth and jobs creation, the approach** **will leverage socio-economic infrastructure investments in underserved target locations.** It will support productive facilities and strengthen market access. The compounded effect of these investments – expanding access to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "A combination of geographical targeting, categorical targeting, ProxyMeans Targeting (PMT) and community-based targeting (CBT) mechanisms will be used in a complementary way to identify beneficiaries and minimize exclusion and inclusion errors that may arise from inadequate coverage of the social registry and biases that result from community beneficiary identification. The main basis for beneficiary targeting will be the PMT using information from the social registry. However, the CBT will be done in areas not covered by the social registry while enrolled beneficiaries will be validated through community visits and public meetings. Among the target households, C4N will specifically prioritize families with young children and pregnant women living in extreme poverty, recognizing that these households encounter significant barriers in accessing essential nutrition and health services. Female recipients will be disproportionately targeted (women to make up at least of 75 percent of cash transfers beneficiaries). 34. **With regard to the SBCC, the sessions will seek to empower mothers, including from households among** **refugees and host communities, with knowledge about proper nutrition and meal preparation, good hygiene practices,** Page 10", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "the social registry"}], "vague_data": []}}}
{"input": "wetland service and valuation methods used, with the average annual wetland value reported to be approximately USD 2,800 ha [-1] yr [-1] at 1995 USD (see Brander et al. 2006 for details). However, Brander et al. (2006) pointed out that the median value in their sample is USD 150 ha [-] 1 yr-1 at 1995 USD, thus suggesting a skewed distribution of values with a long tail of high values. The authors also found that higher values per hectare were observed in North America and Europe, all other things being equal. For the purpose of this analysis, we first assumed that a value of USD 150 ha [-1] yr [-1] at 1995 USD applies to all wetlands in all regions, as the median is a better measure of the central tendency for positively skewed distributions. We converted this number to USD 2000 [22] and used this number to estimate the economic value of the quantity of vulnerable wetlands presented in 21 Brouwer at al. (1999), in their analysis, selected their sample exclusively from studies using contingent valuation as the means of valuation. Woodward and Wui (2001) included 39 valuation studies in their analysis with of these studies from the United", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "direct and effective support to frontline schools; and (iii) Improving decision-making with a data-driven approach, improving information systems and planning, which requires more accurate cost estimation and resultsoriented strategic planning. These measures would allow the MEP to optimize its management and fulfil its mandate to ensure that resources are used effectively to support the learning and development of students throughout the country. [17] **Inclusion: Gender, Refugees and Migrants, and Indigenous Peoples** 11. **Gender parity between boys and girls to access STEAM related jobs is a challenge on which Costa Rica has made** **progress, but more policy action is needed.** PISA 2022 mean scores for Costa Rica in Reading are above LAC’s average (415 vs. 400), as well as mean scores in Mathematics (385 vs. 374) and Sciences (411 vs. 400). Figure 1a shows that there is a statistically significant gender gap in Mathematics but not in Reading and Science as observed in PISA data. Looking at graduates of pre-university technical education (mainly technical stream secondary education) one finds an interesting pattern comparing three specializations (Figure 1b). Gender disparities are high in Electronics and Automation, less in Software Development and were recently eliminated in Network and Database Design. The final example", "output": {"entities": {"named_data": [{"text": "PISA 2022 mean scores"}, {"text": "PISA data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "(l) annual external audits will be conducted and the Management Letters will be submitted to the World Bank within six months after the end of the financial year; (m) IAs will be responsible to take timely action on audit report findings and notify the same to the World Bank. With implementation of these actions, the FM assessment concludes that the current arrangements will provide reasonable assurance that the project resources will be used for the intended purposes. **Procurement** 77. **Procurement will be carried out in accordance with the World Bank Procurement Regulations for** **Borrowers under IPF**, dated July 2016, revised February 2025, sixth edition, hereafter referred to as the ‘Procurement Regulations’. The project will be subject to the World Bank’s Anticorruption Guidelines, dated July 2016, and beneficiary disclosure requirements. The project will use the Systematic Tracking of Exchanges in Procurement (STEP), a planning and tracking system that will provide data on procurement activities, establish benchmarks, monitor delays, and measure procurement performance. 78. **As per the requirement of the Procurement Regulations, a Project Procurement Strategy for Development** **(PPSD) sets out the selection methods to be followed** in the procurement of goods, works, non-consulting and consulting services financed by the World Bank.", "output": {"entities": {"named_data": [{"text": "Systematic Tracking of Exchanges in Procurement"}], "descriptive_data": [], "vague_data": []}}}
{"input": "work was carried out in which 14 semi-structured interviews were conducted. Representatives of the key institutional bodies that deal with refugees and asylum seekers were interviewed; namely the state (officials and politicians); civil society (senior NGO staff and academics); and personnel at the Office of the United Nations High Commissioner for Refugees (UNHCR). It further draws on a multidisciplinary review of academic papers, key governmental documents and diverse media reports. [1] 1Three key newspapers are cited; _Haaretz –_ a central-left newspaper, _Jerusalem Post_ - a central-right newspaper and _Ynet,_ a news website, owned by Israel‘s most popular, politically-mainstream newspaper _Yedioth Aharonot_ 1", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "are described in table 2. The average village has an area of about 7,500 mu (5 km [2] ) of which some 51% were 13 To test for presence of pre-reform trends for variable _Yit_ in household _i_ in year _t_, we use the pre-reform sample to estimate ��� ������� ����� �������� ����where _Ci_ is an indicator variable for location inside Chengdu and _Tit_ is a time. With _β2_ and _β2_ + _β3_ as the pre-reform trend for households outside and inside the Chengdu boundary, significance of _β3_ .implies that the parallel trends assumption can be rejected and we report the level of significance for this variable in table 1, col. 7. 10", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "group-based revolving funds and start-up grants to approximately 234,500 beneficiaries to enhance their economic investments and value chain engagement. PCM of US$10 million has been added to the financing table based on beneficiaries' monthly collective 10 Climate Risk Profile: Uganda (2021): The World Bank Group. 11 “Uganda’s Intended Nationally Determined Contribution.” Ministry of Water and Environment, October 2015. 12 Internal Displacement Monitoring Centre. Global Internal Displacement Database - Disasters. IDMC (2023). 13 UNHCR and partners are reporting increased rates of refugee suicide. Page 3", "output": {"entities": {"named_data": [{"text": "Global Internal Displacement Database - Disasters"}], "descriptive_data": [], "vague_data": []}}}
{"input": "_UNHCR and partners worked to ensure that unaccompanied and separated children (UASC) continue_ _to receive on-going monitoring, while newly separated children are placed in appropriate temporary_ _care arrangements._ Restriction measures, and the subsequent impact operation has also been working with families and on the household income has had a significant individuals to identify caregivers for effect on families’ ability to continue to care for unaccompanied children. unaccompanied and separated children. In addition, these measures also prevent UNHCR In Ecuador and Jordan, UNHCR and partners, staff and partners from carrying out the together with the national child protection monitoring of alternative care arrangements, and systems have increased the capacity for the identification of new unaccompanied and community-level identification of unaccompanied separated children. The COVID-19 pandemic and separated children, and organised has also prevented the identification of temporary transportation to care facilities. Capacity-building care arrangements for children who are and support to the national system continues to separated from their parent(s) or caregiver(s) who be strengthened through the deployment of have been hospitalised – which continues to be UNHCR staff to the national system – one of an additional challenge and presents a significant many mechanisms of cooperation established protection risk to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "poverty. The project will provide C4N support to help vulnerable individuals cope during shocks in areas where the combined exposure to hazards and vulnerability is among the highest in the country. Indeed, hazard mapping shows that the share of population exposed to flooding in the Dikhil region is estimated to be a bit higher than one-third of the exposure level in Djibouti Ville. The financial inclusion subcomponent will further build communities’ resilience to these shocks. Resilient infrastructure supported by the project will contribute to the objectives of the NAP strengthening community resilience. **II.** **PROJECT DESCRIPTION** **A. Project Development Objective** 22. The Project Development Objective (PDO) is to improve access to basic services and safety nets, and enhance economic opportunities for vulnerable communities, including refugees and host communities in target areas. 23. This integrated approach combines investments in basic services, social protection, and economic opportunities to address the multifaceted needs of vulnerable communities, including refugees and host communities. By linking safety nets with livelihood opportunities and broader socio-economic development, the project aims to foster resilience, inclusion, and sustainable economic growth in target areas. These include underserved regions such as Dikhil and refugee-hosting locations facing pressures from population inflows, strained public services,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "to their Grade; Indicator 4: Percentage of technical stream secondary education students with micro-credentials registering English proficiency (all these indicators will be disaggregated by gender and by indigenous and refugee/migrant status). [23] 23 The Project will support block-chain backed micro-credentials (these are authenticated digital certificates, with the block-chain ensuring the authenticity). The information infrastructure and outreach to employers required to bring micro-credentials into regular use is an end in itself as a precursor to a digitally founded lifelong learning trajectory for students. While micro-credentials would be awarded for a number of employability related competency areas, the PDO choses English proficiency as central to the challenge of a Spanish-speaking population adopting to the needs of a globalized work force, especially important for Costa Rica, with trade accounting for 80 percent of the GDP. Page 7", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The World Bank Economic Review 705 One important clarification of these results is that most potential buyers living in a village that had experienced payouts would have also experienced uninsured rainfall shocks during the same season. Therefore, it may be possible that there are effects of trust and learning, but they are outweighed by opposite effects of the weather. As shown in the previous section, rainfall shocks tend to have a negative effect on insurance demand, so the (lack of) evidence of spillovers may be a result of a more complex interaction between trust/learning and direct effects of weather. Overall, these results do not support the hypothesis that trust, learning, or any other effects of simply witnessing insurance payouts are driving increased purchasing. Although it is possible that the measurements of spillovers are too crude and miss more subtle effects, the data simply does not provide evidence that there are strong spillover effects. The lack of visible spillover effects casts doubt on the theory that repurchases are being driven by increased trust in the insurance company or learning about insurance payouts. Notably, this result stands in contrast to recent results that do document spillover effects of insurance payouts (Cole, Stein,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "negative first-order autocorrelation in rainfall that appears to be driven by rains early in the season. The bottom two rows test for autocorrelation of rainfall shocks using the parameters of the 2005 insurance policy to determine shocks. “Would Have Been Payout” is a dummy variable that takes a value of 1 if the insurance policy of 2005 would have given a payout; “Total Insurance Payout” is the size of this payout. By these measures, shocks do not appear to exhibit significant positive first-order autocorrelation. **Table 4.** Rainfall Autocorrelation **Fixed effects** **Arellano-Bond** **(1)** **(2)** Total rainfall −0.106*** −.086*** (.030) (.021) Phase 1 rainfall −.090*** −.075*** (.030) (.029) Phase 2 rainfall −.018 −.026 (.030) (.028) Phase 3 rainfall −.029 .007 (.030) (.028) Would have been payout .023 .017 (.030) (.022) Total insurance payout −.0353 .004 (.030) (.028) _Notes_ : Coefficients reported are from separate univariate regressions. The Fixed Effects specification is OLS with six lags of the dependent variable. The Arellano-Bond regression contains one lag of the dependent variable, with this lag instrumented by five previous lags. Observation are years 1967–2004 for the fixed-effects regression, and years 1962-2004 for the Arellano-Bond regression. All regressions contain weather station fixed effects. Robust standard errors", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "increased from 27,993 in 2018 to 273,066 by December 2023. While the country offers public education to all children regardless of migratory status, more efforts are needed to ensure that enrollment requirements do not exclude migrant children from the classroom, and that learning environments are inclusive. As of September 2023, 64,455 students enrolled in the Costa Rican education system were foreigners (5.4 percent of the total student population). According to administrative registries, 38,870 migrant students (60.3 percent of the total migrant student population) are under irregular status or pending regularization. [20] The issue of disabilities is also a priority item for Government policies on inclusion. MEP statistics indicate 19,643 students with disabilities, with alternative solutions providing services to 81 percent of the disabled students and 2,672 students with a need gap that MEP intends to address. The Government policy includes the provision of tailored teaching methodologies and materials designed to facilitate the full participation, retention, and educational advancement of students with disabilities, as well as facilitation for their transition to the labor market. 13. **Indigenous students face additional educational challenges related to the low availability of educational** **materials in indigenous languages.** There are an estimated 16,000 indigenous students from eight", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "MEP statistics"}], "vague_data": []}}}
{"input": "accounts for OPM and IG into the OPM operations and implementation account and IG’s operations account, both denominated in Uganda Shillings (UGX). Payments for eligible expenditure by OPM and IG can be made from either their US$ or UGX accounts. Transfers by OPM to districts, cities, and urban centers will be done from the operations account to the consolidated fund (holding account) managed by the Office of the Accountant General. Each district, city and urban center fund will have a budget code for the project to account for the funds held in the holding account. The budget codes will be segregated for operations and subprojects. Payments to communities, suppliers, or other beneficiaries by the local governments will be approved by the CAO or City/Town Clerk and Chief Finance Officer (CFO) through the Integrated Financial Management Information System (IFMIS). Thereafter, MoFPED will transfer funds from the consolidated fund into the Treasury Single Account (TSA) to make payments. Subproject payments will be made to a community bank account in a commercial bank. The CFO of the local government will authorize the opening of community bank accounts in local governments and monitor payments made through the account to ensure they are used for", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "B of table 4), the estimates point toward an increase in agriculture, services, and professional (all statistically insignificant estimates), but a decreased likelihood of working in manual labor. Results for men in panel B are largely insignificant, and it is worthwhile noting that the sample size is only slightly above 50% than the women sample size due to DHS sampling frame. **Table 4 OLS estimates women’s and men’s occupation in the DHS individual-level analysis** Occupation 9 Service sector jobs in the wake of structural transformation has been found important in increasing women’s work hours and reduce the gender wage gap (Ngai and Petrongolo, 2017). 17", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "DHS"}], "vague_data": []}}}
{"input": "CRITICAL FUNDING NEEDS IN MENA / 10 OCTOBER 2024 **Health** Underfunding will severely limit UNHCR’s ability to provide essential health services for 35,000 members of Sudanese refugee and host communities - including vulnerable groups such as children, pregnant women, the elderly, and individuals with chronic health conditions - leading to increased morbidity and mortality rates. Without adequate funding, critical interventions such as medical supplies, vaccinations, maternal and child health services, and treatment for communicable diseases will be drastically reduced. This shortage will exacerbate existing health challenges, potentially leading to outbreaks of preventable diseases and worsening overall public health conditions. Moreover, the inability to support health facilities adequately will strain the local healthcare infrastructure, diminishing both the quality and accessibility of care for all populations involved. **Protection** Local authorities and ministries in the east are implementing a registration system and documentation to facilitate access to services and freedom of movement, in accordance with the Ministry of Interior’s decision. So far, authorities have registered and issued 30,000 cards, but their resources have quickly depleted and they are running out of resources to continue registration. UNHCR has been requested to support this initiative, as resource shortages risk preventing further registration, exposing refugees to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Vermeer, M. and S. Rahmstorf. 2009. Global sea level linked to global temperature. _Proceedings_ _of the National Academy of Sciences_ 106 (51), 21527-32. VLIZ. 2011. Maritime Boundaries Geodatabase, version 6.1. Available online at [http://www.vliz.be/vmdcdata/marbound. Consulted on 2011-05-12.](http://www.vliz.be/vmdcdata/marbound) Williams, M., 1990. Understanding Wetlands. In M. Williams (ed) _Wetlands: A Threatened_ _Landscape_ . Wiley-Blackwell. Woodward, R.T. and Y.S. Wui. 2001. The economic value of wetland services: A meta-analysis. _Ecological Economics_, 37, 257-270 World Bank, 2010. Boundaries of the World. Map Design Unit. The boundaries, colors, denominations and any other information shown on this map do not imply, on the part of the World Bank Group, any judgement on the legal status of any territory, or any endorsement or acceptance of such boundaries. 25", "output": {"entities": {"named_data": [{"text": "Maritime Boundaries Geodatabase, version 6.1"}, {"text": "Maritime Boundaries Geodatabase"}], "descriptive_data": [], "vague_data": []}}}
{"input": "selection model provides consistent, asymptotically efficient estimates for all parameters in the model (Dubin & McFadden 1984). **3. Empirical results** The empirical analysis is based on a household survey conducted of 11 countries across Africa: Burkina Faso, Cameroon, Egypt, Ethiopia, Kenya, Ghana, Niger, Senegal, South Africa, Zambia and Zimbabwe (for more information about the entire study, see Dinar et al. 2006). It was difficult to collect land values in this setting. We consequently relied on measures of net revenue per hectare. Net revenue is defined as gross revenue minus the cost of transport, packaging and marketing, storage, post-harvest losses, hired labor (valued at the median market wage rate), light farm tools (such as files, axes, machetes, etc.), rental on heavy machinery (tractors, ploughs, threshers and others), fertilizer and pesticide. Median district prices from the survey were used for both input and crop prices. Household labor costs are not included as a cost in net revenues because it was not clear what value to assign to wages. We controlled for household labor by using household size as a proxy. In each country, districts were chosen to get farms across a wide range of climate conditions in that country. In each chosen", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "household survey"}], "vague_data": []}}}
{"input": "with the institutional rating, we normalize this mean indicator to the range [0 - 100]. Our composite indicator is the product of the normalized environmental index and CPIA rating. Table 2.1 illustrates the calculation of the policies and institutions indicator for four countries in Sub-Saharan Africa. This indicator (row 8) equals the product of the indicator of institutional development problems (row 7) and the indicator of overall environmental problems (row 6). The latter is the average of problem indicator values for global emissions, pollution, fragile lands, biodiversity and water resources. The four country cases illustrate the contributions of separate components to the final indicator values. Chad has a low overall environmental indicator (.69) but a very high institutional indicator (5), yielding a product of 3.44. South Africa’s overall environmental indicator (4.24) is about six times Chad’s value, but its institutional indicator (2) is much lower because its institutions are more highly-developed. The resulting composite indicator for South Africa (8.49) is about 2.5 times Chad’s indicator value (3.44). Kenya has about the same composite indicator value as South Africa (8.35), but the indicator components are quite different. Kenya’s environmental indicator (2.39) is somewhat more than half of South Africa’s (4.24), but", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "efficiency of land use and leaving landlords as well as occupants worse off. The continued importance of agriculture for economic development and poverty reduction in Uganda implies that, in addition to exploring the magnitude of possible underinvestment on lands without clear property rights, finding ways to increase investment could have high social benefits. With more than 85% of the population still living in rural areas and agriculture accounting for 77% of employment and 50% of total output (Belshaw _et al._ 1999), land-related investment will be critical for growth and poverty reduction. Household survey data point towards a large and possibly widening gap between rural and urban levels of consumption and recent increases in poverty. After decreasing from 59.7% in 1992 to 37.4% in 1999/2000, rural poverty increased to 41.1% in 2002/2003. The fact that poverty among crop farmers is much above the rural average (Kappel _et al._ 2005), something that is often attributed to limited agricultural productivity growth (Republic of Uganda 2005), implies that ways to increase agricultural productivity will be critical to prevent widening of rural-urban income gaps. Land-related investments will be critical in this respect because the scope for expansion of cultivated area which, together with elimination of", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "Household survey data"}], "vague_data": [{"text": "Household survey data"}]}}}
{"input": "compare results with the main specification in table 3, I again provide a dummy for whether there was a payout in the village along with a quadratic effect of the ratio of payouts to the premium. When aggregating the village data, I use the mean of the payout ratios in the village to create a payout ratio for the village. [16] The overall results of the table tell a consistent story: significantly sized payouts drive repeat buyers but not new purchasers, showing few spillover effects. Columns 1 and 2 shows how payouts affect the number of total and repeat buyers, respectively, the next year, and the results are very consistent with the baseline results from table 3. A dummy for whether there was any payout is negative, but the payout size has a positive effect. This suggests that low payouts have a marginally negative effect on the number of repeat purchasers, but this effect flips to positive as the size of the payout ratio increases above approximately 1. Column 3 shows the effect of payouts on new buyers in a village. Here, all the payout coefficients show a different pattern than for new buyers, but due to large standard errors", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "village data"}]}}}
{"input": "estimate the inundation depth at a grid cell level of 3 arc-seconds, (~ 90 m) and provide coastal surge hazard layers, along with pluvial and fluvial layers. The maps provide information on the extent and depth of flood hazard for a specific location. For the coastal component, we explicitly model four return periods - 25, 50, 100, and 200 year events, under current and future climate conditions.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Bank's response. We begin by constructing an overall indicator of environmental problems from our thematic indicators. Using regression analysis, we find a strong relationship between countries’ general indicator values and the scale of their environmental borrowing, but a relatively weak relationship for AAA. At the thematic level, we find that problem indicators have relatively weak relationships with both lending and AAA. Adding country risk to the analysis, we test an optimal allocation model and find that it is consistent with the Bank’s actual lending and AAA since 1998. We conclude that our model’s assignment of lending and AAA to countries reflects the Bank’s actual experience with partner countries. The model’s explanatory power is relatively low, however, and when we compare model assignments to actual allocations, we find many large discrepancies for countries and environmental themes. Some gaps may reflect activity by other donor institutions, but many others may represent problems with efficient implementation of the Bank’s Environment Strategy. To promote further discussion of this issue, we use our optimal allocation model to develop measures of lending opportunity by environmental theme for the Bank's partner countries. 2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**A. Technical, Economic and Financial Analysis** 59. **The project is technically feasible and focused on enhancing the implementation of legislation and policies on** **refugees while ensuring service delivery to both host and refugee populations in Zambia.** The proposed design responds to gaps identified by the MoHAIS, district level officials in Meheba, various line ministries and the UNHCR. This was confirmed by information and data shared during project preparation. The project draws on analytical and operational work on refugees and host communities across World Bank operations in the region. Component 1 of the project is designed to focus on visible and practical changes in policies that tangibly improve the experiences of refugees while fostering longer term legislative reform. Component 2 on infrastructure adopts a multi-sectoral approach by working with both line ministries and local level district officials to achieve enhanced services for both refugees and host communities and in many cases, expand on existing objectives or scale up well tested designs. Component 3 builds on experiences from and synergies with the World Bank financed Zambia Agribusiness and Trade Project (P179507), as well as numerous national agri-business support programs in Meheba to: 1) foster strong participation among farmer cooperatives to ensure sustainable", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Act of 2010) that will enhance opportunities for protection and solutions for self-reliance. [16] To assist policy delivery, the Government has established an interagency National Steering Committee chaired by the Office of the Vice President. In March 2023, the MoHAIS launched a plan for the Modernization of Refugee and Host Community Settlement Areas (MORHCSA) which seeks to turn the new Refugee Policy into action on the ground. 15. **The World Bank Group, following consultation with the UNHCR, confirms that the protection framework for** **refugees continues to be adequate in Zambia.** Zambia meets the eligibility criteria for accessing the International Development Association replenishment (IDA20) Window for Host Communities and Refugees (WHR). The country currently hosts 101,837 refugees, exceeding the threshold of 25,000 required under the window. [17] The GRZ has signed and ratified the 1951 United Nations Refugee Convention and the 1967 Protocol relating to the Status of Refugees. The Government has also ratified the African Union Convention for the Specific Problems of Refugee Populations in Africa. To 13 There are a total of 19 primary and 7 secondary schools and 10 health posts in the settlements. One Meheba Local Area Plan, Planning Survey and Issues Report, GRZ, 2023. 14 Consultations", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Access to decent work:** The key barrier to accessing work, according to respondents who are unemployed, is a lack of knowledge of the Czech language (59%). This finding was also reflected in focus group discussions conducted by UNHCR with Ukrainian refugee women and men in Brno, Ostrava in Prague in August and September, where refugees reported challenges in securing jobs that matched their qualifications due to language barriers. All participants in the focus group discussions emphasized the need for better language proficiency to improve their employment prospects. of Protection Monitoring respondents of working age are employed in host country Nevertheless, 67% of respondents reported being employed compared to 60% in Q1. . [4] Moreover, respondents’ access to earnings also increased from 87% to 93% during the same time period. Working excessively long hours also decreased from 24% to 16%. These findings ostensibly indicate an improvement in access to employment and in working conditions amongst Ukrainian Temporary Protection holders. Employment continued to be mentioned as one of the top two priority needs (32%) of households interviewed. Moreover, in terms of information, 29% of respondents indicated a need for more information about job opportunities; this continued to be the highest reported information", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Economics of Disasters and Climate Change Fig. 1 A visual of what the combined hazard maps (which include coastal and fluvial/pluvial) look like. The map presented here is the worse-case scenario we simulate, a 200-year return period flood with high sea level rise number of people within each district who live below the poverty line: this Bpoverty map^ is displayed in Fig. 3a, and the full methodology can be found in (Lanjouw et al. 2013). [3] In addition, we use gridded population density data with a 1 km resolution from Landscan (Geographic Information Science and Technology 2015). This Bpopulation map^ is displayed in Fig. 3b. While we are able to simulate current and future flood hazard, we are unable to project socioeconomic characteristics like poverty or population at the district level, as such an exercise is extremely challenging. Specifically for Vietnam, a recent paper models population and poverty in 2030 at national-level, but notes that examining how these dynamics is distributed spatially within the country is still not possible (Rozenberg and Hallegatte 2016). Nonetheless, as a stress test, a number of papers in the field have employed the same strategy we follow in this paper, of using current socio-economic characteristics", "output": {"entities": {"named_data": [{"text": "Landscan (Geographic Information Science and Technology 2015)"}, {"text": "Landscan"}], "descriptive_data": [{"text": "gridded population density data"}], "vague_data": []}}}
{"input": "fixed effects, the two strategies are complementary. While the district-level analysis informs us about differences across and within districts over time, the local-level analysis gives us the additional impact at the very local level. This means that any differences in effects across district and local analysis should not be interpreted as inconsistencies, but rather as differential and additional impacts. In a difference-in-differences setting, it is important that the sample is balanced, assuming that the treatment and control groups are on similar trajectories. Table 2 shows the summary statistics for the women’s surveys across four different groups, close and far away, and before and during the mine’s production phase. Columns 1 and 3 show mean values of the population that live far away from mines, before and during mining respectively. Columns 2 and 4, in 14", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "the women’s surveys"}], "vague_data": []}}}
{"input": "Policy Research Working Paper 7250 ### **Abstract** Ghana is experiencing its third gold rush, and this paper sheds light on the socioeconomic impacts of this rapid expansion in industrial production. Using a rich dataset consisting of geocoded household data combined with detailed information on gold mining activities, the authors conduct two types of difference-in-differences estimations that provide complementary evidence. The first is a local-level analysis that identifies an economic footprint area very close to a mine, and the second is a district-level analysis that captures the fiscal channel. The results indicate that men are more likely to benefit from direct employment as miners compared to men further away, and that women in mining communities may more likely gain from indirect employment opportunities and earn cash for work. Authors also find that infant mortality rates decrease significantly in mining communities, compared to the evolution in communities further away. This paper is a product of the Office of the Chief Economist, Africa Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "geocoded household data"}], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) **2024.** The Project is specifically aligned with CPF Objective 3: Supporting results-oriented management and quality for all in the education sector _._ Priorities for the education system described in the CPF include elements that inform the proposed Project: (i) quality of education; (ii) equity in educational opportunity; and (iii) relevance of education for success in the labor market. Finally, the CPF mentions that closing the digital skills gap is critical to reduce the illiteracy and income inequality divide. The inclusion of digital competencies as curricular content in the educational system will stimulate internet access and use. The Project will also support the CPF approach to foster skills for green jobs and employability in high value-added sectors. It is aligned with Outcome 2 regarding building and protecting human capital of the World Bank’s Gender Strategy 2024-2030. Further, the Project directly addresses global challenges related to the effects of situations of fragility, conflict, and violence as a global challenge, and contributes towards indicator 14 of the World Bank’s Scorecard by providing improved education services to displaced populations and people in host communities. 18. **The Project is consistent with Costa Rica’s Nationally Determined", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "1 Zamstats.gov.zm. 2 Zambia Statistics Agency. 2023. _Highlights of the 2022 Poverty Assessment in Zambia_ . World Bank. 2023. _Zambia Gender Assessment_ . 3 Zambia: Selected Issues, IMF, 2023. 4 2022 Census of Population and Housing, GRZ 2023. 5 According to the 2021 Labour Force Survey Report by Zamstat, the working-age population (15 and older) is 10 million, of which only 3.1 million are employed. 6 Zambia: Selected Issues, IMF, 2023. 7 Zambia: Selected Issues, IMF, 2023. Page 8", "output": {"entities": {"named_data": [{"text": "2022 Census of Population and Housing"}], "descriptive_data": [], "vague_data": []}}}
{"input": "devastating conflict in **Yemen** have left 18.2 million people dependent on humanitarian assistance. In **Iraq**, UNHCR also urgently needs resources to continue supporting the authorities in ensuring access to civil documentation and inclusion in the national social safety net for some 1 million internally displaced Iraqis. UNHCR is responding to two refugee situations in **Algeria** : a nearly 50-year-old displacement of Sahrawi refugees in five refugee camps near Tindouf in the south-west of the country, and an urban asylum-seeker and refugee population of diverse origin in Algiers and other governorates. **Mauritania** has hosted a significant number of refugees since 2012 and continues to face a large influx of Malian refugees; more than 100,000 people have arrived in 2024 alone. UNHCR is providing vital assistance to the most vulnerable refugees and invests in the resilience of more than 250,000 refugees as well as host communities in the Hodh Chargui region. The number of refugees and asylum-seekers registered with UNHCR in **Morocco** increased significantly in recent years. UNHCR works to ensure access to asylum and protection under the framework of the National Strategy for Immigration and Asylum (SNIA) and towards the inclusion of refugees and asylum-seekers in national social protection systems. Amid", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": ".77. One point of concern with these results is that there are many cases where there are multiple purchasers of insurance in a certain village in one year and then zero in the next year. Although this could be the result of people simply being unsatisfied with insurance, the large amount of villages that suddenly drop to zero purchasers is suspicious, especially since the BASIX data does not contain information about whether marketing activities took place in a given village in a given year. For all the villages that had purchasers in one year and then none in the next year, it is quite likely that no BASIX representative visited the village; therefore the customer did not really have a chance to purchase the insurance. If this was the case, it would make sense to exclude these villages from the analysis, as the previous year’s payout would have no way to possibly influence a customer’s purchase decision. In columns 3 and 4 I exclude villages that had no purchasers the following year from the analysis, creating what I call the “Marketing Restricted Sample.” Restricting the sample this way results in a drop of the number of observations from 10,977 to", "output": {"entities": {"named_data": [{"text": "BASIX data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) **Figure 1b: Technical education graduates by gender in strategic STEAM fields** 12. **By the end of 2022, Costa Rica was hosting 270,636 forcibly displaced and stateless people, and the uneven** **preparedness of these students strains the education system.** [19] Even if the influx of migrants and refugees acts as a positive factor for some schools that would be facing closure due to decline of the native-born population, the education system faces stress because of the differential quality of preparedness and disruptions faced by immigrant students. In recent decades, the country has seen the arrival of migrants and refugee applicants fleeing political and economic conditions in Colombia, Cuba, El Salvador, Nicaragua, and Venezuela. According to the United Nations High Commissioner for Refugees and administrative records from the General Directorate of Migration and Foreigners, the number of asylum seekers in Costa Rica increased from 27,993 in 2018 to 273,066 by December 2023. While the country offers public education to all children regardless of migratory status, more efforts are needed to ensure that enrollment requirements do not exclude migrant children from the classroom, and that learning environments are inclusive. As of September 2023,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "has also ratified the African Union Convention for the Specific Problems of Refugee Populations in Africa. To 13 There are a total of 19 primary and 7 secondary schools and 10 health posts in the settlements. One Meheba Local Area Plan, Planning Survey and Issues Report, GRZ, 2023. 14 Consultations with health care workers and UNHCR at the Meheba settlement report a high number of unnecessary deaths of expectant mothers due to inadequate services and the poor quality of the access road. 15 Zambia National Statistical Report, Ministry of Home Affairs and Internal Security, May 2024. 16 They include, among others _,_ the Immigration and Deportation Act, Refugees Act No.1 of 2017 and amendments to other legislation, such as the Lands Act CAP 184, Higher Education Bursaries and Scholarships Act no.31 of 2016, Birth and Death Registration Act CAP 51, Citizenship Act of No 32 of 2016. 17 Zambia National Statistical Report, Ministry of Home Affairs and Internal Security, May 2024. Page 11", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "discussions with refugees from Ukraine across the country in the first quarter of 2024. ## Key Figures 338,736 320,000 ## 338,736 320,000 Temporary Protection holders in Czechia among whom have registered for an extension ## 92% of Protection Monitoring respondents are Temporary Protection holders ## 32% of respondents have at least one household member missing documentation or whose documents have expired ## 75% of respondents are women and children ## 39% Consider accommodation an urgent need", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "detail as to allow for regular and effective implementation and monitoring of all the activities to be funded. The budgets will be activity based and will be used to monitor performance during the implementation of activities. The project’s annual work plan and draft budget will be informed by the Grant Agreement. The total project cost and activity work plan will be agreed up front, and any variations will need prior approval by the World Bank. The annual work plan and budget will be submitted to the World Bank Task Team Leader for prior review and no-objection clearance no later than November 30 before the start of the coming financial year. Utilization of the budget will be monitored through quarterly Interim Financial Reports (IFRs) by analyzing overutilization and underutilizations and using the reports as management’s tool for decision-making. 5. **Disbursement and funds flow** . The project will be on statement of expenditure method of disbursement whereby the Designated Account (DA) will have a fixed allocation of funds. The project will report expenditures and request for monthly replenishment of the DA. The project will open two US$ DAs (DA-A for the MoHAIS and DA-B for the MoHAIS Kalumbila Town Council [KTC] -", "output": {"entities": {"named_data": [{"text": "quarterly Interim Financial Reports"}], "descriptive_data": [], "vague_data": []}}}
{"input": "in farming. Low income is reflected in poor food security, with almost 60 percent of refugee households reporting that they typically eat only one meal per day. The main reasons provided for the low employment levels were lack of skills (44 percent) and lack of information about the local labor market (34 percent). Other reasons cited include the need for investments in roads and connectivity to strengthen market access for agricultural producers and traders. A 2024 African Development Bank (AfDB) study on forced displacement in the region concluded that priority needs for self-reliance are better road connectivity, access to water and energy, improved educational and 6 The GoR’s strategy is consistent with lessons from global experience in the 2023 World Development Report that a sustainable approach to managing forced displacement requires: (a) policies that provide freedom of movement and the right to work; (b) inclusion of refugees into national service delivery systems to shift away from expensive parallel systems; and (c) support for self-reliance through access to jobs. Page 2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) **F. Lessons Learned and Reflected in the Project Design** 41. **Education technology policies and projects should be developed with a clear purpose, strategy, and vision of** **the desired educational change.** Costa Rica’s own long experience in the use of Education Technology (EdTech) and lessons from other countries such as Uruguay have provided valuable lessons on how to achieve expected results in a context of competing priorities. A key lesson is the importance of defining a common objective early on. This means that all stakeholders involved in the Project should have a clear understanding of what they are working towards. Another important aspect is the need for a specific team to drive the change. This team should consist of individuals with technological skillsets, such as engineers and developers, as well as education planners. This combination of expertise ensures that both the technical and educational aspects of the project are properly addressed. 42. **Understanding the key elements for success within the broader political economy is essential.** As highlighted in the Moldova Governance e-Transformation Project (P121231), it is crucial to establish reform at a high strategic level of government to ensure agreement among", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "there is an effect in neighboring districts. **3.1 Resource data** The Raw Materials Data are from InterraRMG (2013). The data set contains information on past or current industrial mines. All mines have information on annual production volumes, ownership structure, and GPS coordinates on location. We complete this data with exact geographic location data from MineAtlas (2013), where satellite imagery shows the actual mine boundaries, which allows us to identify and update the center point of each mine. The production data and ownership information are double-checked against the companies’ annual reports. For Ghana, this exercise results in 17 industrial mines tracked over time. We have annual production levels from 1990 until 2012. As mentioned, Table 1 shows the mining companies active in Ghana during recent decades, with opening and closing years (although some were closed in between, and are not presented in the table). Figure 2 shows the geographic distribution of these mines. **Figure 2 Gold mines and DHS clusters in Ghana** **Panel A Gold mines and 20 km buffer zones Panel B Gold mines, DHS clusters, and 100 km buffer zones** 4 The distances are radii from mine center point, and form concentric circles around the mine. 5 The DHS", "output": {"entities": {"named_data": [{"text": "MineAtlas (2013)"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Turn Down the Heat: Climate Extremes, Regional Impacts, and the Case for Resilience [World Bank (2015) Platform for Urban Management and Analysis.^ http://puma.worldbank.org/](http://puma.worldbank.org/) World Bank (2016) Climate Change and Poverty in Vietnam. World Bank Internal Document World Bank, and GFDRR (2011) Vulnerability, Risk Reduction, and Adaptation to Climate Change - Vietnam World Bank, Australian AID (2014) ‘WHERE ARE WE DURING FLOODING?’ A Qualitative Assessment of Poverty and Social Impacts of Flooding in Selected Neighborhoods of HCMC", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Economics of Disasters and Climate Change Fig. 3 (a) Poverty map and (b) population density map for Vietnam at the district level. Sources: (Lanjouw et al. 2013; Geographic Information Science and Technology 2015) point indicating a potential slum location. Evidence suggests that slum areas exist in the northern districts of HCMC (Habitat for Humanity 2008), which we do not find in PUMA. For this reason, we ran the analyses for two samples – all the districts in the province, and only the districts with potential slums from PUMA. The potential slum locations are presented in Fig. 4. Methodology Exposure to Flooding at the National Level At the national level, we estimate per district the number of people exposed to each scenario of flooding, and the number of poor people exposed. In the flood data, we define exposed areas as those grid cells where the flood level is greater than zero; non-exposed areas are those grid cells where the flood level is zero. This is a measure of extent rather than depth, and has been used in previous studies to examine exposure to floods (Jongman et al. 2014; Winsemius et al. 2015; Ceola et al. 2014). Furthermore, while we lose information", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "flood data"}], "vague_data": []}}}
{"input": "environmental degradation and deforestation are not new phenomena in Uganda, the large-scale and long-term presence of refugees has added to the existing pressure on the environment. From 2001 to 2023, Uganda lost 1.1 million hectares of tree cover, equivalent to a 14 percent decrease since 2000. [7] Wetlands decreased from 16 percent of the country’s land area in 1994 to an estimated 10 percent in 2021, according to the Ministry of Water and Environment. In a country where 89 percent of primary energy needs are met by biomass, land degradation is a multi-faceted crisis that has been deepened by the large refugee population. [8 ] While average woodfuel consumption per person in a refugee household is lower than that of a host household, demand still averages 660 kilograms per person per year, concentrated in and around settlement areas. [9] Refugees also open up new areas of bushland and woodland for farming, either for their own production or as hired workers or sharecroppers on host community land. 4 World Bank (2023). _World Development Report 2023: Migrants, Refugees, and Societies._ Washington, DC: World Bank at p. 208. 5 Poverty rates in refugee-hosting districts during the COVID-19 crisis ranged from 37.7 percent in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "million people face high flood risk, while living on less than $5.5 per day. These findings are based on high-resolution flood hazard and population maps that enable global coverage, as well as poverty estimates from the World Bank’s Global Monitoring Database of harmonized household surveys. This paper is a product of the Climate Change Group and the Global Facility for Disaster Reduction and Recovery, and a background paper for the 2020 Poverty and Shared Prosperity Report. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at jrentschler@worldbank.org. _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development_ _issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the_ _names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those_ _of the authors. They do not necessarily represent", "output": {"entities": {"named_data": [{"text": "Global Monitoring Database of harmonized household surveys"}], "descriptive_data": [{"text": "high-resolution flood hazard and population maps"}], "vague_data": []}}}
{"input": "one hand, since 2010 urbanization and development in high-risk coastal zones has been occurring at rapid rates in many parts of the world. These trends are putting an increasing number of people in harm’s way. Human activities, such as ground water extraction, are exacerbating risks as land subsidence is increasing the extent and intensity of flooding. On the other hand, the increase in the estimated flood exposure headcount is methodological; the use of more accurate and higher resolution data, as well as the inclusion of pluvial flooding mean that this study captures flood risks more comprehensively than past studies. In addition, the Global Assessment Report (UNDRR 2017) offers estimates of risks from five major natural hazards (including flood risks), though it focuses on monetary quantifications of disaster risks. Besides such global assessments, the recent availability of high-resolution flood and population maps has enabled countless local and national risk assessments, for instance in Tanzania, the United Kingdom, the United States, and Vietnam (Chakraborty et al. 2014; Erman et al. 2019; Fielding 2012; Braese et al. 2020). **Flood risks and poverty.** Many analyses have explored the link between natural hazards – flood risks in particular – and poverty; a detailed review of", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "high-resolution flood and population maps"}], "vague_data": []}}}
{"input": "mine action. The analysis of the data resulting from this mapping combined with the analysis of the protection response monitoring data brought out the observation below: - Only two protection actors have interventions in MA which cover only a few localities of the 7 out of 11 departments affected by ED **(Ref Graph4 & Gaph2).** 4 out of 11 departments most affected by EE remain without any LAM intervention. - There is a **major gap in Explosive Device Risk Education** (EDRE) interventions in several regions affected by ED (Diffa, Tillabery, Dosso, Agadez and Niamey). - A critical lack of victim assistance is observed in all 11 affected departments ( **Ref Graph5)** . - Existing capacities have only made it possible to reach about 3,000 people [8] with EDRE [activities, representing only 2% of target set in the Humanitarian Response Plan (HRP).](https://reliefweb.int/report/niger/niger-plan-de-reponse-humanitaire-mars-2023) - 98% of the HRP LAM target is therefore not reached. In addition, 77% of the funding requirement MA interventions is not met. - There is also a **lack of human resources dedicated to coordination at national and regional** **level, prevention, and assistance to victims** . The MA Sub-Cluster has not been functional since the withdrawal of UNMAS in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "protection response monitoring data"}]}}}
{"input": "(Su _et al._ 2013), a figure that has risen further as fiscal decentralization reduced alternative revenue sources for local governments (Qun _et al._ 2015). [3] Revenue generated in this way provides a huge implicit subsidy to industrialization (Ding and Lichtenberg 2011), with negative impacts on availability of land for residential and housing purposes (Peng and Thibodeau 2012). This pattern of land development, which would be difficult to maintain without complementary restrictions in labor markets that in and of themselves may lead to considerable efficiency losses (Au and Henderson 2006b), has several consequences. First, as local governments compete to attract industry, prices for industrial land in China have remained very low (World Bank and DRC, 2014). Supplying land to industry below its real value led to inefficient use of a valuable resource; in fact a nation-wide survey in 2003 1 The average is for urban areas in East Asia with more than 5 million inhabitants in 2010 (World_Bank and DRC 2014). 2 Farmers’ residential land is often not expropriated, something that led to the spread of ‘urban villages’, i.e. unplanned neighborhoods that tend to provide shelter for migrants tend exert negative externalities on prices for neighboring properties (Song and Zenou 2009).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "nation-wide survey"}]}}}
{"input": "eligible expenditures, and other details will be defined in an updated DCRM Manual for Phase II, approval of which by the World Bank is a disbursement condition. The sub-component will: (a) fund data collection to measure strains on schools, health facilities, and water points in the RHDs; and (b) finance approximately 41 infrastructure subprojects. Through ongoing analytical work, the World Bank has developed an Artificial Intelligence (AI)-based model that predicts refugee inflows before they occur. [21] If the World Bank is able to raise funds to run the AI model live, the GoU will undertake an assessment to consider using it for Phase II to facilitate the disbursement of DCRM funding to districts before large refugee inflows occur, supporting preparedness and minimizing stress on host populations and refugees in the RHDs. **Component 2: Integrated Natural Resource Management (US$30 million equivalent)** 30. **Component 2 will support investments in environmental restoration and protection to respond to ecosystem** **degradation in the RHDs and additional impacts caused by climate change and refugee presence.** The expansion of farming by refugees and host communities is driving rapid deforestation in the RHDs, reducing the extent of natural forests and woodlands. Refugees and hosts also harvest wood for", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**6. Summary and Conclusions** In this paper, we have constructed a spatial panel database of cyclone tracks and coastal landfalls in Bangladesh, West Bengal and Odisha. For 1960-2016, our tracking data come from the Bangladesh Meteorological Department (BMD) for cyclones with Bangladesh landfalls and the India Meteorological Department (IMD) for cyclones with landfalls in West Bengal and Odisha. For storms before 1960, our data come from country reports in the global IBTrACS database maintained by the Global Data Center for Meteorology of the US National Oceanic and Atmospheric Administration. We determine each storm’s landfall as its first intersection with an ordered line of coastline points, spaced at .001 decimal degrees (approximately 100 meters). We identify each cyclone’s primary coastal impact zone as the set of coastline points lying within the cyclone’s radial distance from its landfall point to its zone of maximum wind speed. Although we confine our exercise to Bangladesh and the two Indian coastal states, our methods are general and could be expanded to an arbitrarily-large set of coastal locations. We use the database for an analysis of cyclone strike locations and impact zones in seven historical periods: 1877-1900, 1901-1920, 1921-1940, 1941-1960, 1961-1980, 1981-2000 and 2001-2016. Although we", "output": {"entities": {"named_data": [{"text": "global IBTrACS database"}], "descriptive_data": [{"text": "spatial panel database of cyclone tracks and coastal landfalls"}], "vague_data": []}}}
{"input": "flood risks. Indeed, large coastal cities are likely to be risk hotspots. Hallegatte et al. (2013) estimate the flood risks in the world’s 136 largest coastal cities. They show that population and asset growth, climate change and subsidence are all likely to contribute to a drastic increase in global average flood losses – from $6 billion per year in 2005 to over $60 billion in 2050, assuming proactive adaptation actions in all cities. Kulp and Strauss (2019) conduct a global assessment of the potential impact of sea level rise on the world’s coastal population. The global scale of their study and the use of high-resolution flood and population data makes it the closest comparable analysis of flood risk. Their assessment suggests that today between 190 million and 630 million people (depending on the emissions scenario considered) live in areas that could be inundated by sea level rise by the year 2100. They also estimate that one billion people live on land that is less than 10 meters above current high tide lines. This present study complements the one by Kulp and Strauss (2019) in several ways: First, it considers not only the one billion people living near current high tide", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "high-resolution flood and population data"}], "vague_data": []}}}
{"input": "conduct due diligence on the creditworthiness of the proposed borrowers. To minimize borrowers’ moral hazard, there will be no direct contact between the BDF and end borrowers; all information required by the BDF on borrowers and projects will be collected through the PFIs. Full details will be included in a PCG Manual, acceptance of which by the World Bank will be a condition of disbursement for this sub-component. 36. **Eligibility criteria.** The PCG will be open to creditworthy refugees. Detailed terms and conditions of the guarantees will be spelled out in the PCG manual and in a PCG Agreement to be signed between the BDF and PFIs. The BDF will be solely responsible for the selection of PFIs and monitoring of compliance with the eligibility criteria. 37. _Sub-component 2(d): Graduation for vulnerable groups (US$6.5 million)._ To support highly vulnerable refugees and host community members who are not bankable, graduation-style programming will be introduced in Phase II. Sub-component activities will target individuals living in extreme poverty who face barriers such as lack of collateral, limited financial literacy and social exclusion. MINEMA will contract an implementing partner to support at least 2,500 households (70 percent refugee/30 percent host community members/60 percent femaleheaded)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "90m x 90m pixel. The map shows a high concentration of flood-exposed populations in Hanoi, as well as urbanized areas along the Red River. The granularity offered by these pre-processed population exposure maps could be valuable for various applications; e.g. for the development of disaster mitigation plans prior to a flood event, or to estimate the number of affected people during flood events in order to prepare the scale-up of shock-responsive social protection systems. However, several limitations of these maps should be noted: First, poverty estimates are not available with the same resolution and are not incorporated in these maps. Second, while the maps can help to identify the scale of overall vulnerability and the location of pockets of vulnerability, they cannot replace detailed needs assessments for the targeting of post-disaster support or the evaluation of damages after specific events. 2 These maps will be made available publicly, and will be available upon request in the meanwhile. 23", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "0.183 0.076 0.107 0.104 Mean of dep var. 0.328 0.111 0.137 0.214 0.209 0.928 0.841 _Note:_ Robust standard errors clustered at the DHS cluster level in parentheses. All regressions control for year and district fixed effects, urban dummy, age, and years of education. Active is active status of mine in the survey year. *** p<0.01, **p<0.05, *p<0.1. Results for women’s partners also available upon request. OLS = ordinary least squares. The women and men samples have different sampling frames and therefore we are not analyzing these results jointly. Two further caveats should be noted: (i) with many variables tested, such evidence should not be given too much weight, (ii) number of sampled men in the treatment category is quite small. Out of 7,157 sampled med, only 484 men live close to active mines. A bigger treated sample would provide more reliable results. [10] **5.2 Child health** We explore effects on child health, such as size at birth, infant mortality, anthropometrics, and incidence of cough, diarrhea, and fever. Panel A and Panel B use different variable definitions 10 Results for sampled women’s partners are similar. 18", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "to establish or expand their operations. This will include improving the scale and quality of community tree nurseries, and the establishment of tree plantations with market orientation, based on locally appropriate and climate-resilient species with commercial demand and also adapted to future climate conditions. The use of indigenous tree species will be promoted where technically viable. Inter-cropping within plantations during the early years of growth will provide co-benefits to group members from food and cash crops. Groups will also be supported to establish wood fuel plantations in public institutions with kitchens (e.g., schools and health facilities) to provide a sustainable supply of fuel for mass catering. LIPW under this sub-component will be limited to these institutional woodlots, as the nursery and plantations are productive assets from which participants will draw Page 10", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the marketing restricted sample, which is restricted only to villages where at least one person purchased insurance in the following year. The average ratio of payout to premium (for those who received payouts) for the full sample is 3.6; for those in the marketing restricted sample it is 4.5. All regressions contain state fixed effects. Errors are clustered at the weather station level. ***p _<_ 0.01, **p _<_ 0.05, *p _<_ 0.1. _Source_ : Authors’ analysis based on data from BASIX. a payout flips to negative and significant. However, the payout ratio is positive and significant while the payout ratio squared is negative and significant. Together, this suggests that people who receive very small payouts are less likely to purchase insurance, while those who have large payouts are more likely to purchase. The overall effect of receiving a payout switches from negative to positive when the payout ratio reaches around .77. One point of concern with these results is that there are many cases where there are multiple purchasers of insurance in a certain village in one year and then zero in the next year. Although this could be the result of people simply being unsatisfied with insurance, the large", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "data from BASIX"}], "vague_data": []}}}
{"input": "wetlands are associated with an island or mainland coast), as described in Hoozemans and Hulsbergen (1995). [15] Five possible responses to SLR corresponding to categories of wetland migratory potential were defined for the DIVA database: 1. No, or hardly any change; 2. A retreat of the coastline, combined with inland migration of coastal ecosystems; 3. A retreat of the coastline without the possibility of inland migration due to topography (e.g., coastlines with relatively high relief); 4. A possible retreat of the coastline but increase of flooding area behind the coastline (“ponding”); and 5. Total loss of the coastal ecosystem (Hoozmans et al. 1993). ###### **II.2 Methodology** The procedure used in this analysis followed several steps. First, the SRTM database was used to identify inundation zones. [16] Second, a country surface for wetlands was constructed from the polygons extracted from the Global Lakes and Wetlands database. Third, migratory potential of wetlands were assigned from the WMP classification of the coastline from the DIVA database. Fourth, the country surface of wetlands was overlaid with the inundation zone layer. The analysis then determined the area of wetlands that would be exposed to increased SLR and the area of wetlands that may be lost", "output": {"entities": {"named_data": [{"text": "DIVA database"}, {"text": "SRTM database"}, {"text": "Global Lakes and Wetlands database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Development to Foster Private Sector and Growth_ _in Rwanda._ 14 A transit district hosts asylum-seekers in the immediate period after they have come across the border. They stay in Transit Centers while their refugee claims are assessed and while the government identifies a long-term site for their resettlement. Rubavu has experienced major inflows from the DRC in recent times, with many asylum seekers staying for months. The district is being included in the project for an Integrated Craft & Production Center (ICPC) so that asylum seekers can work and seek training opportunities immediately upon arrival. This is expected to expedite the process of socio-economic inclusion. The ICPC will also be used by host community members in the district. 15 The two roads are an exception. They have been pre-identified by the government. For other subprojects, the GoR has prepared an indicative list, which will be validated through additional consultations with refugees, host communities and other stakeholders. The list includes: (a) classroom construction for a school and TVET center in Gisagara; (b) health facilities in Gatsibo and Nyamagabe; (c) water systems in Kirehe and Nyamagabe; (d) markets in Kirehe and Karongi; and (e) ICPCs in Kirehe and Rubavu. 16 The only", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "women as of 29 September 2024 [1] and children [2] ## 98% 34% of Protection Monitoring respondents are Temporary Protection holders ## 34% of Protection Monitoring respondents are of respondents consider accommodation as Temporary Protection holders their highest priority need ## 67% 29% ## 29% of working age respondents are employed in Czechia 1 Ministry of the Interior, Czechia 2 Ministry of the Interior, Czechia of respondents need more information about job opportunities", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "language skills leads to the inability to upscale professional skills and to seek meaningful employment opportunities matching qualifications. When seeking employment through agencies, women reported cases of labour exploitation with jobs that often involve long working hours, no breaks, no social protection coverage, and no annual leave. From protection monitoring, 24% of respondents reported working excessively long hours. 12% indicated they did not have an employment contract, while 3% reported the confiscation of their documentation (e.g., passport) by their employer. ### Protection Risk IV **Access to adequate healthcare:** In focus group discussions conducted by UNHCR with elderly Ukrainian refugees [3], access to adequate healthcare emerged as the main concern. Participants highlighted significant barriers, including difficulties finding a general practitioner and understanding a medical insurance system that is new to them. Refugees highlighted a particular challenge in doctors neglecting to consider medical histories from Ukraine, resulting in misdiagnoses and incorrect treatment. Some instances, such as when prescribed medications conflicted with known conditions, illustrated a disconnect between patient backgrounds and treatment approaches in the Czech healthcare system. This forced some refugees to rely on bringing medications from Ukraine, exacerbated by difficulties obtaining longterm prescriptions. Language barriers also hinder effective communication of health", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**1.** **Introduction** Natural disasters are estimated to cause an average of over $300 billion in direct asset losses every year; this estimate increases to $520 billion when considering the well-being (or consumption) losses experienced by people (Hallegatte et al. 2017). While each country faces its individual set of natural hazards – including cyclones, earthquakes, or wildfires – floods are one of the most common and severe hazards to disrupt people’s livelihoods around the world. Especially in lower income countries where infrastructure systems – including drainage and flood protection – tend to be less developed, floods often cause unmitigated damage and suffering. Recent events, ranging from Bangladesh and Nigeria to the United States and Vietnam, illustrate that the threat is a global reality. Not only rare and major floods, but also smaller and frequent events can revert years of progress in poverty reduction and development. In the coming years, land subsidence, rapid coastal urbanization, and climate change are bound to result in increasing exposure of people and their livelihoods. In this study we estimate the number of people who are directly exposed to the risk of intense flooding in 189 countries. We do so by using high-resolution flood and population data", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "high-resolution flood and population data"}], "vague_data": [{"text": "high-resolution flood and population data"}]}}}
{"input": "and gold production was booming. The first gold rush occurred between 1892 and 1901, and the second after World War I. Gold production decreased at the dawn of independence in 1957, and remained low until the 1980s. Over the last 20 years, Ghana has been experiencing its third gold rush. During this period, annual gold production has increased by 700 percent, as shown in Figure 1. It is the expansion that has happened during this recent gold rush that is used in this analysis to understand the socioeconomic effects of mining. The high international gold price was a driving factor in the expansion of small-scale mining, such as the 2,700% increase in gold mining territory around the Offin River between 2008 and 2012 (Hausermann et al., 2018). Between 2006 and 2012, two large-scale mines opened in Ghana, but no mine closed down (Table 1) possibly due to the high gold price increasing profitability and extending life length. The expansion across artisanal small-, medium-, and large-scale mining contributed to an increase in total production that rose from 541,147 oz in 1990 to 3,119,823 oz in 2009 according official Ghana statistics (Bloch and Owusu, 2012). This production increase led to an increased", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "official Ghana statistics"}]}}}
{"input": "occupants and measures taken by the recently passed Land Act to restore such security, based on recognition of the importance of land-related investment and higher agricultural productivity for pro-poor growth that will help narrow the gaps between rural and urban well-being in Uganda. We use this to outline the estimation strategy to be utilized and discuss some of the associated econometric issues. **2.1 Origins and incidence of overlapping tenure in Uganda** The main reason for the prevalence of overlapping property in Uganda’s land tenure system dates back to colonial occupation. Under the 1900 Buganda agreement, [1] the British awarded large tracts of “ _mailo_ ” land, together with any smallholders occupying them, to the Buganda king and his notables (Brett 1973). Lands not covered under this agreement were declared Crown Land, allowing the government to alienate 1 In this agreement, the total area of Uganda, estimated at 19,600 square miles, was divided into three broad classes. The first class, comprising 958 square miles, was given to the Buganda king (kabaka), the second one, amounting to a total of 8,000 square miles, was distributed equally among 1,000 chiefs and private land owners. The remainder was declared Crown Land and vested in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "relevant expertise. Accessed at [http://www.compassonline.org/pdf_files/EBM_Consensus_Statement_v12.pdf](http://www.compassonline.org/pdf_files/EBM_Consensus_Statement_v12.pdf) Millennium Ecosystem Assessment. 2005. _Ecosystems and Human Well-Being: Wetlands and_ _Waters Synthesis_ . World Resources Institute, Washington, DC. Nicholls, R.J., Hoozemans, F.J.M. and M. Marchand. 1999. Increasing flood risk and wetland losses due to global sea-level rise: Regional and global analyses”. _Global Environmental_ _Change_, 9. S69-S87. Nicholls, R.J. 2004. Coastal flooding and wetland Loss in the 21 [st] century: Changes under the SRES climate and socio-economic scenarios. _Global Environmental Change_, 14, 69-86. Nicholls, R.J., Hanson, S., Herweijer, C., Patmore, N., Hallegatte, S., Corfee-Morlot, J., Chateau, J., and R. Muir-Wood. 2007. _Ranking Port Cities with High Exposure and Vulnerability to_ _Climate Extremes_ . OECD Environment Directorate, Environment Working Papers No. 1. Nicholls, R. J., and A. Cazenave. 2010. Sea-level rise and its impact on coastal zones. _Science,_ 328, 1517-20. Overpeck J., Otto-Bliesner B., Miller G., Muhs D., Alley R. and J. Kiehl. 2006. Paleoclimatic evidence for future ice-sheet instability and rapid sea-level rise. _Science_, 311,1747-1750. Pfeffer, W. T., Harper, J.T., and S. O’Neel. 2008: Kinematic constraints on glacier contributions to 21st-century sea-level rise. _Science_, 321, 1340-1343. Rahmsdorf, S. 2007. A semi-empirical approach to projecting future sea-level rise. _Science_, 308, 368-370. Semeniuk, V. 1994. Predicting the effect", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**3.1.** **Flooding hazard data** Floods can be caused by a variety of factors. The most common types are considered in this analysis: **Fluvial flooding** occurs when intense precipitation or snow melt causes rivers to overflow. **Pluvial flooding** occurs when rainwater builds up beyond the absorptive capacity of soil. Country-level pluvial and fluvial flood maps, developed by Fathom Ltd, are used in this analysis (Smith et al. 2015). The data sets provide information on flood extents and flood depth at an approximate spatial resolution of 90 meters and are available for all countries. The maps are based on a global hydrological and topographic model. The model simulates flood events with return periods of 5, 20, 50, 100, 250, and 500 years. This study considers flooding with a 100-year return period. A 1-in-100-year event, for example, is expected to occur once every 100 years on average (i.e. it has a probability of 1% of occurring in any given year). As with all global flood maps, the effects of artificial flood protection structures like dikes are not incorporated. Two editions of the Fathom global flood maps are available; 2016 and 2019. Wherever available, the newer version has been used. The 2019 version differs", "output": {"entities": {"named_data": [{"text": "Fathom global flood maps"}], "descriptive_data": [{"text": "Country-level pluvial and fluvial flood maps"}, {"text": "Flooding hazard data"}], "vague_data": []}}}
{"input": "financial and social sustainability by means of internal mobility, selfreliance, and inclusion in national services. The design of DRDIP II fully aligns with these lessons through its focus on selfreliance and integration of refugees into national service delivery systems. 54. **Multi-sectoral development investments directed to forcibly displaced populations and host communities can** **improve welfare, mitigate the negative effects of displacement, generate positive externalities, and promote social** **cohesion.** The 2022 World Bank report, _Social Cohesion and Forced Displacement,_ concludes that to pre-empt social tensions that can emerge in situations of forced displacement, governments and humanitarian and development agencies need to direct short- and long-term assistance to both the displaced and host communities. This can help reduce real and perceived inequalities and prevent host communities from forming negative attitudes about newly arriving displaced persons. DRDIP II will continue the area-based approach of Phase I, providing multi-sectoral support to respond to the impacts of forced displacement, covering refugees and host communities. **III.** **PROJECT IMPLEMENTATION** **A.** **Institutional and Implementation Arrangements** 55. **The project will retain the same arrangements as Phase I**, but with enhanced coordination and collaboration mechanisms under OPM’s DoR. OPM will implement DRDIP II at the national level through a PIST, which", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "models. By modeling changes in river discharge and inundation areas, they show that a high-concentration climate change scenario could lead to a large increase in flood frequencies in Southeast Asia, India, East and Central Africa, and large parts of Latin America. Yet, existing models are ill-suited to provide reliable long-term projections of climate change at the local level. The IPCC’s Fifth Assessment report shows that forecasts for average temperature and rainfall changes by mid-century vary significantly depending on which model and which assumptions are considered. However, it is not only the change in the mean that matters – already regions around the world are experiencing changes in the variability of climatic events; in the form of increased frequency of formally rare and extreme events, such as droughts and intense floods. In the meanwhile, the continued urbanization of high-risk areas will mean that more and more people will be exposed to flood risks. Indeed, large coastal cities are likely to be risk hotspots. Hallegatte et al. (2013) estimate the flood risks in the world’s 136 largest coastal cities. They show that population and asset growth, climate change and subsidence are all likely to contribute to a drastic increase in global average", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "and effectiveness of resource utilization, minimize duplicative efforts, support address unmet needs effectively, and foster programmatic coherence. Operating as an intersectoral platform, the CBI TWG, accountable to the 3RP coordination in Türkiye, focuses on managing both sector-specific and multipurpose cash assistance. This coordinated approach is designed to meet the basic and specific needs of vulnerable populations, ensuring that the assistance provided through CVA is both targeted and impactful. This approach has become increasingly relevant and critical, especially considering the challenging circumstances following the 2023 earthquake, which necessitated a broader and more targeted coordination of resources and assistance. 1 Republic of Türkiye, Ministry of Interior, Presidency of Migration Management, Statistics (24/04/2025), _Temporary Protection_, [https://en.goc.gov.tr/temporary-protection27](https://en.goc.gov.tr/temporary-protection27) 2 Republic of Türkiye, Ministry of Interior, Presidency of Migration Management, Press Release (20/08/2024) https://www.goc.gov.tr/ulkemizdeki-yabanci-sayilarina-iliskin-ortaya-atilan-gercek-disi-iddialar-hakkinda-basin-aciklamasi 1", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "were assigned from the WMP classification of the coastline from the DIVA database. Fourth, the country surface of wetlands was overlaid with the inundation zone layer. The analysis then determined the area of wetlands that would be exposed to increased SLR and the area of wetlands that may be lost due to SLR. More specifically: 15 We acknowledge that the migratory potential of wetlands also depends on a wide range of additional factors that are site-specific and highly variable such as the continued flow of sediment and nutrients from inland stream as well as human activities. Such detailed information was not available on a global scale. 16 It should be noted that the SRTM database suffers from known limitation in urban as well as forested areas where the SRTM elevation data may capture the height of building or trees instead of ground level elevation. A similar limitation is noted by Nicholls et al. (2007). 8", "output": {"entities": {"named_data": [{"text": "DIVA database"}, {"text": "SRTM database"}, {"text": "SRTM elevation data"}], "descriptive_data": [{"text": "SRTM elevation data"}], "vague_data": []}}}
{"input": "been conducted according to IPF policy and directives to verify that** **the current systems provide reasonable assurance of resource allocation for their designated purpose.** The assessment focuses on the capacities of the implementing agencies, leveraging insights from previous projects. Detailed arrangements for budgeting, accounting, staffing, internal controls, fund flow, reporting, and auditing have been outlined during project preparation, with measures to mitigate fiduciary risks. **B. Results Monitoring, Evaluation, and Verification Arrangements** 61. **The project’s monitoring and evaluation (M&E) arrangements reflect the capacity constraints and operational** **challenges faced by a project with two implementing agencies, which lack an integrated management information** **system, including the M&E.** The project will be implemented with necessary oversight at the local level, where M&E capacities will be mobilized for the collection, organization and analysis of project-related data. The main instrument for M&E will be the Results Framework (Annex 1). The indicators at PDO and intermediate levels, as well as their respective baselines, midterm, and end-of-project targets, will serve as the basis for reporting progress. The indicators, data sources, and data collection methods take into account the limited institutional capacities in the project target locations. All relevant indicators are disaggregated by gender, and where applicable by refugees", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Socio-economic Inclusion of Refugees & Host Communities in Rwanda Project Phase II (P509677) **D. Project Components** 16. **Jya Mbere Phase II investments will support priority domains from the self-reliance index – education,** **health, labor and income – and implementation of the government’s graduation strategies for Rwandan** **nationals and refugees.** The strategic evolution to focus on self-reliance will drive design changes for Phase II compared to Phase I, including: (a) more funding will go to climate-resilient economic infrastructure and livelihood, including to address job skills gaps, which is a priority for the country as a whole and for refugees; [13] and (b) new economic opportunity activities will be added for vulnerable groups and people who cannot access finance from formal financial institutions. Project activities will be organized in five components, as described below. **Component 1: Access to Services and Socio-economic Investments (US$41.1 million equivalent, of which US$13.3** **million equivalent from the WHR)** 17. **Phase II will continue to support much-needed infrastructure in the five refugee-hosting districts, plus one** **transit district, Rubavu.** [14] As per Phase I, priority investments will be identified through the government’s District Development Strategy (DDS) process, which draws on consultations from the village, cell, sector", "output": {"entities": {"named_data": [{"text": "self-reliance index"}], "descriptive_data": [], "vague_data": []}}}
{"input": "climate change. Nevertheless, the findings presented in this paper should be interpreted considering a number of caveats. While we use current and future flood data, we only use current population and poverty data, as reliably projecting these socioeconomic trends spatially into the future is almost impossible. Changes in these trends – among many other factors – can lower socioeconomic 7 Disaggregated results per district, and results using depth as an indicator can be found in the online supplementary materials.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "current and future flood data"}]}}}
{"input": "**The World Bank** Integrated Community Resilience Project (P506969) PROJECT APPRAISAL DOCUMENT and seasonal rivers (wadi) are vital for supporting oases and recharging shallow aquifers. Projections indicate climate will intensify extreme heat, with the number of high heat index days nearly doubling from 66 to 123. This will severely affect livelihoods, particularly in rural areas where livestock rearing—a key source of income for 60 percent of the rural population—is projected to reduce revenues by up to 24 percent. Livestock also represents a form of savings and insurance for nearly one-third of poor households (30 percent), compared to just 11 percent among non-poor households [17] . Moreover, climate change will impact human productivity, with labor output expected to decrease by as much as 3.5 percent by mid-century due to heat stress. The poor, who rely heavily on natural resources, are the most vulnerable to these impacts. Additionally, climate-induced diseases such as malaria have increased significantly, with a 37-fold rise over the past two decades. Combined with heat-related health issues, this is expected to further reduce the labor supply by up to 1.5 percent. 17. **The project is fully aligned with the World Bank’s Country Partnership Framework (CPF) for Djibouti (2022-** **2026), which", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "with effective stakeholder engagement, procurement, and contract management capabilities. **C. Project Beneficiaries** 38. There are two cohorts of primary beneficiaries under the project: (a) refugees and former refugees who will benefit from a more inclusive national policy regime and (b) refugee and host community members in and around the Meheba settlement and Kalumbila District, who will benefit from better infrastructure, services, and support to agribusiness. The total number of direct beneficiaries under the project is estimated to be 172,837. [38] 39. **Refugees and former refugees nationally.** There are currently 101,837 [39] refugees and former refugees in Zambia who will be direct beneficiaries under Component 1. Legislative and policy changes stemming from Zambia’s National Refugee Policy which will be implemented nationally will have a positively impact on their lives. This cohort will also benefit from the issuance of national ID cards which for the first time will place them on the Zambia national registry. 40. **Refugees and host communities in Kalumbila District.** They will benefit from infrastructure, health, and education services and support to farming activities and agribusiness. The estimated number of specific beneficiaries per project component together with total direct beneficiaries is detailed in Table 1. **Table 1. Project Beneficiaries", "output": {"entities": {"named_data": [{"text": "Zambia national registry"}], "descriptive_data": [], "vague_data": []}}}
{"input": "these interventions. **Sub-component 1.2.: Financial Inclusion Services (total IDA US$1 Million, including WHR US$0.3 Million)** 35. **This sub- component will support FIS activities for 1,500 beneficiaries who are members of households receiving C4N** **(including an estimated 500 refugees)** . This initiative aims to enhance financial inclusion and promote economic resilience by providing a one-off US$500 financial inclusion grant and technical support services for the poor and vulnerable households so they can try out household self-help activities. Eligible beneficiaries must meet key criteria, including (i) being part of a household benefiting from cash transfers, (ii) willingness to engage in small household self-help activities focused on improving their wellbeing, (iii) completing training on household self-help activities to be provided by a service provider that will be selected by the MASS, and (iv) presenting a concise action plan outlining their proposed self-help activity. Among refugee beneficiaries, it is expected that some households may opt for in-kind support from other development partners – and where this will be the case, their election into the FIS will not be constrained by not being participants into the C4N. 36. This subcomponent will also seek to achieve greater financial inclusion for women by promoting more women representation", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "of coverage turned out to be a multiple of the fair price (around three times in either case). [5] Why is insurance so costly? Several reasons are invoked, including supply-side constraints induced by either agency costs or adverse selection, problems of information opacity of tail events, coordination failures, [6] and oligopolistic practices. While the securitization [7] of catastrophic risk through the issuance of catastrophe bonds may in the future induce greater market discipline, until now it has fallen short of reducing the costs of insurance to actuarially fair levels. [8] If insurance is so expensive, why do countries still buy it? One reason could be risk aversion; another could be the presence of concavities in the production function and/or convexities in the borrowing cost function that create hedging opportunities as in Froot et al. (1993). While both these assumptions may play an important role for the demand of insurance, nonetheless we think that they only partially justify why a 1 By exposure we denote the probability of being hit by a natural disaster and by vulnerabilty the expected loss associated with any of such disasters. 2 See Elrich and Becker (1972). 3 See Hofman and Brukoff (2006) for a survey", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "affects civilians more than the military, especially in the 2nd quarter of 2023 **(Ref graph3).** In fact, the reported ED incidents resulted in a total of 132 victims [4] and survivors, most of whom (52%) were civilians (killed or injured). **The percentage** **of civilians killed is almost double that of military** **killed,** which puts the threat on civilians more than militaries and reflects the need to strengthen mine action within affected communities. The affected regions are those of Tillabery (areas of the 3 borders in the Sahel) and Diffa (region of the Lake Chad basin). **The Tillabery region has 7 affected** departments [5] **, and the Diffa region has 4** . A minimal number of ED incidents have also been reported in 3 other regions: Agadez, Dosso and Niamey ( **Ref graph2** ). This situation puts more than 200,000 people at risk of ED incidents in the affected areas. The prevalence of ED incidents related also leads to restrictions on the mobility of civilian populations on the roads to weekly markets, and the main cities of communities/departments. About 36% of those interviewed [6] say they encounter mobility constraints due to the activities of the NSAGs and military operations. This indicator", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "698 Stein the results could be biased. For instance, assume that there were a number of villages that experienced a rainfall shock but received very low payouts, making them unhappy with insurance. If the marketing teams knew this, they may have decided to not market to as many of these villages, therefore censoring villages that received a payout but were likely to have few repeat buyers. Regressions that use previous years’ payout characteristics to try to predict whether insurance is sold in a village the following year do not reveal any patterns that would suggest selection bias (shown in table S.5 in the supplemental [appendix, available at https://academic.oup.com/wber), but they may miss more subtle selection patterns.](https://academic.oup.com/wber) It is possible that the coefficient for the marketing restricted sample is upward biased and it therefore would be reasonable to regard the coefficients in columns 1 and 3 as lower and upper bounds, respectively. The payout ratio has a positive and strongly significant effect while the squared term is smaller and negative. This suggests that higher insurance payouts result in greater propensity to purchase the following year, but that the marginal effects flatten out for larger payouts. Also, the simple dummy of receiving", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the scenarios presented in Table 2, and aggregate our results at the district level to estimate the number of people affected. To include the poverty dimension, we use the poverty headcount rate in each district to estimate the percentage of poor people exposed. For instance, if 20,000 people are exposed to floods in District X, and District X has a poverty headcount rate of 20%, 1000 poor people are exposed to floods in that district. [5] Slum Exposure in Ho Chi Minh City For the HCMC analysis, we estimate the general exposure to flooding, for the whole province of HCMC and in each of its 24 districts. The flood maps used here are based on a model of HCMC, and are not the same map as used in the figurative example in Section 4.1. 5 As evidenced in the HCMC analysis with slum data, poor people are often not evenly distributed but clustered in particular areas. However, due to data limitations across the country, we assume poverty is evenly distributed within a district when conducting the national-level analysis.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "slum data"}, {"text": "poverty headcount rate"}]}}}
{"input": "order to look at the results of weather separately from the effects of insurance, I analyze how previous weather events affected insurance purchase decisions in the first year that insurance was offered to BASIX customers, which was 2005. To accomplish this, I first aggregate the purchasing data to the village level and then test to see whether villages that experienced a rainfall shock in 2004 had more insurance purchasers in 2005 than", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "purchasing data"}]}}}
{"input": "Policy Research Working Paper 4310 #### **Abstract** The need for land-related investment to ensure sustainable land management and increase productivity of land use is widely recognized. However, there is little rigorous evidence on the effects of property rights for increasing agricultural productivity and contributing toward poverty reduction in Africa. Whether and by how much overlapping property rights reduce investment incentives, and the scope for policies to counter such disincentives, are thus important policy issues. Using information on parcels under ownership and usufruct by the same household from a nationally representative survey in Uganda, the authors find significant disincentives associated with overlapping property rights on short and long-term investments. The paper combines this result with information on crop productivity to obtain a rough estimate of the magnitudes involved. The authors make suggestions on ways to eliminate such inefficiencies. This paper—a product of the Sustainable Rural and Urban Development Team, Development Research Group—is part of a larger effort in the group to assess the impact of land policies. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at kdeininger@worldbank.org. _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "nationally representative survey in Uganda"}], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) Procurement Prior Review Thresholds detailed in Annex I of the Bank’s Procurement Procedure are to be observed. The Project will use the Systematic Tracking of Exchanges in Procurement (STEP) to plan, record, clear and track procurement transactions for the Project. An initial Procurement Plan has been prepared by the MEP in accordance with the results provided by the PPSD, including a timeline for implementation. **C. Legal Operational Policies** **D. Environmental and Social** 53. The Project will finance consulting services to design, develop and implement educational tools, information systems, platforms and other software, as well as to develop assessments, policies, plans and strategies for the educational sector. The Project will also finance the equipping of selected schools with internet connections and hardware (e.g., notebooks, tablets, smart boards, projectors, headphones, robotics, computational kits). The Project will not finance any type of civil works. The environmental and social risk rating is classified as Moderate. The Project is expected to have mostly positive social impacts through improved education quality, inclusion, and resilience. Impacts on vulnerable and systematically excluded groups are expected to be positive with limited negative social effects. **V.** **GRIEVANCE REDRESS SERVICES** 54.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Economics of Disasters and Climate Change Fig. 4 Location of slum areas and locations with urban expansion in the city of HCMC. Source: (PUMA 2013) We then overlay this flood layer with the population density data set, to estimate the number of people per population grid cell that are exposed to floods. As the population density data set is at a lower resolution (1 km) than the flood data (90 m), we estimate the percentage of the population grid cell which is flooded, and multiply this percentage by the population in that grid cell. For instance, if a population grid cell has 500 people, and 10% of that cell is flooded (based on the flood data), then we estimate 50 people to be exposed to floods in that cell. In doing so, we assume that the population is evenly distributed within a grid cell. We run this analysis for all the scenarios presented in Table 2, and aggregate our results at the district level to estimate the number of people affected. To include the poverty dimension, we use the poverty headcount rate in each district to estimate the percentage of poor people exposed. For instance, if 20,000 people are exposed", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "population density data set"}], "vague_data": [{"text": "poverty headcount rate"}, {"text": "flood data"}, {"text": "population density data set"}]}}}
{"input": "large-scale gold mines in Ghana. We find that a new large-scale gold mine changes economic outcomes, such as access to employment and cash earnings. In addition, it raises local wages and expenditure on housing and energy. An important welfare indicator in developing countries is infant mortality, and we note a large and significant decrease in mortality rates among young children, at both the local and district levels. [1] We hypothesize that increased access to prenatal care is one of the mechanisms behind the increased survival rate. 1 In the 2010 Ghana population census average district size is 112,000 3", "output": {"entities": {"named_data": [{"text": "2010 Ghana population census"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Economics of Disasters and Climate Change Fig. 2 Flood maps showing inundation depth (cm) in case of a: (a) 10-year return period flood under current conditions, (b) 25-year return period flood under current conditions; (c) 50-year return period flood under current conditions; (d) 10-year return period flood given a 30 cm sea level rise; (e) 25-year return period flood given a 30 cm sea level rise; and (f) 50-year return period flood given a 30 cm sea level rise Local-Level Data on Urban Areas and Potential Slums in Ho Chi Minh City The spatial socioeconomic data set used for HCMC is a data set of potential slum areas from 2000 to 2010, from the Platform for Urban Management and Analysis (PUMA), a city-level data set developed by the World Bank (World Bank 2015).This data was collected via satellite in the year 2012, through a combination of visual interpretation of various sources and vintages of imagery. To guide the identification of slums, previous work has provided information on the appearance and geographical extent of slums in HCMC. Surveys of poverty in the city find the appearance of slums in HCMC to be characterized as densely built small households and shelters that", "output": {"entities": {"named_data": [{"text": "Platform for Urban Management and Analysis"}], "descriptive_data": [{"text": "spatial socioeconomic data set used for HCMC"}, {"text": "Surveys of poverty in the city"}], "vague_data": [{"text": "Surveys of poverty in the city"}]}}}
{"input": "_Note:_ In panel A, active is status of mine in birth year; in panel B, active is active status of mine in survey year. Robust standard errors clustered at the DHS cluster level in parentheses. All regressions control for year and district fixed effects, urban dummy, age, and years of education. *** p<0.01, **p<0.05, *p<0.1. OLS = ordinary least squares. An active mine is associated with a decrease in cough among children under age five (panel B of table 5), and children are also (insignificantly) more likely to have a health card. An active mine is associated with insignificant decreases in the anthropometrics measures (World Health Organization measures in standard deviations), such as height-for-age and weight-for-age. However, the standard errors for these coefficients are very large relative to the estimated coefficients, which is why the effects are imprecisely estimated. **5.3 Spatial heterogeneity of results** Thus far we have used a cutoff distance of 20 km. Panel A of figure 4 shows that the largest treatment effect for services for women is found within 10 km of a mine, with an 8 percentage point increase in the probability that a woman works in the service sector. This is equivalent to a", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "reduce the time lag it takes to deliver support given the evolution over the last five years. The duration of C4N will be 24 months (2 years) whereas SBCC will be phased throughout the implementation of the project. 32. A total of 2,860 refugees - including student refugees in Djibouti-Ville will benefit from the C4N. This support, which proved critical for children from rural vulnerable households during covid-19, will help refugee children remain in school longer and improve their educational outcomes, addressing barriers such as school fees and additional basic costs. 33. **The C4N will cover all six regions with beneficiary coverage in each region determined based on a** **predetermined set of targeting criteria.** In accordance with the principle of convergence which the project promotes, efforts will be made to achieve overlap of C4N and SBCC interventions with component 2 interventions in Dikhil by maximizing beneficiary coverage in the region. A combination of geographical targeting, categorical targeting, ProxyMeans Targeting (PMT) and community-based targeting (CBT) mechanisms will be used in a complementary way to identify beneficiaries and minimize exclusion and inclusion errors that may arise from inadequate coverage of the social registry and biases that result from community beneficiary identification. The", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "social registry"}]}}}
{"input": "high impact intensity and others have none. The first and second moments of the spatial impact distribution also change over time: The median landfall location shifts eastward from northern Odisha to the Bangladesh/West Bengal border area, while locational variance increases markedly after 1960. We also consider the overall distribution of impacts during the 140-year period covered by our database. Despite pronounced period-to-period shifts in impact locations, the overall distribution is far from uniform. We find the highest impact zones in northern Odisha and the Sundarbans region of West Bengal, with somewhat lower impacts in the zone between those two areas and a pattern of decline from the high-impact zones to the southern coastline boundaries of Odisha and Bangladesh. We should note that these boundary results are not artifacts of our methodology: We have also incorporated cyclone strikes in proximate areas south of the end points. Finally, despite the pronounced bimodality of the spatial distribution, we also find significant variation within zones. For example (Figure 8c), western coastal Bangladesh, generally a mid-impact zone, also has significant stretches of coast that have very low historical impacts. To summarize, our focal coastline area has witnessed highly-varied long- and short-term distributions of cyclonic storm", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Several important questions can be addressed with these data. The first relates to locational stability: What are the permanent and transient components of household and community responses to long- and short-run cyclone clustering, and to the power of recent cyclones? Outright relocation will be part of the response, but so will relocation of prime-age household members to less-impacted inland areas where their earnings and residence will offer financial insurance and a potential safe harbor from future cyclones. The size and speed of the response will depend critically on expectations about future cyclone strikes, which can be inferred from the highly varied data in our cyclone panel. Other questions of interest can also be explored once cyclone-related controls are introduced. For example, how much coastal outmigration reflects the “pull” of urban opportunities, and how much reflects the “push” of cyclone-related hazards? How do disaster mitigation policies affect responses to these hazards? Some coastal zones in our study area invest significant resources in damage prevention via polder construction and other measures, while others offer compensation once cyclone-related damage has occurred. Incorporation of controls from our cyclone panel database may permit more accurate estimation of the timing and magnitude of responses to these", "output": {"entities": {"named_data": [{"text": "cyclone panel"}], "descriptive_data": [], "vague_data": []}}}
{"input": "since FY 1998, and all AAA since FY 2000. Using the appropriate thematic codes, we calculate total Bank lending and AAA by country and environmental theme. Our five environmental indicators and the institutional problem indicator are constructed to match the corresponding thematic categories in the project database. The seventh thematic 9", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "project database"}]}}}
{"input": "works. The environmental and social risk rating is classified as Moderate. The Project is expected to have mostly positive social impacts through improved education quality, inclusion, and resilience. Impacts on vulnerable and systematically excluded groups are expected to be positive with limited negative social effects. **V.** **GRIEVANCE REDRESS SERVICES** 54. _**Grievance Redress**_ . Communities and individuals who believe that they are adversely affected by a project supported by the World Bank may submit complaints to existing project-level grievance mechanisms or the Bank’s Grievance Redress Service (GRS). The GRS ensures that complaints received are promptly reviewed in order to address project-related concerns. Project affected communities and individuals may submit their complaint to the Bank’s independent Accountability Mechanism (AM). The AM houses the Inspection Panel, which determines whether harm occurred, or could occur, as a result of Bank non-compliance with its policies and procedures, and the Dispute Resolution Service, which provides communities and borrowers with the opportunity to address complaints through dispute resolution. Complaints may be submitted to the AM at any time after concerns have been brought directly to the attention of Bank Management and after Management has been given an opportunity to respond. For information on how to submit [complaints", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "a reliable, accurate, and timely manner; and (c) project assets will be appropriately safeguarded. 75. **Based on the assessment conducted, the FM risk is rated moderate.** Project arrangements will rely on the existing public FM system at the IAs and the districts, which is adequate. The IAs have experience managing World Bank-financed operations and have mostly complied with key FM deliverables. However, the following potential risks are identified that relate to all the IAs, unless otherwise specified: (a) the Rwanda Feeder Roads Development Project (P126498), implemented by RTDA and Phase I of Jya Mbere under MINEMA have experienced challenges, including low budget execution, and qualified audit opinions on the achievement of value for money; (b) inadequate preparation of the AWPB, which could lead to errors in financial reporting and potential misallocation of expenditure; (c) delayed and/or poor-quality financial reporting; (d) staff capacity constraints; (e) poor planning, budgeting and budget monitoring systems; (f) possible ineligible expenditure due to potential BRD non-compliance with the MG manual guidelines; (g) inadequate and delayed implementation of internal and external audit recommendations; and (h) lack of automated accounting system at BRD. 76. **FM risk mitigating measures include** : (a) MINEMA will update the FM guidelines in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "we use a cutoff distance of 20 km, we assume there is little economic footprint beyond that distance. Of course, any such distance is arbitrarily chosen, which is why we try different specifications to explore the spatial heterogeneity by varying this distance (using 10 km, 20 km, through 50 km) as well as a spatial lag structure (using 0 to 10 km, 10 to 20 km, through 40 to 50 km distance bins). [4] Second, we collapse the DHS mining data at the district level. [5] The number of districts has changed over time in Ghana, because districts with high population growth have been split into smaller districts. To avoid endogeneity concerns, we use the baseline number of districts that existed at the start of our analysis period, which are 137. Eleven of these districts have industrial mining. Because some mines are close to district boundaries, we additionally test whether there is an effect in neighboring districts. **3.1 Resource data** The Raw Materials Data are from InterraRMG (2013). The data set contains information on past or current industrial mines. All mines have information on annual production volumes, ownership structure, and GPS coordinates on location. We complete this data with exact", "output": {"entities": {"named_data": [{"text": "Raw Materials Data"}], "descriptive_data": [{"text": "DHS mining data"}], "vague_data": []}}}
{"input": "project as a whole. MINEMA conducted public and stakeholder consultations across the project target areas to gather feedback on the proposed activities, address concerns, and explore ideas to mitigate potential adverse impacts on socio-economic activities and livelihoods. The project’s stakeholder engagement plan, built on inclusive consultations, incorporates a comprehensive grievance redress mechanism (GRM) that provides stakeholders with accessible channels to resolve project-related grievances and complaints promptly. **B. Fiduciary** **Financial Management (FM)** 74. **An FM assessment was carried out for the project in accordance with the World Bank policy and directives** **on Investment Project Financing (IPF).** The assessment was carried out on the IAs – MINEMA, RTDA, BRD, BDF and the six districts – during project preparation to determine whether they have acceptable FM arrangements, which will ensure that: (a) funds are used for the intended purposes in an effective, efficient and economical way; (b) financial reports will be prepared in a reliable, accurate, and timely manner; and (c) project assets will be appropriately safeguarded. 75. **Based on the assessment conducted, the FM risk is rated moderate.** Project arrangements will rely on the existing public FM system at the IAs and the districts, which is adequate. The IAs have experience managing", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "at national-level, but notes that examining how these dynamics is distributed spatially within the country is still not possible (Rozenberg and Hallegatte 2016). Nonetheless, as a stress test, a number of papers in the field have employed the same strategy we follow in this paper, of using current socio-economic characteristics to examine potential future trends, which is considered standard practice (Hirabayashi et al. 2013; Koks et al. 2015; Winsemius et al. 2015). 3 While we considered other metrics of poverty (e.g. the Multi-dimensional Poverty Index), the only available data that was spatially explicit was the headcount and headcount rate, which we use for the analysis. This headcount rate uses an income definition of poverty, with those earning less than $1.25 USD per day classified as poor.", "output": {"entities": {"named_data": [{"text": "Multi-dimensional Poverty Index"}], "descriptive_data": [], "vague_data": [{"text": "headcount and headcount rate"}]}}}
{"input": "IGAs, small businesses and** **cooperatives all contribute to economic empowerment and development in target areas.** By aligning Sub-component 2.2 activities with the socio-economic infrastructure and productive facilities developed under Sub-component 2.1, the project aims to maximize productivity, improve market access, and bolster local economies. Together, these efforts will foster inclusive growth and resilience by ensuring that IGAs benefit from essential infrastructure, such as grain mills, seed centers, other productive facilities and local markets, creating a supportive environment that amplifies the economic impact across communities. The project will strengthen private sector linkages, drawing from good practices identified in the Yemen Emergency Crisis Response Program (ECRP) (2016-2022) (P159053), which used a community-driven approach to sector and business selection, and provided support to SMEs and MSMEs to finance productive investments and support financial inclusion for vulnerable communities. The World Bank’s Private Sector for Refugees (PS4R) initiative also offers good practice on how to create mutually beneficial relationships between the private sector and refugee communities on entrepreneurship, employment, investment, and products and services [23] . 52. **Technical expertise will be mobilized to identify key opportunities and effective strategies for catalyzing local** **economic initiatives** . This expertise will provide specialized guidance and advice, ensuring the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "provinces combined contribute the rest. By contrast, agriculture is high in labor intensity (24 percent of total employment) but with low productivity (the contribution to GDP was 3.4 percent in 2021). [7] 4. **Zambia’s economy and population are highly vulnerable to climate change.** The country’s dependence on rainfed agriculture, which employs two-thirds of the workforce, and on hydropower makes it particularly vulnerable to climate shocks, threatening food production, electricity supply, and economic growth. While the country experiences low exposure to natural disaster risks in general, resilience is hindered by social vulnerability. Adverse impacts of climate change include increased frequency and severity of seasonal droughts, higher temperatures, flash floods, occasional dry spells, and changes in the growing season. In agriculture, the key risk stemming from climate change is the projected lower maize yields, as this is the country’s staple crop. Zambia is currently experiencing drought conditions in 84 of its 116 1 Zamstats.gov.zm. 2 Zambia Statistics Agency. 2023. _Highlights of the 2022 Poverty Assessment in Zambia_ . World Bank. 2023. _Zambia Gender Assessment_ . 3 Zambia: Selected Issues, IMF, 2023. 4 2022 Census of Population and Housing, GRZ 2023. 5 According to the 2021 Labour Force Survey Report by Zamstat, the", "output": {"entities": {"named_data": [{"text": "2022 Census of Population and Housing"}, {"text": "2021 Labour Force Survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "activities to be implemented under DRDIP II in the 13 refugee settlements, 12 RHDs, refugee transit districts, and selected secondary cities. 82. **The potential E&S risks that may arise from component 1 civil works may include:** noise, dust, soil, water pollution, construction debris, sedimentation and deposition of fine materials in downstream watercourses during construction; soil and water pollution due to construction and occupational hazards. Some of the project activities under component 2 on INRM will also have positive environmental impacts. 83. **There are risks to sensitive ecosystems and biodiversity hotspots in the western and south-western RHDs.** The western region of the project falls within the Albertine Rift valley, considered one of the global biodiversity hotspots, with many tropical high forests remaining but under high pressure. The western region has a dense network of national parks, wildlife reserves, and natural forests. Kyangwali, Rwamwanja, and Kiryandongo refugee settlements are situated near Bugoma Central Forest Reserve, Katonga Wildlife Reserve, and Kibeka Central Forest Reserve, which have already been encroached upon. Likewise, the south-western region has Lake Nakivale and Mburo-Nakivale wetland system, which serves as a habitat for unique species of birds, animals, plants, and fish. Page 23", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "To construct a water-resource indicator, we draw on two sources of information. The first is an estimated geographic distribution of excess demand for water resources (surface and sub-surface) in Vörösmarty, et al. (2000). We use GIS to compute the total population residing in excess-demand areas identified by this research. The second information source is a database of deaths and injuries from floods maintained by the Centre for Research on the Epidemiology of Disasters (CRED, Université Catholique de Louvain). For each of the Bank's partner countries, we calculate the sum of deaths and injuries for all recorded floods since 1960. In constructing an indicator for flood damage, we weight deaths to injuries in the ratio 50:1. Using equal weights, we combine our indicators for demand pressure and floods into a composite indicator of water-related problems. [4] We derive our indicator for environmental policy and institutional problems from two sources. The first is the World Bank's Country Policy and Institutional Assessment (CPIA) database, which rates environmental policies and institutions on a numerical scale of 1 (the lowest) to 6. For this exercise, we reverse the scaling (1 becomes the highest) and normalize the ratings so that countries with the greatest problems score", "output": {"entities": {"named_data": [{"text": "Country Policy and Institutional Assessment (CPIA) database"}], "descriptive_data": [{"text": "database of deaths and injuries from floods"}], "vague_data": []}}}
{"input": "will be served by health centers, resulting in 50 maternal lives saved per year and a 15 percent reduction in other causes of morbidity (baseline morbidity of 19 percent). [28] The NPV of these investments is estimated at US$1.3 million at a 12 percent discount rate, with an ERR of 29 percent. 61. _Communal WASH_ investments reduce morbidity from diarrhea and other waterborne diseases, along with time and cost savings to access water. The analysis assumes the mortality rate due to unsafe water will reduce by 10 percent (from 25 deaths per 100,000 to 22.5), along with time savings of two hours per week per beneficiary household in accessing clean water and US$20 in annual cost savings per household (CEIC data). The NPV of these WASH investments is estimated at US$1.1 million at a 12 percent discount rate, with an ERR of 28 percent. 62. Additional assumptions used in the analysis for this component include: (a) value of a statistical life: US$2,394; [29] and (b) annual O&M costs of five percent of total investment value. [30] 63. The results of the analysis for this component and the sensitivity analysis are summarized in the tables below: **Table 6: NPV and ERR", "output": {"entities": {"named_data": [{"text": "CEIC data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "we would have liked a sample to include data from the same households before and after the reform. The fact that NBS changed its panel of households in 2011 makes this impossible. The ability to use two panel data sets, each with multiple observations per household before and after the reform, still allows us to control for time-invariant household characteristics. [10] This implies that we can use a triple-difference approach that focuses on changes between the first and second panel period for the same households between treated and non-treated households in pre- and post-reform periods. Given the involvement of supervisors resident in the sample villages and the use of detailed logbooks to record consumption on a daily basis (Chen and Ravallion 1996), NBS data on consumption are considered of exceptionally high quality (Jalan and Ravallion 1999). Beyond information on consumption, the survey includes (less precise) data on income and individual members’ labor supply to farm or off-farm activities, migration, income from different sources, and an account of agricultural output and inputs. We also have data on key village characteristics including total working age population, agricultural land, and distance to public health and education facilities to control for village level time-varying", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "NBS data on consumption"}], "vague_data": [{"text": "two panel data sets"}, {"text": "data on key village characteristics"}, {"text": "data on income"}]}}}
{"input": "direct and indirect human actions. Fifth, we have not estimated the net present value of the coastal wetland loss over a period of time. The remainder of the paper is organized as follows. Section 2 summarizes the data sources and describes the methodology. Section 3 presents area estimates of wetlands at risk from sea-level rise (SLR) as well as the economic value of these projected losses. Section 4 briefly concludes. ##### **Data and Methodology** ###### **II.1 Data** In order to assess the exposure of wetlands at risk from SLR, we employed Geographic Information System (GIS) software to overlay the area of the wetlands with the inundation zones projected for 1m SLR. We have used the best available spatially-disaggregated global data sets from various sources, including the National Aeronautics and Space Administration (NASA), the US Geological survey (USGS), the World Wildlife Fund (WWF), and the Dynamic and Interactive Assessment of National, Regional and Global Vulnerability of Coastal Zones to Climate Change and Sea-Level Rise (DINAS-Coast) project. In particular: _Country boundaries and regions and coastlines_ . Country coastlines were extracted from the World Vector Shoreline, a standard National Geospatial Intelligence Agency (formerly Defense Mapping Agency) product at a nominal scale of 1:250,000.", "output": {"entities": {"named_data": [{"text": "World Vector Shoreline"}], "descriptive_data": [{"text": "the best available spatially-disaggregated global data sets"}], "vague_data": []}}}
{"input": "vulnerability to flooding, drought, and landslides and their adaptation and resilience priorities; (b) climate-sensitive planning; and (c) climate-resilient infrastructure standards for local government authorities and community institutions, including energy efficiency and renewable energy in schools and health facilities to respond to climate risks. Targeted capacity building will be provided for women in the community committees to strengthen their capacity to engage. 29. _Sub-component 1.3: Displacement Crisis Response Mechanism (DCRM) (US$10 million)._ The DCRM is a contingency financing mechanism for RHDs that experience large refugee inflows. Funds from this sub-component will be rapidly disbursed to districts that reach pre-agreed population triggers in terms of children per school classroom, patients per health facility, and people per water point. The DCRM financing will be used for infrastructure construction, upgrading or rehabilitation to expand education, health, and water service capacity in districts experiencing public service pressure caused by large refugee inflows. The DCRM triggers, eligible expenditures, and other details will be defined in an updated DCRM Manual for Phase II, approval of which by the World Bank is a disbursement condition. The sub-component will: (a) fund data collection to measure strains on schools, health facilities, and water points in the RHDs; and (b) finance", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the needs of communities to intensify their coping strategies including livelihood-seeking activities that may expose them to ED risks. The application of the [sanctions in progress following the coup in Niger could increase the cost of living](https://ecowas.int/wp-content/uploads/2023/07/COMMUNIQUE-FINAL-CINQUANTE-ET-UNIEME-SOMMET-EXTRAORDINAIRE-DE-LA-CONFERENCE-DES-CHEFS-DETAT-ET-DE-GOUVERNEMENT-DE-LA-CEDEAO-SUR-LA-SITUATION-POLITIQUE-AU-NIGER.pdf) and increase the vital needs of already vulnerable populations. This new situation would expose them to the risk of enrolment in NSAG for a salary and therefore increase the capacity of NSAG in the installation of ED. In addition, the population could intensify their survival strategies by engaging in several types of activities to adapt to the high cost of living, including the search for subsistence in areas potentially affected by ED. Consequently, an upsurge in ED incidents is very likely. ## **III. Major challenges in mine action interventions (MA)** Graph4. Mapping of MA activities, 30 juin 2023 In January 2023, the Protection Cluster launched a joint initiative of mapping protection interventions including mine action. The analysis of the data resulting from this mapping combined with the analysis of the protection response monitoring data brought out the observation below: - Only two protection actors have interventions in MA which cover only a few localities of the 7 out of 11 departments affected by", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "protection response monitoring data"}], "vague_data": []}}}
{"input": "The World Bank Economic Review 695 BASIX conducts marketing visits through village meetings and door-to-door visits. The first step is to hold a group meeting in the village, where potential customers are shown a marketing video that includes details about rainfall insurance (and other BASIX products). It then speaks with visitors and answers questions. The BASIX team then makes a follow-up visit where it goes door to door, trying to sell BASIX products, including rainfall insurance. Data The data set consists of the entire set of BASIX’s purchasers of rainfall index insurance from 2005 through 2007, which covers six states. [3] Though it ran small pilots in 2003 and 2004, BASIX began to mass-market rainfall insurance starting in 2005. The data contain limited personal information about each customer, including their location, how many policies they purchased, and what payouts they received during that season. The BASIX data covers 42 weather stations and includes a total of 19,882 customers during the period 2005–2007. [4] After numerous rainfall shocks in 2006, BASIX realized that many customers who had purchased only a small amount of insurance were disappointed that they received small payouts. In response, BASIX instituted a rule in 2007 that required", "output": {"entities": {"named_data": [{"text": "the BASIX data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "highly-developed. The resulting composite indicator for South Africa (8.49) is about 2.5 times Chad’s indicator value (3.44). Kenya has about the same composite indicator value as South Africa (8.35), but the indicator components are quite different. Kenya’s environmental indicator (2.39) is somewhat more than half of South Africa’s (4.24), but Kenya’s institutional problem indicator (3.5) is about 1.8 times South Africa’s. As a result, the products of the two indicators are nearly the same for the two countries. Of the four countries, Nigeria has by far the largest composite indicator value (25.29) because of the size of its overall environmental indicator (8.43). the equal-weighted index. Our results show that correlations among the indicators remain at .95 or higher, over a broad range of plausible definitions. 7", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "that net receipts from these schemes were, if anything, lower to for households inside the prefecture boundary than outside. Treatment and control areas may already have followed different growth trajectories before reforms. The standard way to check whether may have been the case is to test for parallel trends. [13] As discussed in detail below, we cannot reject the hypothesis of no significant differences in pre-reform trends between households inside and outside the border for overall household welfare and the share of income derived from agriculture non-farm employment, migration, and local wages and, with one exception, individuals’ time use, and agricultural yields and profits. Some significant pre-reform trends exist, however, with respect to use of agricultural inputs and crop choice. They point towards marked declines in agricultural assets ( 18% in Chengdu vs. +35% in villages outside the prefecture boundary) and use of inputs (-38% vs. -16%). Output shares of wheat and other grains increased and those of oil crops decreased in Chengdu while the opposite was true for households in neighboring counties. Also, key interventions in place during the period of concern are a new rural pension scheme (Lei _et al._ 2013), cooperative medical scheme (Wagstaff _et al._ 2009),", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "price increasing profitability and extending life length. The expansion across artisanal small-, medium-, and large-scale mining contributed to an increase in total production that rose from 541,147 oz in 1990 to 3,119,823 oz in 2009 according official Ghana statistics (Bloch and Owusu, 2012). This production increase led to an increased sector contribution to GDP from 4,83% (1990) to 5,78% (2009), alongside export value of US$304m in 1990, US$702m in 2000, and US$2246 m in 2008, reaching 43% of national exports in 2008. Mining related foreign direct investment (FDI) also rose from US$165m to US$762m between 1995 and 2009. Mining was the dominating sector with between 48% and 94% of mining FDI to total FDI from 1995 to 2007, until the country saw an incredible increase in non-mining foreign direct investment (Bloch and Owusu, 2012), following the discovery of oil in 2007. 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "official Ghana statistics"}]}}}
{"input": "counterfactual, and does not allow quantification of benefits in a way that can be compared to the cost of the intervention. To provide these and, in doing so, draw out the implications of the experiment in a more systematic manner, more systematic survey evidence is needed. **2.3 Analytical approach and data sources** We use panel data from the National Bureau of Statistics’ regular household survey in 7 counties adjacent to the border of Chengdu prefecture (3 counties inside and 4 outside the boundary), [9] as illustrated in figure 1 to assess household-level effects of Chengdu’s property rights reform on household welfare, time use, inputs into and productivity of agricultural production. A modified regression discontinuity design whereby reform effects are identified by comparing between counties located just inside the prefecture border who were affected by the reform and otherwise comparable ones just outside the border who were not is applied. Ideally, we would have liked a sample to include data from the same households before and after the reform. The fact that NBS changed its panel of households in 2011 makes this impossible. The ability to use two panel data sets, each with multiple observations per household before and after the", "output": {"entities": {"named_data": [{"text": "National Bureau of Statistics’ regular household survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Policy Research Working Paper 7388 ### **Abstract** As part of a national experiment in 2008, Chengdu pre fecture implemented ambitious property rights reforms, including complete registration of all land together with measures to ease transferability and eliminate migration restrictions. A triple difference approach using the Statistics Bureau’s regular household panel suggests that the reforms increased consumption and income, especially for less wealthy and less educated households, with estimated benefits well above the cost of implementation. Local labor supply increased, with the young shifting toward agriculture and the old toward off-farm employment. Agricultural yields, intensity of input use, and diversity of output also increased. Improving property rights in peri-urban China appears to have increased investment and diversification. This paper is a product of the Agriculture and Rural Development Team, Development Research Group. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted at kdeininger@worldbank.org. _The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development_", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "Statistics Bureau’s regular household panel"}], "vague_data": []}}}
{"input": "salinization, and pesticide exposure, which risk human and animal health. 77. **The Social risk is rated as Substantial.** Component 1 activities, such as Cash for Nutrition, Productive Inclusion, strengthening the social registry, and distributing community resilience kits, may present risks of elite capture, social conflict, and excluding vulnerable individuals like women, young mothers, and persons with disabilities due to inadequate beneficiary targeting. These activities might also increase risks of Sexual Exploitation and Abuse/Sexual Harassment (SEA/SH), corruption, fraud, and theft from households receiving benefits and kits. Additional risks include poor stakeholder engagement, weak grievance management, exclusion from beneficiary lists, payment delays, road safety especially of project workers, and insufficient enforcement and training for Codes of Conduct. 78. **Component 2.1 will finance developing and rehabilitating essential infrastructure in rural communities of Dikhil** **and refugee-hosting areas in Ali Addeh, Holl Holl, and Obock**, aiming to increase access to services like electrification, water and sanitation, renewable energy, health and education facilities, roads, and utilities. Risks related to land acquisition and physical and/or economic displacement are unknown, but activities causing these risks are expected to be ineligible for financing. Some key risks under this component include: SEA/SH from labor/project workers in remote areas; accidents from", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "the social registry"}], "vague_data": []}}}
{"input": "The data for our study come from the 2005/2006 Uganda National Household Survey (UNHS), fieldwork for which was conducted by the Uganda Bureau of Statistics from May 2005 to April 2006. The survey collected information at the community, household, and parcel level for about 7,500 households in 753 EAs including 30 IDP camps. Household level data cover demographics, main economic activities, education, health, assets, income levels and sources, as well as consumption and welfare indicators. The agricultural module provides information on ownership status, crop production, input use and land-related investment at the parcel level, complemented by other forms agricultural income. [13] The 2002 population census was used as a sample frame. Following stratification into urban (30%) and rural (70%) sub samples, enumeration areas (EAs) were chosen with the probability of selection being proportional to size. Based on a listing of households in each of the selected EAs, 10 households per EA were randomly sampled. As table 1 illustrates, 5,530 of the sample households were involved in agricultural activities. Of these, about 31%, or 1,728 with 5,448 parcels, are mixed owner/occupants who operated at least one parcel under full ownership and one under usufruct. This sub-sample forms the basis for our", "output": {"entities": {"named_data": [{"text": "2005/2006 Uganda National Household Survey"}, {"text": "2002 population census"}], "descriptive_data": [], "vague_data": []}}}
{"input": "2024 CRITICAL FUNDING NEEDS IN EUROPE ###### **Ukraine Situation** As the full-scale war in Ukraine continues unabated, ongoing hostilities are heavily impacting civilians, with **3.7 million people currently internally displaced.** [1] UNHCR and partners are on the frontline providing lifesaving assistance to the newly displaced, including psychosocial support, legal assistance, core-relief items, cash assistance and emergency shelter support and repairs. Where conditions allow, UNHCR is supporting government-led early-recovery efforts including repairs to civilian housing and infrastructure. Heading into yet another winter—and with targeted attacks compromising energy infrastructure in parts of the country—additional funding is critical to help scale up assistance for millions of people to repair their damaged homes, afford electricity and heating costs, and ensure they have access to essential non-food items such as clothing, heaters, thermal kits, as well as cash assistance. Over **6.1 million refugees** from Ukraine have sought safety across Europe, where host countries have generously provided protection, access to services, and inclusion into national systems. However, host governments and communities need support to guarantee access to rights and services, provide dedicated support for the most vulnerable, foster greater inclusion and ensure social cohesion. UNHCR leads the **[Regional Refugee Response Plan](https://data.unhcr.org/en/documents/details/105903)** (RRP) for the Ukraine Situation", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "initiatives and ongoing strong political will in Europe remain promising, concrete efforts are needed to support those without legal recognition in the region. **UNHCR’S 2024 FINANCIAL REQUIREMENTS** **FOR STATELESSNESS-RELATED ACTIVITIES** **IN EUROPE** **TOTAL FUNDED (as of 30 Sept 2024)** The breakthrough came early this year when with UNHCR’s support, Sadik’s wife Buqa obtained identity documents. This enabled the registration of their children in birth registries and paved the way for them to apply for identity documents. The new legal status has opened new frontiers for the family, granting them access to healthcare, education, social assistance, and more. © UNHCR/Igor Sljivancanin _* References to Kosovo shall be understood to be in the context of Security Council Resolution 1244 (1999)._ Page 6 **U N H C R R E G I O N A L B U R E A U F O R E U R O P E,** O C T O B E R 2 0 2 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "birth registries"}]}}}
{"input": "**The World Bank** Integrated Community Resilience Project (P506969) PROJECT APPRAISAL DOCUMENT 62. **M&E teams will also be embedded in each of the Project Implementation Unit (PIU), MASS and ADDS** . These teams, in coordination with the community facilitators mobilized at local level, will be responsible for collecting data based on the results framework outlined in the M&E plan. They will transmit data on a regular basis, contributing to the periodic reports. Data to track key performance indicators will be collected from various sources: (a) project-specific surveys and questionnaires; (b) service providers; (c) local governments; (d) consultant reports; and (e) construction progress reports from supervising engineers/ engineering firm. 63. **A comprehensive midterm review of the project’s implementation and results will be conducted by the** **government and the World Bank in 2027, during which the target values will be assessed and any necessary adjustments** **to the project design will be made if needed.** The project will provide targeted support to strengthen M&E capacity within MASS and ADDS. Where feasible, the project will finance consultants to assist MASS and ADDS in developing a detailed M&E and reporting system plan. In addition, consultants will provide on-the-job training for M&E specialists across MASS, ADDS, and", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "project-specific surveys and questionnaires"}], "vague_data": [{"text": "project-specific surveys and questionnaires"}]}}}
{"input": "_Note:_ Figure 4 shows the main treatment coefficients using the baseline estimation strategy (with DHS individuallevel data; see table 4 for more information), but with different distance cutoffs (10 km, 20 km, 30 km, 40 km, and 50 km). *** p<0.01, **p<0.05, *p<0.1. The results above suggest substantial heterogeneity in outcomes and highlights the importance to explore spatial heterogeneity in the results. In the following sections we explore plausible explanations for these outcomes. **5.4 Difference-in-differences at the district level** The results for female employment in the district-level analysis are shown in table 6. Agricultural work decreases for women in mining districts and manual work increases. Following from this, the likelihood that a woman is working year-round increases. [11] This is similar to what we saw in the individual-level regressions, but the results are now statistically significant. **Table 6 Effects of mine opening at the district level on female employment** (1) (2) (3) (4) (5) (6) (7) not agri- service profess- manual earns works working culture or sales ional work cash all year Active district 0.019 -0.085** 0.034 -0.018** 0.050** -0.021 0.054* (0.027) (0.042) (0.030) (0.008) (0.020) (0.049) (0.032) Observations 19,226 19,226 19,226 19,226 19,226 19,270 15,991 R-squared 0.207 0.327 0.128", "output": {"entities": {"named_data": [{"text": "DHS individuallevel data"}], "descriptive_data": [{"text": "DHS individual level data"}], "vague_data": [{"text": "DHS individual-level data"}]}}}
{"input": "only in conjunction with policies for local procurement. Moreover, some of the mining-related papers have focused on mining in an African context, exploring a range of outcomes, including HIV-transmission and sexual risk taking (Corno and de Walque 2012; Wilson 2012), women’s empowerment (Benshaul-Tolonen 2018), infant mortality (Benshaul-Tolonen, 2019) and labor market outcomes (Kotsadam and Tolonen 2016). Mining is also associated with more economic activity measured by nightlights (Benshaul-Tolonen, 2019; Mamo et al, 2019). Kotsadam and Tolonen (2016) use DHS data from Africa, and find that mine openings cause women to shift from agriculture to service production and that women become more likely to work for cash and year-round as opposed to seasonally. Continuing this analysis, Benshaul Tolonen (2018) explores the links between mining and female empowerment in eight gold producing countries in East and West Africa, including Ghana. Women in gold mining communities have more diversified labor markets opportunities, better access to health care, and are less likely to accept domestic violence. In addition, infant mortality rates decrease with up to 50% in mining communities, from very high initial levels (Benshaul-Tolonen, 2019). In a study that focuses exclusively on Ghana, Aragón and Rud (2013) explore the link between pollution from", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "DHS data from Africa"}], "vague_data": []}}}
{"input": "# **MOLDOVA** **OLDER REFUGEES** **BRIEFING NOTE** #### Disability & Age Task Force Refugee Coordination Forum Moldova ### **JANUARY 2025** The **Disability & Age Task Force (DATF)** was established in March 2022 with the support of the Refugee Coordination Forum and under the **Protection Working Group** . The Task Force is composed of humanitarian actors including Government authorities, United Nations Agencies, International and National NGOs, and Organizations of Persons with Disabilities (OPDs), providing specific services for people with disabilities and older people. Its objective is to improve the inclusion of older persons and persons with disabilities in the Ukrainian Refugee Response in the Republic of Moldova, ensuring access to mainstream services as well as guaranteeing the availability of specific services to respond to needs. ## **BACKGROUND** Almost three years have passed since Russia’s full-scale invasion of Ukraine in February 2022, forcing millions of Ukrainians to flee the country in search of safety. Moldova in its turn is the country that has received **the largest numbers of** **refugees per capita** of the population of **2,4 million** . As of end December 2024, about 135,000 refugees from Ukraine still remained sheltered in Moldova, with about 76,000 having received asylum, temporary protection, or residence", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the project is counted towards Private Capital Enabling (PCE) and Private Capital Mobilization (PCM). Component 2 on Economic Opportunity & Self-Reliance is verified as both PCE and PCM by supporting a partial credit guarantee (PCG) scheme and matching grants. Sub-component 2(c) support to the Business Development Fund (BDF) PCG scheme is expected to facilitate access to finance for up to 3,000 7 African Development Bank, UNHCR, IGAD & EAC (2024) _Regional Report:_ _Regional Program on Enhancing the Investment Climate for the_ _Economic Empowerment of Refugee, Returnee, and Host/Return Community Women in the East and HoA and Great Lakes Region._ 8 Access to Finance Rwanda (2024) _FinScope 2024 Report_ . The report shows high levels of financial inclusion but low usage of financial services. 9 Non-monetary poverty for the other four host districts is: Nyamagabe (Kigeme camp) 39 percent, Gatsibo (Nyabiheke Camp) 37 percent, Kirehe (Mahama camp) 35 percent and Karongi (Kiziba camp) 34 percent. Data is from the 2022 Census. 10 World Bank (2021) _Climate Risk Profile: Rwanda_ . 11 Alex Hunns et al (2023) “Refugee Settlements are Highly Exposed to Extreme Weather Conditions.” Page 3", "output": {"entities": {"named_data": [{"text": "2022 Census"}], "descriptive_data": [], "vague_data": []}}}
{"input": "before_ active*mines -0.013 0.025 -0.018* 0.002 0.003 0.075*** -0.028 (0.040) (0.030) (0.009) (0.021) (0.024) (0.028) (0.037) _Note:_ Robust standard errors clustered at the DHS cluster level in parentheses. All regressions control for year and district fixed effects, urban dummy, age, and years of education. *** p<0.01, **p<0.05, *p<0.1. Panel A is limited to bottom 40% in the income distribution, panel B uses urban interaction, and panel C has a count variable for active mines. Panel D1 drops sample between 20 and 40 km away, and D2 drops individual samples two years before mine opening. 151 women are sampled within 20 km from an active mine and in an urban area, and 246 women are sampled within 20 km from a mine regardless of its activity status and in an urban area. **Table A4 Spillovers on employment across districts** Panel A: Using production in the previous period (1) (2) (3) (4) (5) (6) (7) not agri- service profess- manual earns works VARIABLES working culture or sales ional work cash all year gold period 0.004 -0.009** 0.003* 0.004*** -0.002 0.001 0.006 District (0.004) (0.004) (0.002) (0.002) (0.004) (0.003) (0.004) neighbor -0.004 0.005 -0.001 -0.002*** 0.001 0.008* -0.002 gold production (0.004) (0.004) (0.004)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Preparing country boundaries and coastlines_ . Countries and regions were identified with data from the World Bank and Exclusive Economic Zones from VLIZ (2011). The coastlines are derived from the SRTM 90 meter digital elevation model (DEM) data files used as a mask for calculating country totals for wetlands. Information on WMP categories for the Coastline was downloaded from the DIVA GIS database. _Building coastal terrain models (DTM)_ . Coastal terrain models derived from the SRTM 90 meter DEM data files were converted into an ESRI ArcGIS data format, and merged to conform to country boundaries in the ArcGIS environment. The analysis includes SRTM tiles, which are 5 x 5 decimal degrees, with a coastline. _Identifying inundation zones:_ Inundation zones were derived from the DTM by setting the value to 1 for SLR equal to 1 m. _Calculating exposure indicators_ . Delineated inundation zones were overlaid with wetlands to calculate exposure of wetlands to a 1 m SLR. Low elevation wetlands are within the Low Elevation Coastal Zone [17] . For the area calculation, grids representing cell areas in square kilometers at different resolutions were created, using the length of a degree of latitude and longitude at the cell center.", "output": {"entities": {"named_data": [{"text": "DIVA GIS database"}, {"text": "SRTM 90 meter DEM data files"}], "descriptive_data": [{"text": "Exclusive Economic Zones from VLIZ"}], "vague_data": [{"text": "data from the World Bank"}]}}}
{"input": "caregiving responsibilities over business activities. This norm restricts their time and engagement in income-generating pursuits and weakens their perceived legitimacy as entrepreneurs, reducing their chances of qualifying for credit. Additionally, women are often expected to rely on family support, especially from spouses, instead of seeking independent financial solutions, distancing them from formal financial institutions and financial products. 31 Baseline failure rates by segment are extremely difficult to assess. As such, the analysis uses conservative assumptions based on extensive discussions with key stakeholders and potential beneficiaries. These assumptions have been tested for sensitivity. 32 CEIC data 33 In the absence of available survey data, the analysis uses proxies for these losses and repair costs from survey data from neighboring Burundi. Based on this data, annual flooding losses amount to ~US$89 per household and repair costs amount to US$25.60 per household. 34 [Gendered Social Norms Diagnostic and their Impact on Women’s Financial Inclusion in Rwanda, 2022, Access to Finance Rwanda](https://afr.rw/downloads/gendered-social-norms-diagnostic-and-their-impact-on-womens-financial-inclusion-in-rwanda/) Page 18", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "survey data from neighboring Burundi"}], "vague_data": [{"text": "survey data"}]}}}
{"input": "with the notion that reduction of expropriation threats led to more effective use of agricultural land that created jobs for the less-skilled. **4.2 Impacts on time use** If, for example by promoting land-related investment or productivity-enhancing transfers of land to more efficient uses or users via rental markets, reforms increased productivity of land use and wages or changed certain activities’ relative productivity, we would expect corresponding shifts in overall labor supply or time allocation across sectors. [15] As we have individual level data on labor supply, we can use regressions for all individuals of working age (16-60 or 16-55 for males and females) in the sample to disaggregate estimated reform effects by gender. [16] Doing so suggests that reforms led to an expansion of labor market opportunities and a significant increase in total labor supply by males -with the young (16-40 years old) focusing on agriculture and the old (41-60 years old) on off-farm work and similar shifts, though no change in aggregate labor supply, by females. 14 With a mean cultivated area of 3.45 mu, the estimated benefit per mu in terms of consumption and income is 3,150*0.077/3.45 and 4,928*0.067/3.45, respectively. . 15 As we have information on time", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "individual level data on labor supply"}]}}}
{"input": "million people in Sub-Saharan Africa are estimated to live in both extreme poverty (using a $1.9 a day definition) and significant flood risk – thus making them particularly vulnerable to prolonged adverse impacts on livelihoods and well-being. The remainder of this study is structured as follows. Section 2 offers an overview of the existing evidence base, especially on flood risk and poverty. Section 3 summarizes the flood risk, population, and poverty data used in the analysis. Section 4 details the analytical methodology and computational process. Section 5 presents and discusses the results. [1] ##### **2. Existing evidence** Prior to the availability of high-resolution global flood hazard maps, studies relied on historical disaster catalogues to produce rough global exposure estimates. Peduzzi et al. (2009) use a global inventory of recorded flood events from EM-DAT to estimate an exposure indicator at the country level. Yet, the lacking data on the spatial distribution and coincidence of flood risk and population, this approach does not allow a robust estimation of exposure headcounts. Jongman et al. (2012) provide the first global flood exposure analysis that utilizes spatial hazard and population data, albeit at relatively coarse resolution by current standards (10 x 10 kilometers for population", "output": {"entities": {"named_data": [{"text": "EM-DAT"}, {"text": "high-resolution global flood hazard maps"}], "descriptive_data": [], "vague_data": [{"text": "spatial hazard and population data"}]}}}
{"input": "**Calculate sums** - For each flood risk array, calculate the total number of people exposed and add the results to the World Bank global administrative map shapefile ##### **5. Results** For each of the countries analyzed, the results are available as raster files with a 90m spatial resolution and as shapefiles with data aggregated to the admin 1 (sub-national), admin 0 (national), regional, and global levels. In this section, we present visualizations of key findings as maps, using a variety of spatial scales, as well as graphs to highlight pertinent insights. **5.1.** **Global and regional flood exposure** Our estimates show that globally 2.2 billion people are exposed to some level of flood risk; 1.47 billion people, or 19 percent of the world population, are exposed to a significant level of flood risk (i.e. facing inundation depths of over 0.15 meter in the event of a 1-in-100 year flood, or _moderate_ risk or higher in Figure 2). In other words, considering a global population of 7.7 billion (World Bank, 2019), approximately one in five people in the world are exposed to substantial flood risk. 10", "output": {"entities": {"named_data": [{"text": "World Bank global administrative map shapefile"}], "descriptive_data": [], "vague_data": []}}}
{"input": "maps developed for this study allow for this potential in future work. For the HCMC analysis, the location of the slum areas in the PUMA data set are mainly restricted to the old town. Furthermore, slum areas are often difficult to define (with PUMA only identifying potential slums) and the data we have likely does not capture all slum areas within HCMC. In terms of the hazard, the flood maps for HCMC show flood depth and extent from the river and from sea (when looking at the sea level rise scenario). Pluvial flooding and possible ‘sink’-areas in the city are not taken into account. Moreover, the lowest return period we have flood maps for is not low, compared to what is experienced in the city. Some areas of HCMC are flooded every year. Since this analysis used a flood with a 10-year return period as the flooding scenario with the highest recurrence interval we were not able to capture the relative differences in exposure to these yearly/bi-annual flooding events (and we hypothesize that poor people are relatively more exposed to these types of flooding than the general population). Despite these limitations, the analysis presented at the country and city-level can", "output": {"entities": {"named_data": [{"text": "PUMA data set"}], "descriptive_data": [], "vague_data": [{"text": "flood maps for HCMC"}, {"text": "flood maps"}]}}}
{"input": "GRZ’s decentralization policy. This includes procurement and FM responsibilities. Given that the bulk of technical activities are at the district level, adherence with the ESF will rest with the SPMU. The staffing profile of the SPMU will include (a) project manager, (b) environmental specialist, (c) social specialist, (d) civil engineer, (e) agribusiness specialist, (f) project accountant, (g) procurement specialist, (h) admin assistant, and (i) driver. The TOR and eligibility criteria for the above staff will be detailed in the PIM. Detailed institutional and implementation arrangements are provided at annex 1. **B. Results Monitoring and Evaluation Arrangements** 52. **The primary responsibility for overall project M&E will lie with the national PMU at the MoHAIS.** The PMU will have M&E capacity to support the establishment of a data platform to track project implementation across different Page 23", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) 9. MEP/PIU should retain all records contracts, invoices, bills, receipts, and other documents) of expenditures related to the Project until at least either one year after the Bank has accepted the audited financial statements covering the period during which the last withdrawal from the loan account was made or two years after the closing date, whichever is later. MEP will give the Bank access to these records to examine them. 10. **FM Supervision** . Project supervision will review the implementation of FM arrangements and performance, identify corrective actions as necessary, and monitor fiduciary risks. Supervision missions will take place on an annual basis and will include desk review of project IFRs and audit reports, following-up on any issues raised by auditors, as appropriate; participation in project supervisions at least once a year, to look into the operation of the control systems and arrangements described in this assessment; and updating the FM rating in the Financial Management Implementation Support and Supervision Report, as needed. In addition, during the first year of execution, the Project will be closely monitored (biannually) to verify that the FM arrangements are working as intended and to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "to build resilience in districts experiencing large refugee inflows. A pilot to reduce gender-based violence (GBV) and violence against children (VAC) also contributed to social cohesion. A 2022 World Bank study on forced displacement reinforced the value of projects such as DRDIP, concluding that ‘multi-sectoral development investments directed to refugees and host communities can improve welfare, mitigate the negative effects of displacement, generate positive externalities for host communities, and promote social cohesion.’ [19] 21. **DRDIP II will be informed by lessons learned from Phase I and from other development responses in Uganda** **and the region over the last seven years.** Based on implementation experience and stakeholder consultations, key lessons include: (a) the CDD approach – particularly community-led procurement – is effective in the Uganda context for planning, community engagement, targeting, monitoring, and implementation; (b) the Labor-Intensive Public Works (LIPW) approach used for integrated natural resource management (INRM) subprojects based on the watershed approach has demonstrated encouraging results for environmental improvement, though with sustainability challenges for commercial assets such as tree plantations; (c) infrastructure investments have been of high quality and have improved basic services, including reported reductions in pupil-classroom, pupil-desk, and pupil-sanitation facility ratios. However, operations and maintenance (O&M) needs", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "of the spatial distribution, we also find significant variation within zones. For example (Figure 8c), western coastal Bangladesh, generally a mid-impact zone, also has significant stretches of coast that have very low historical impacts. To summarize, our focal coastline area has witnessed highly-varied long- and short-term distributions of cyclonic storm impacts during the past 140 years. Our database therefore incorporates three major elements that are important for research on expectations formation and adaptation: pronounced long-term impact clustering; highly-varied clustering over 20-year periods; and a pronounced west/east trend. As previously noted, such variation is necessary for using cyclone impacts as effective statistical controls in comparative adaptation studies. We conclude that our panel database can make a significant contribution to household- and community-level studies that also incorporate social, economic, demographic and political variables from the relevant regions of India and Bangladesh. 21", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "panel database"}]}}}
{"input": "with partner countries. We accept these overall preferences, and assume that future thematic lending shares will be identical to the lending shares for the period 1998 - 2003. **Table 7.1: Tests of the Cobb-Douglas Allocation Rule:** **Environmental Lending and AAA** (Standard errors in parentheses) Log Log Lending AAA Log Environmental Problem 1.136 1.265 Indicator (EPI) (0.18)** (0.21)** Log OED Success Probability (OSP) 2.602 1.143 (0.73)** (0.87) Constant -9.960 -5.099 (3.09)** (3.67) Observations 139 139 R-squared 0.28 0.21 Adj. R-Squared 0.27 0.20 **F [EPI = OSP = 1]** **2.65** **0.78** **Prob. > F** **0.07** **0.46** significant at 5%; ** significant at 1% _____________________________________________________________ We also use the lending shares as guidelines for AAA, since the Bank’s analytical and advisory activities are supposed to serve its lending program. Table 7.2 presents percent changes associated with movement from actual to optimal lending by sector and region. In Sub-Saharan Africa, for example, the overall gap between actual and optimal environmental lending is small (+5%), but thematic gaps vary from around -40% for climate change and biodiversity to +64% for land. South Asia has a relatively large overall gap (+33%), and thematic gaps ranging from -60% or less for biodiversity and climate change to over", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "GoR has progressive laws and policies on forced displacement.** The World Bank, in consultation with the United Nations High Commissioner for Refugees (UNHCR), has confirmed that Rwanda’s refugee protection framework is adequate for the purposes of access to the Window for Host Communities and Refugees (WHR). [5] Rwanda is a signatory to the 1951 Refugee Convention and the Global Compact on Refugees (GCR). The 2014 _Law_ _Relating to Refugees_ complies with international law and entrenches the right to work and freedom of movement. At the policy level, Rwanda’s _Strategic Plan for Refugee Inclusion 2019-2024_ made commitments to: (a) provide all [1 Data is from April 30, 2025. There are also 14,936 asylum-seekers in Rwanda: see https://data.unhcr.org/en/country/rwa](https://data.unhcr.org/en/country/rwa) [2 Loschmann, C., Bilgili, O. & Siegel, M. (2019) “Considering the benefits of hosting refugees: evidence of refugee camps influencing local labour](https://link.springer.com/article/10.1186/s40176-018-0138-2) [market activity and economic welfare in Rwanda,” IZA Journal of Development & Migration, pp. 1-23.](https://link.springer.com/article/10.1186/s40176-018-0138-2) 3 The self-reliance survey is part of the “Enhancing Self-Reliance and Preparedness for Forced Displacement in the Great Lakes Region” activity [(P500793) and draws on the global Refugee Self-Reliance Initiative index (www.refugeeselfreliance.org).](http://www.refugeeselfreliance.org/) 4 Phase I of Jya Mbere was approved on April 30, 2019, and will close", "output": {"entities": {"named_data": [{"text": "global Refugee Self-Reliance Initiative index"}], "descriptive_data": [{"text": "self-reliance survey"}], "vague_data": []}}}
{"input": "ship-to-shore radio after 1900, aircraft observation after 1940, and satellite observation after 1960. Measurement error has undoubtedly fallen over the years, but we cannot judge whether earlier technologies imparted any systematic bias to the recording of cyclone occurrences, track locations, wind speeds and storm radii. If historical observations have been unbiased estimates of storm characteristics, then the aggregative estimates in this paper should be also be regarded as unbiased, but with significantly-decreasing variance over the 140-year period. The remainder of the paper is organized as follows. Section 2 provides a technical discussion of database construction. Section 3 employs the database to investigate trends in the incidence and power of Indian Ocean cyclonic storms from 1877 to 2016. Section 4 focuses on trends in the spatial distribution of cyclone landfalls in Bangladesh, West Bengal and Odisha, while Section 5 broadens the analysis to impact zones around cyclone landfalls. Section 6 summarizes and concludes the paper. **2. Georeferenced Database Construction** We combine data from BMD, IMD and IBTrACS to document all recorded cyclonic storms in the Indian Ocean region from 1877 to 2016. We construct a panel database; the component for each storm includes a unique identification number; year and month of", "output": {"entities": {"named_data": [{"text": "IBTrACS"}], "descriptive_data": [{"text": "BMD"}, {"text": "IMD"}], "vague_data": []}}}
{"input": "have any positive expenditure on these, and we saw earlier that electricity access changes with the mine. This confirms that, among those who spend anything on electricity, they spend more on it in mining communities. **Table 12 Using GLSS: Household income and expenditure** (1) (2) (3) (4) (5) (6) (7) (8) (9) ln ln ln ln household level ln expenditure wages wages wages pc total health hh all women men exp. exp. food housing education energy active*mine 0.520** 0.694*** 0.391 -0.178* -0.126 -0.069 0.316** -0.168 0.297** (0.226) (0.241) (0.238) (0.093) (0.089) (0.095) (0.139) (0.199) (0.119) Observations 6,226 2,914 3,312 7,522 7,522 7,396 7,420 6,541 4,752 R-squared 0.121 0.128 0.118 0.959 0.964 0.963 0.933 0.837 0.950 _controls_ individual Y Y Y hh head Y Y Y Y Y Y hh size Y Y Y Y Y district fe Y Y Y Y Y Y Y Y Y year fe Y Y Y Y Y Y Y Y Y deflated N N N Y Y N N N N mean (ln) 15.30 15.29 15.31 13.04 14.19 13.42 10.88 10.74 9.52 _Note:_ (1) Annual wages and salaries for individuals in all ages (nondeflated). (2) Annual wages and salaries for women in all ages", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Annexe 1 :** Some examples of ED incidents _(Sources : Protection Monitoring, CNCCAI, INSO)_ - _**20/03/23:**_ _around 8 a.m. the vehicle of a local authority jumped on an improvised_ _explosive device at Bougoum, Torodi-Niamey axis (Tillabery region)_ - _**25/05/23 :**_ _ED in Ngouba at the passage of shepherds. 3 dead and cows killed (Diffa region)_ - _**16/06/23**_ _: EE against a DFS vehicle in Chetima Wango. 7 dead / 4 injured (Diffa region)_ - _**6/06/23 :**_ _an explosive remnant of war (ERW) exploded against 03 children in the village of_ _Agali (department/municipality of Dosso). The victims who were looking for scrap metal_ _probably confused the device with a piece of iron that they hit with a hammer. The explosion_ _caused the death of a child and 02 injured. It should be noted that the CNCCAI Regional Branch,_ _which is supposed to coordinate EDRE activities at the regional level, does not exist in Dosso_ _due to a lack of resources._ - _**4/07/2023 :**_ _around 9 a.m., an Improvised Explosive Device (IED) allegedly exploded at the_ _passage of vehicle of the DFS Niyya operation, who were patrolling on the Torodi-Makalondi_ _axis, not far from the village of Niaktiré (Tillabéry region)._ **Annex 2:**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**(3)** **(4)** Would have been payout in 2004 −3.843*** −4.592*** −5.045** −3.788* (0.987) (1.039) (2.173) (1.898) Ratio of hypothetical 2004 payout to 2005 Premium 4.365 −0.755 (4.610) (5.543) Payout ratio squared −1.991 −0.279 (1.814) (2.064) Constant 8.001*** 0.651 7.985*** 1.015 (0.714) (6.341) (0.713) (6.494) Weather station constants NO YES NO YES Observations 733 733 733 733 R-squared 0.073 0.094 0.075 0.097 _Notes_ : The dependent variable is the number of buyers in 2005, which was the first year rainfall insurance was offered to our sample. The unit of observation is the village. Would have been Payout in 2004 is a dummy that takes a value of 1 if there would have been a payout in 2004 had the 2005 policy been offered in that year. This is calculated based on daily rainfall data from APHRODITE and each policy’s payout structure. The weather station constants are the premium in 2005, the average historical payout, the total number of historical payouts, and the standard deviation of rainfall. Historical variables are calculated for the period 1962-2004. Observations are weighted by the quality of rainfall data. If there are no rainfall stations contributing to the APHRODITE data in 2004 within a .75°x.75° grid around", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "daily rainfall data from APHRODITE"}], "vague_data": []}}}
{"input": "spirit of a Bstress-test^ to examine the seriousness of the issue, this paper employs flood hazard maps and spatial socioeconomic data to examine the following questions in context of Vietnam: 1. How many people are exposed currently? How might this change under climate change? 2. Where is exposure highest currently? How might this change under climate change? 3. How many poor people are exposed currently? How might this change under climate change? Furthermore, given that the dynamics of poverty and natural disasters (and particularly, floods) occur at the local level, analyses at the national scale (or even at the province or district level) may miss important mechanisms and small-scale differences, from one city block to the next. To complement the country-level analysis, we also focus at the local level within Ho Chi Minh City (HCMC), a city with high flood exposure. Here, we combine high-resolution flood hazard data with spatial data on slum location to examine the distribution of exposure across poor and non-poor locations. While prior studies have examined flood risk in Vietnam, this paper provides two main contributions. First, we develop new high-resolution flood hazard datasets, which incorporate both riverine and coastal flooding and consider climate change. [1]", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "spatial data on slum location"}], "vague_data": [{"text": "flood hazard maps"}, {"text": "spatial socioeconomic data"}, {"text": "high-resolution flood hazard data"}]}}}
{"input": "skewed. [10] As the scatter plot in Figure 5.1 suggests, the association between overall environmental problems and lending is very strong for those countries that have received environmental loans. **Figure 5.1: World Bank Environmental Lending vs.** **Overall Environmental Problems (Log Scale)** In a log-log regression of environmental lending on the overall environmental indicator (Table 5.1, column 1), the estimated response elasticity is .70, with an associated t-statistic of 10.3 and regression R [2] (adjusted for degrees of freedom) of .53. 10 Conventional regression and correlation analysis assume that variable distributions do not contain extreme “outlier” observations, because such outliers can sharply skew the results. In this case, both nominal and per-capita distributions are extremely skewed. Log measures, on the other hand, have regular, approximately-normal distributions with no outliers. 12", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the IAs will, however, continue to coordinate with and report to MINEMA pursuant to the terms of MoUs they will sign; and (b) BRD will convene quarterly coordination meetings with other organizations supporting host community-refugee livelihood to identify synergies and opportunities for collaboration. **B. Results Monitoring, Evaluation, and Verification Arrangements** 54. **M&E System.** MINEMA will have overall responsibility for M&E, including the preparation of consolidated quarterly progress reports and an Annual Report to the World Bank. MINEMA, BRD, RTDA and BDF will have M&E specialists responsible for collecting and collating data on project outputs and outcomes. Reporting templates will be reviewed for Phase II and included in an updated M&E section in the PIM. The existing Project MIS will continue to be utilized. 55. **Project results will be captured through baseline, annual and endline surveys.** This will include surveys of users of project-financed infrastructure (schools, health facilities, water systems, markets, etc.) to directly track satisfaction with Jya Mbere II investments. Regular phone surveys will also be conducted for beneficiaries under component two to gather data on business sustainability and profitability to allow for real-time learning and course correction as necessary. Page 15", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "baseline, annual and endline surveys"}, {"text": "surveys of users of project-financed infrastructure"}], "vague_data": []}}}
{"input": "Bank household surveys are available with subnational representativeness. These subnational units are typically provinces or states (i.e. admin1) but can also include custom groupings of subnational regions determined by the sampling strategy of household surveys. Overall, this study covers 189 countries, which are disaggregated into 2,260 subnational units. **3.4.** **Poverty estimates** For each of the 2,260 subnational units, the World Bank’s Global Monitoring Database offers several poverty estimates, which are all derived from the latest available Living Standards Measurement Survey (LSMS) for the respective country. For the purpose of this study, the standard World Bank definitions of poverty are used to determine the number of poor people in a given subnational administrative unit. Specifically, poverty is defined by the daily expenditure thresholds of $1.90, $3.20, and $5.50. ##### **4. Methodology** **4.1. Concept of analysis** To estimate the number of people who are exposed to intense flood risk, this study follows four main steps: **1.** **Generate a combined flood hazard map:** For each country and each subnational administrative unit, a single flood hazard layer is created by combining different flood types. The resulting flood map has a 90-meters resolution, with each pixel showing estimated inundation depths in meters. For pixels where", "output": {"entities": {"named_data": [{"text": "World Bank’s Global Monitoring Database"}, {"text": "Living Standards Measurement Survey"}], "descriptive_data": [], "vague_data": [{"text": "household surveys"}, {"text": "Bank household surveys"}]}}}
{"input": "**Table A2 Summary statistics for children’s surveys** (1) (2) (3) (4) far from a mine close to a mine before during before during _infant mortality_ first 12 months 0.07 0.07 0.08 0.06 _child health_ diarrhea 0.17 0.17 0.13 0.17 cough 0.24 0.22 0.22 0.18 fever 0.20 0.21 0.24 0.20 _child anthropometrics_ ht/age (st dev.) -94.43 -104.88 -127.04 -115.76 wt/age (st dev.) -90.80 -100.16 -114.28 -103.48 wh/ht (st dev.) -40.29 -45.24 -47.816 -40.52 Sample size (child at birth) 3709 2204 661 314 _Note:_ Column (1) is a sample at 20 to 100 km from a nonactive mine. Column (2) is a sample at 20 to 100 km from an active mine. Column (3) is a sample within 20 km of a nonactive mine. Column (4) is a sample within 20 km of an active mine. Infant mortality considers mine active status in birth year. ht/age = height-to-age; wt/age = weight-to-age; wh/ht = weight to height; st. dev. = standard deviation. **Table A3. Heterogeneous effects for bottom 40%, with urban locality interactions, intensity of** **mining, and timing of opening** Woman’s occupation agri- service profess- manual not earns works culture sales ional labor working cash all year PANEL A: Bottom 40% active*mine 0.033", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "As property rights and their links to rural-urban integration have recently been identified as key reform areas by China’s leadership, drawing the lessons from past reform experiments is important. Yet, beyond anecdotal accounts, few studies aim to assess either the magnitude of associated impacts or their incidence among different types of households. To provide a rigorous quantitative assessment, we use the fact that the experiment was implemented in Chengdu prefecture, with neighboring counties remaining unaffected. Panel data from NBS’ regular rural household survey for counties on both sides of the boundary allow us to assess reform impacts on household consumption and income, labor supply, incidence of land rental, crop choice, and productivity of agricultural land use. We use a triple difference strategy based on changes within the same household before and after the reform and inside vs. outside the boundary for identification, a choice justified by noting that sample counties on both sides of the border followed parallel trends before the intervention and we can control for a range of time variant public programs, in particular pension and medical schemes as well as agricultural subsidies that may have been implemented differently on both sides. Results suggest that about 3-4 years", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "NBS’ regular rural household survey"}], "vague_data": []}}}
{"input": "countries, however, until very recently Israel did not have an asylum system, and its ongoing institutional evolution is partly a response to the recent influx. Although it carries distinctive features, Israel‘s asylum regime is guided by the prevalent exclusionary logic which dominates the policies of other developed countries. This has important implications for the asylum seekers. Their countries of origin and the scale of their influx challenge existing ̳humanitarian spaces‘. Once a critical threshold has been crossed, they are seen as a threat which can no longer be contained. Accommodating measures are being rejected for self-preservation considerations, spurred-on by Israel‘s ethnonational identity. Relatively little has been written about the meaning and significance of these developments (Willen 2010a, 2010b; Afeef 2009; Kritzman-Amir 2009; Yacobi 2009; Man 2010). This study seeks to complement the existing literature, drawing on a combination of primary and secondary sources. During July 2010, a period of field work was carried out in which 14 semi-structured interviews were conducted. Representatives of the key institutional bodies that deal with refugees and asylum seekers were interviewed; namely the state (officials and politicians); civil society (senior NGO staff and academics); and personnel at the Office of the United Nations High Commissioner", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "is derived from a number of data sources and categories: ‘Lagoon’ from ArcWorld (ESRI, 1992: referenced in Lehner and Döll 2004); ‘Delta’, ‘Lagoon’, ‘Mangrove’, ‘Estuary’, ‘Coastal Wetland’, and ‘Tidal Wetland’ of WCMC wetlands map (Dugan, 1993; WCMC, 1993; referenced in Lehner and Döll 2004) - see Lehner and Döll (2004) for a detailed description. 7", "output": {"entities": {"named_data": [{"text": "WCMC wetlands map"}, {"text": "‘Lagoon’ from ArcWorld"}, {"text": "ArcWorld"}], "descriptive_data": [], "vague_data": []}}}
{"input": "a cost in net revenues because it was not clear what value to assign to wages. We controlled for household labor by using household size as a proxy. In each country, districts were chosen to get farms across a wide range of climate conditions in that country. In each chosen district, a random but clustered sample of farms was selected. The clustering helped to reduce survey expenses. The number of surveys in each country 6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the ERR to 23 percent while increasing the estimated number of beneficiaries by 20 percent increased the ERR to 35 percent. **B. Fiduciary** **(i)** **Financial Management** 63. The FM assessments for the project implementing agencies were conducted using World Bank Guidance: FM Manual for World Bank Investment Project Financing Operations, reissued on September 7, 2021. The purpose of the assessment was to evaluate the adequacy of FM arrangements to support project implementation. The objectives of the assessment were to determine whether the MoHAIS has minimum FM arrangements, adequate to ensure that (a) funds are properly accounted for and used only for the intended purposes in an efficient and economical way; (b) capability exists for the preparation of accurate, reliable, and timely periodic financial reports; (c) internal controls exist which allow 45 A 15 percent discount rate is estimated as the risk-adjusted opportunity cost of capital. Additional NPV estimates at other discount rates have also been provided as a measure of the sensitivity of the analysis. 46 This corresponds to the average village population in similar areas according to the International Organization for Migration (IOM). This information can be accessed at Village Assessment Survey County Profiles. [https://iomsouthsudan.org/tracking/sites/default/publicfiles/documents/Lakes.pdf](https://iomsouthsudan.org/tracking/sites/default/publicfiles/documents/Lakes.pdf) _._ 47 Burden of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Bangladesh and the two Indian coastal states, our methods are general and could be expanded to an arbitrarily-large set of coastal locations. We use the database for an analysis of cyclone strike locations and impact zones in seven historical periods: 1877-1900, 1901-1920, 1921-1940, 1941-1960, 1961-1980, 1981-2000 and 2001-2016. Although we believe that our results have independent interest, we highlight their implications for socioeconomic analysis of household and community responses to cyclonic storm risks. Episodic, short-run responses to some individual storms are well-documented. Such anecdotal evidence certainly provides many useful insights, but georeferenced panel data are required for systematic comparative research on coastal adaptation. In this context, robust assessment of causal factors requires significant variation in cyclone impacts, both across coastal areas and over time. The results of our seven-period analysis indicate that such variation characterizes the coastal zone. During each 20-year period, some areas have 20", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "georeferenced panel data"}]}}}
{"input": "rural areas** . Maternal mortality remains high (234 deaths for 100,000 births) with rural areas driving the trend [4] . According to the **Human Capital Review for Djibouti (World Bank, 2024)**, access to basic services such as targeted social safety nets, education and healthcare remains limited, with rural areas experiencing the most pronounced deprivations. The widespread poverty in these regions is characterized by poor living conditions, inadequate access to clean water and sanitation, and substandard infrastructure, and limitations on the freedom of movement for camp-based refugees. [5] While this situation is aggravated for refugees, who can face discrimination and challenges related to documentation, members of the host community also live in precarity. These factors contribute to a lower quality of life and hinder economic opportunities. 10. **The Dikhil region, an arid and resource-constrained area in southern Djibouti, faces a unique and multifaceted** **challenge of poverty that requires a comprehensive, integrated rural development approach.** The region not only hosts a significant migrant population, primarily from Ethiopia, but also grapples with chronic underdevelopment, reflected in high poverty rates, limited access to basic services (including water, sanitation, healthcare, and education), and high levels of unemployment. The continuous inflow of migrants places additional strain", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "in working conditions amongst Ukrainian Temporary Protection holders. Employment continued to be mentioned as one of the top two priority needs (32%) of households interviewed. Moreover, in terms of information, 29% of respondents indicated a need for more information about job opportunities; this continued to be the highest reported information need. 4 As per the 2024 Socio-Economic Insights Survey conducted by UNHCR, this figure could be as high as 79% amongst working-age Ukrainian refugees. The data was collected in the period 15 May-16 July. UNHCR / September 2024 4", "output": {"entities": {"named_data": [{"text": "2024 Socio-Economic Insights Survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "**Annex** **Table A1. Variable definitions** _Characteristics_ total children Total lifetime fertility wealth Household wealth index score non-migrant Respondent was born in the location and has never moved migrant Any respondent who has ever moved in their life urban The household lives in urban area _Woman’s occupation_ not working Was not working in last 12 months service & sales Works in services or sales professional Works as a professional agriculture Works in agriculture manual labor Works in manual labor earning cash Earns cash for work (0= not paid, in kind) works all year Works all year (0= seasonally, occasionally) _Woman’s education_ 3 years education At least 3 years of education no education No education _Child health_ first 12 months Child died within 12 months from birth diarrhea Child had diarrhea in last 2 weeks cough Child had cough in last 2 weeks fever Child had fever in last 2 weeks _Child anthropometrics_ ht/age (st dev.) Height for age (standard deviation) wt/age (st dev.) Weight for age (standard deviation) wh/ht (st dev.) Weight for height (standard deviation) 40", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "can make a large difference in the flood hazard particularly in well-protected areas. In these wellprotected areas, our flood maps may overestimate the flood hazard. This is a data limitation that affects many studies of flood exposure: even in high-income countries like the US, flood protection databases are incomplete and many areas are left undefended in national models when in reality they are defended (Wing et al. 2017). While recent work has tried to patch together a database of flood protection (Scussolini et al. 2016), the authors admit much remains unclear and this is a current state of the research. For most of the analyses, the Bcombined^ maps are used, which include both coastal and the fluvial/pluvial floods. For instance, the combined maps for the 25-year return period flood (under current conditions, and low, medium, and high future conditions) are presented in Fig. 1. Local Flood Hazard Maps for Ho Chi Minh City In addition to the flood hazard maps developed for this study as described above, we use an additional set of maps produced specifically for HCMC. 2 These uncertainties largely arise from climate models; global climate models (GCMs) struggle to represent the physical processes that produce extreme rainfall.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "flood protection databases"}, {"text": "flood hazard maps"}]}}}
{"input": "**Figure A2 Using GLSS: Employment and wages** **Panel A Woman working in services** **Panel B Log wages (woman)** **Panel C Man working in mining** **Panel D Log wages (man)** _Note:_ The four panels show the regression results from four spatial lag models using the GLSS sample. The sample is restricted to women (top two) and men (bottom two) aged 15–49. The solid lines are the coefficient for _active*mine_ for 7 distance bins (0–10 km, 10–20 km, ... 60–70 km) compared with a control group (80–100 km) away. The regressions also control for mine location at the same distances. See table 11 for control variables. 45", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "1% of occurring in any given year). As with all global flood maps, the effects of artificial flood protection structures like dikes are not incorporated. Two editions of the Fathom global flood maps are available; 2016 and 2019. Wherever available, the newer version has been used. The 2019 version differs from the 2016 version in the resolution of the digital elevation model that has been used to simulate event scenarios. The 2019 edition uses the newest DEM MERIT elevation model that corrects for multiple errors, including tree and building height adjustments. **Coastal flooding** is caused by storm surges and high tides in coastal areas. A commonly used global coastal flood risk map is used in this study: the Global Tide and Surge Reanalysis (GTSR) data set by Muis et al. 2016. As it uses a digital terrain model that does not account for common errors such as stripe noise and tree heights (unlike for instance DTM MERIT), this map is expected to provide a lower bound or conservative estimate of global coastal flood risk. In particular, resulting from coarse resolution in modeling elevation, bathymetry and meteorological forcing, the data set underestimates extreme sea levels. In addition, the largest tropical cyclone-induced", "output": {"entities": {"named_data": [{"text": "Fathom global flood maps"}, {"text": "Global Tide and Surge Reanalysis (GTSR)"}], "descriptive_data": [], "vague_data": [{"text": "global coastal flood risk map"}]}}}
{"input": "Our results for total Bank lending are uniformly significant at the 99% level, and the results for the OED ratings are significant at the 95% level or higher. The parameter estimates suggest that a 1% increase in Bank lending is associated with a .4% increase in environmental lending, and a 1% increase in the OED rating is associated with an environmental lending increase of about 1%. Once we control for these two factors, environmental problems retain a significant impact on environmental lending at the 99% level. However, the estimated response elasticity drops from .70 to around .45. The results for AAA in Figure 5.1 are quite different from the results for lending. The association with environmental problems is uniformly significant at the 99% confidence level, but we find no significance for environmental lending, non environmental lending, the OED success probability, or any regional dummies. R squares for the AAA regressions are much lower than R-squares for lending, suggesting a much greater random component in the allocation of AAA resources. **6. Allocation by Environmental Theme** From an institutional perspective, our overall results for lending are encouraging because they suggest that large, politically-difficult reallocations across countries would not generally be necessary to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) 47. **The economic analysis suggests that this Project would yield positive benefits that outweigh its costs, with a** **Net Present Value estimated at US$383 million.** The internal rate of return is 21 percent, with a 5 percent discount rate. The analysis estimates the Project’s economic impact by projecting the increased earning potential of graduating cohorts as they participate in the labor market. Upon evaluating the anticipated effect size of the Project’s components on academic performance, the analysis converted these gains to additional years of schooling, and subsequently to increased income. The graduating student cohorts were disaggregated to those who entered the workforce immediately upon finishing secondary school and those who pursued tertiary education to account for the variance in workforce participation and the years in which they would enter the workforce. The analysis aggregated the effect on income until 2039, when the last cohort who benefit from the Project would graduate from the compulsory education system in Costa Rica. Annex 2 presents the Economic and Financial Analysis for the Project. **Paris Alignment** 48. **Assessment and reduction of mitigation risks.** Project activities are expected to have negligible GHG contributions, and as", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**______________________________________________________________________________** **Table 4.1: Trend Tests for Thematic Shares** Climate Pollution Land Biodiversity [8] Water Policy Other Time 0.318 -0.167 0.639 0.074 0.008 -1.071 0.199 (0.63) (0.19) (1.38) (0.37) (0.01) (1.65) (1.09) Constant 8.337 33.404 8.529 2.215 20.456 24.930 2.128 (2.44)* (5.54)** (2.72)* (1.61) (5.86)** (5.67)** (1.71) Obs. 11 11 11 11 11 11 11 R-squared 0.04 0.00 0.17 0.01 0.00 0.23 0.12 Absolute values of t statistics in parentheses - significant at 5%; ** significant at 1% **______________________________________________________________________________** Produced by thousands of interactions between the Bank and its partner countries, these results suggest very strong continuity in the relative valuation of thematic objectives. We will return to this point in Section 7, which develops a model for the optimal allocation of environmental resource allocation by the Bank. **5. How Has Environment Mattered in the Aggregate?** We begin our assessment by analyzing the match between environmental lending, AAA and environmental problems at the country level. Our overall environmental indicator is the mean of the five thematic indicators. [9] We use log values for the analysis because the size distributions of country indicators and resource allocations are extremely 8 For biodiversity, our data include only Bank lending. Grants by the Global Environment", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "Bank lending"}]}}}
{"input": "**The World Bank** Uganda Development Response to Displacement Impacts Project Phase II (P510476) PROJECT APPRAISAL DOCUMENT include selected activities in the transit districts of Kisoro, Kanungu, Bundibugyo, and Ntoroko (Western Region) and Amuru and Lamwo (Northern Region). [14] The urban centers of Gulu, Mbarara, Arua, Koboko, and Kitgum will be included in some components. Geographic coverage can be expanded later if the government officially adds new RHDs or transit districts. Implementation will commence first in the 12 RHDs, where project structures from Phase I can be rapidly reestablished. Activities will commence in the transit districts and urban centers in year two, once needs assessments have been completed. DRDIP II’s largest footprint will be in the north, which has been most affected by the recent inflows. Planning and implementation will be informed by a clear understanding of the context of each district. 16. **Transit districts do not permanently host refugees, but field assessments have shown that population flows in** **those locations affect the delivery of basic services while asylum seekers wait to have their status assessed and be** **assigned to a host district.** Accordingly, project funds will be allocated to respond to the displacement impacts in the transit districts to expand", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "contain the marketing restricted sample, which is restricted only to villages where at least one person purchased insurance in the following year. All regressions contain state fixed effects. Errors are clustered at the weather-station level. ***p _<_ 0.01, **p _<_ 0.05, *p _<_ 0.1. _Source_ : Authors’ analysis based on data from BASIX. the year before. I then regress the number of each type of buyer on payout statistics and the total number of buyers in the previous year. When there was an insurance payout in the previous year, most of the repeat buyers received money from the insurance company while new buyers did not receive anything. [14] If there are similar effects of payouts on people who had not purchased insurance the year before, this would be evidence that insurance payouts are generating trust and/or learning about insurance. [15] These results are presented in table 7. In order to compare results with the main specification in table 3, I again provide a dummy for whether there was a payout in the village along with a quadratic effect of the ratio of payouts to the premium. When aggregating the village data, I use the mean of the payout ratios in", "output": {"entities": {"named_data": [{"text": "data from BASIX"}], "descriptive_data": [{"text": "BASIX"}], "vague_data": []}}}
{"input": "**The World Bank** Integrated Community Resilience Project (P506969) PROJECT APPRAISAL DOCUMENT incorporate climate risk awareness and opportunities, covering areas such as sustainable livestock practices, waterefficient grazing, hydroponics, and solar-powered solutions. 49. **In addition to IGAs, support will be provided to cooperatives, family businesses and individual entrepreneurs,** **including those with existing business activities and potential for growth** . These interventions will help beneficiaries scale their operations, improve productivity, and access markets. Beneficiaries, including refugees and host communities, will collaborate on IGAs or business ventures, utilizing peer learning, skills-sharing, and value-chain integration to expand market access. Priority for business support will be given to sectors that generate jobs, particularly those that leverage value chains and cross-border economic opportunities. The project will strengthen market linkages and value chain integration, helping beneficiaries connect with local, national, and regional markets. This approach will include training on business development, understanding value chains, accessing new markets, and procurement, which will increase the sustainability of their activities and expand their reach. Finally, the sub-component will provide ongoing mentorship and technical assistance to ensure business sustainability. Animateurs will work closely with beneficiaries to provide tailored support in managing and growing their businesses, helping them overcome challenges and build resilience", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "National Adaptation Plan (NAP) (2019)**, aiming to reduce vulnerability to climate change and to facilitate integration of adaptation into all levels of development planning including (i) access to water for all; ii) the promotion of best practices in the agricultural, forestry, fishery, and tourism sectors and reduced vulnerability to the effects of climate change and increase the resilience of the most exposed socioeconomic or geographical sectors; iii) the protection of ecosystems and ecosystem services; and iv) the resilience of key strategic infrastructure. The project will contribute to the objectives of the NAP with climate adaptation activities outlined in component 2 and financial inclusion under component 1. 20. **The Project is also fully aligned with the goals of the Paris Agreement** . The project is aligned with Djibouti’s commitment to combatting climate change as outlined in the 2023 revised Nationally Determined Contribution (NDC). The government prepared a draft version of a revised NDC outlining both mitigation and adaptation measures aligned 17 World Bank (2024), Climate Change Development Report 18 World Bank (2023), [World Development Report 2023: Migrants, Refugees and Societies](https://www.worldbank.org/en/events/2023/06/29/wdr2023) Page 6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Economics of Disasters and Climate Change Barrett A, McIntosh R, Pritchard M, Hannan M, Alam Z, Marks M (2013) Asset Values: Why Are Some Households Doing Better than Others? Chars Livelihood Program Ceola S, Laio F, Montanari A (2014) Satellite nighttime lights reveal increasing human exposure to floods [worldwide. Geophys Res Lett 41(20):7184–7190. https://doi.org/10.1002/2014GL061859](https://doi.org/10.1002/2014GL061859) Chinh DT, Dung NV, Gain AK, Kreibich H (2017) Flood loss models and risk analysis for private households in can Tho City. Vietnam Water 9:313 De Lay S (2011) Slums in Ho Chi Minh City, Vietnam. Global Cities 2011. [http://hochiminhcity2011.jimdo.](http://hochiminhcity2011.jimdo.com/slums/) [com/slums/](http://hochiminhcity2011.jimdo.com/slums/) Del Valle, Alejandro et al. (2018) The Short-Term Economic Impact of Tropical Cyclones: Satellite Evidence from Guangdong Province. Econ Dis Climate Chang 1–11 DHI (2003) MIKE 11 - A Modelling System for Rivers and Channels. Short Introduction Tutorial. Water and Environment Fay M (2005) The Urban Poor in Latin America. Directions in Development - General. The World Bank. [http://elibrary.worldbank.org/doi/book/10.1596/0-8213-6069-8](http://elibrary.worldbank.org/doi/book/10.1596/0-8213-6069-8) FIM (2013) Final Report, Volume 2, Integrated Flood Management Strategy. Ho Chi Minh City Flood and Inundation Management Geographic Information Science and Technology (2015) Landscan Population Data. Oak Ridge National Laboratory [GFDRR (2015) Country Profile - Vietnam. https://www.gfdrr.org/sites/gfdrr/files/region/VN.pdf](https://www.gfdrr.org/sites/gfdrr/files/region/VN.pdf) Goeschl T, Managi S (2017) Public in-kind relief", "output": {"entities": {"named_data": [{"text": "Landscan Population Data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "protection to respond to ecosystem** **degradation in the RHDs and additional impacts caused by climate change and refugee presence.** The expansion of farming by refugees and host communities is driving rapid deforestation in the RHDs, reducing the extent of natural forests and woodlands. Refugees and hosts also harvest wood for cooking, shelter, and fencing in excess of sustainable yields, causing additional degradation of tree cover and affecting fragile sites such as wetlands, hillsides, and riverine areas. In addition to the environmental impacts, this can be a source of tension between refugees and host community members. Climate change is exacerbating these challenges, as previously explained, with lower rainfall, longer and more frequent droughts, and more frequent extreme weather events. These factors are causing more crop failure, water scarcity and floods, droughts and landslides. The component will support 730,000 people (50 percent female/20 percent refugees) with enhanced resilience of terrestrial and aquatic systems, covering at least 11,200 hectares of land. 21 The AI Model was produced under the Enhancing Self-Reliance and Preparedness for Forced Displacement in the Great Lakes Region Advisory Services and Analytics (P500793). Data and analysis from the model, if rendered live, could also be used to support monitoring, evaluation,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "areas, our flood maps may over-estimate the flood hazard. When including climate change, this percentage increases by 13–27%, depending on the severity of sea level rise. This increase in exposure is due to the concentration of the population in coastal areas. For the 50-year flood, more than a third (38%) of today’s population is already exposed. Given climate change, this number is expected to increase by 7–21% (resulting in overall exposure of between 40 and 48%) for the same return period (50-year). For a 100- and 200-year flood under a high climate scenario, more than half of the population is exposed. Climate change impacts can be seen in these exposure numbers - for instance, a 50-year flood with medium climate change impacts has the same exposure of a 200-year historical flood (at 44%), while almost half the country’s population (48%) is exposed to a 50-year flood with high climate impacts. Full results are presented in Table 3. But these national results on exposure are not evenly be distributed across the country. The spatial analysis also allows us to examine which districts have the highest absolute and the highest relative exposure. We present results for the 25-year flood, for a historical", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "more difficult. According to UNHCR’s protection monitoring, over 54% of families have at least one child without a birth certificate, and 71% have family members without national identity cards. Displaced populations are often unable to access or have lost civil documentation and face challenges getting replacements for reasons connected to their displacement. Often legal assistance is needed to resolve the issue and access to justice is inhibited by the lack of identity documents. Without additional funding, 12,780 IDPs and IDP returnees won’t be able to access identity documents or legal assistance. UNHCR’s protection monitoring found that 91% of IDP households have at least one member with a vulnerability. Without additional funding, 3,170 extremely vulnerable people will go without urgent tailored support to those processing trauma and living with mental health issues, survivors of gender-based violence, elderly individuals often living alone, and people with disabilities. [For more information, please contact the UNHCR MENA Regional Ofce in Amman (Jordan) at: MENAreporting@unhcr.org](https://www.unhcr.org/) [www.unhcr.org](https://www.unhcr.org/) ~~6~~", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Note:_ This figure shows the mine locations and the district in which the mines are located. The baseline specification is shown in the following equation: Y��� - β�active_district�� - ∝�� g� �λX�� �ε��� �3� The outcome for individual _i_ in district _d_ in time period _t_ is regressed on district and year fixed effects, an indicator for whether the individual lived in an active mine district at the time of the interview, and time varying individual-level factors. Even though the treatment is defined at the district level, we use individual-level data to be able to control for individual- level factors and explore heterogeneity at the individual level. The standard errors are, however, clustered at the district level to take into account the interdependence induced by the higher-level treatment. Since the treatment variable is at the same level as our district fixed effects, the _β1_ coefficients are directly interpretable as difference-in-differences estimates. That is, they capture the difference between mining districts and nonmining districts before and after mining starts. In estimating the district-level effects of mine openings on birth outcomes, we control for birth year fixed effects instead of survey-year fixed effects, as we are interested in the effect of mining", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "individual-level data"}]}}}
{"input": "works with states to address the challenges of irregular and mixed movements at Europe’s borders through a comprehensive [route-based approach. This strategy focuses on](https://www.refworld.org/policy/strategy/unhcr/2024/en/148087) coordinated actions to protect refugees and migrants, uphold their rights and reduce dangerous journeys. It emphasizes cooperation among states, UN agencies and civil society to manage irregular movements and ensure responses align with international obligations. 2 Mediterranean Situation [Operational Data Portal](https://data.unhcr.org/en/situations/mediterranean) 3 8,500 arrivals to Italy; 6,900 to Greece; 6,500 arrivals to Spain (4,095 of whom arrived in the Canary Islands); and 216 to Cyprus. 4 As of 30 September 2024. Page 4 **U N H C R R E G I O N A L B U R E A U F O R E U R O P E,** O C T O B E R 2 0 2 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "vulnerable communities, including refugees and host communities. By linking safety nets with livelihood opportunities and broader socio-economic development, the project aims to foster resilience, inclusion, and sustainable economic growth in target areas. These include underserved regions such as Dikhil and refugee-hosting locations facing pressures from population inflows, strained public services, and climaterelated vulnerabilities. Additionally, the social protection support will be expanded across all regions to ensure broader coverage. **B. Theory of Change and PDO Indicators** 19 World Bank, 2025, Djibouti Climate Change Development Report (CCDR) 20 Project’s activities are exposed to identified climate risks (extreme heat, droughts, floods), but each activity financed under this operation will integrate climate-resilient design to reduce material risks to an acceptable level. Page 7", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "gain from having full ownership as compared to only occupancy rights on customary land is expected to amount to 3.5% for coffee, 16.3% for fruits, and 20.0% for banana with correspondingly larger gains of 9.3%, 31.9%, and 39.1%, respectively, on freehold or _mailo_ land. To interpret these figures, note that they are very conservative estimates as they completely neglect the value of soil fertility investment which can be very large according to recent studies valuing annual nutrient loss due to lack of soil conservation at 20% of average household income (Pender _et al._ 2004). Given that in addition we also exclude any credit-related investment incentives due to clear land ownership, the coefficients estimated here points towards substantial economic effects of overlapping property rights. **4.3 Options to increase tenure security** Our results thus far imply that, despite legal provisions aiming to strengthen property rights to land that is only occupied but not owned, significant and quantitatively large investment disincentives persist and cause productivity losses of considerable magnitude. This makes it important to explore other ways of bringing investment levels on such land closer to the social optimum. To explore this, our survey asked households who occupied land under usufruct about their", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "members’ labor supply to farm or off-farm activities, migration, income from different sources, and an account of agricultural output and inputs. We also have data on key village characteristics including total working age population, agricultural land, and distance to public health and education facilities to control for village level time-varying effects. With 9-13 villages per county and a sample size of 10 households per village, the pre-reform sample comprises a total of 310 and 470 households inside and outside Chengdu, respectively. [11] The post-reform sample similarly includes 280 and 390 households inside and outside the prefecture boundary. After dropping some 5% of sample households who neither engaged in productive activities nor participated in labor markets due to old age or disability, we end up with a sample of 285 pre- and 259 post-reform 9 The NBS sample is drawn from a fixed set of counties. We compare outcomes of NBS households in counties from both sides of the Chengdu prefecture border with three counties in Chengdu and four counties in Meishan and Ziyang. 10 We use the years of 2005 and 2006 for the pre-reform and of 2011 and 2012 for the post-reform period. To avoid contamination as land reform", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "data on key village characteristics"}]}}}
{"input": "resilience: learning from the ecological wisdom of living with floods in the Vietnamese Mekong Delta. Landsc Urban Plan 155:69–78 McElwee P et al (2017) Flood vulnerability among rural households in the red River Delta of Vietnam: implications for future climate change risk and adaptation. Nat Hazards 86(1):465–492 Ministry of Natural Resources and Environment (2009) Climate Change, Sea Level Rise Scenarios for Vietnam Patankar A (2015) The Exposure, Vulnerability and Adaptive Capacity of Households to Floods in Mumbai. World Bank Policy Research Working Paper No. 7481 PUMA (2013) Interim Report Version 1.0.^ Platform for Urban Management and Analysis (PUMA) Software Development and Satellite Imagery Processing Consultants Rozenberg J, Hallegatte S (2016). Modeling the impacts of climate change on future Vietnamese households: a micro-simulation approach Scussolini, P., Aerts, J. C., Jongman, B., Bouwer, L. M., Winsemius, H. C., de Moel, H., & Ward, P. J. (2016). FLOPROS: an evolving global database of flood protection standards. Nat Hazards Earth Syst Sci, 16(5), 1049–1061 Smith A, Freer J, Bates P, Sampson C (2014) Comparing ensemble projections of flooding against flood estimation by continuous simulation. J Hydrol 511:205–219 Thoai TQ et al (2018) Determinants of farmers’ adaptation to climate change in agricultural production in the", "output": {"entities": {"named_data": [{"text": "FLOPROS"}], "descriptive_data": [], "vague_data": []}}}
{"input": "provided protection, access to services, and inclusion into national systems. However, host governments and communities need support to guarantee access to rights and services, provide dedicated support for the most vulnerable, foster greater inclusion and ensure social cohesion. UNHCR leads the **[Regional Refugee Response Plan](https://data.unhcr.org/en/documents/details/105903)** (RRP) for the Ukraine Situation in these efforts along with more than 300 partners. In 2024, UNHCR aims to assist over **850,000 refugees with protection support** including information and counselling, targeted cash for protection and socio-economic activities, including livelihoods support. For more on UNHCR's 2024 plans and financial requirements for the Ukraine Situation, see **[here.](https://data.unhcr.org/en/documents/details/106081)** **UNHCR’S 2024 FINANCIAL REQUIREMENTS** **FOR UKRAINE SITUATION COUNTRIES** US$ million # 993.3 **TOTAL FUNDED (as of 30 Sept 2024)** % # 52 **COUNTRY** **TOTAL** **BUDGET** **(USD)** **TOTAL FUNDED** **(%)** Bulgaria **$17.0M** 71% Czech Republic **$11.9M** 44% Estonia **$4.2M** 50% Hungary **$14.2M** 60% Latvia **$4.2M** 50% Lithuania **$4.2M** 50% Poland **$85.0M** 38% Rep. of Moldova **$102.8M** 60% Romania **$54.3M** 45% Slovakia **$20.3M** 53% Ukraine **$598.9M** 52% [1 IOM DTM - Ukraine](https://dtm.iom.int/ukraine) Page 3 **U N H C R R E G I O N A L B U R E A U F O R E U R O P E,**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Some instances, such as when prescribed medications conflicted with known conditions, illustrated a disconnect between patient backgrounds and treatment approaches in the Czech healthcare system. This forced some refugees to rely on bringing medications from Ukraine, exacerbated by difficulties obtaining longterm prescriptions. Language barriers also hinder effective communication of health needs. Many focus group discussion respondents highlighted the need to rely on assistance during medical appointments. It was also observed that participants face uncertainty about obtaining disability certificates, with most participants unaware of the process. Notably, healthcare emerged as the fourth most important information need during protection monitoring. _2 UNHCR Focus Group Discussion with 10 Ukrainian refugee women 25-59 years of age in January 2024 in Prague._ _3 UNHCR Focus Group Discussions with 28 Ukrainian elderly refugees aged 60-79 (26 women, 2 men) in Prague and Plzen in March -_ _April 2024._ UNHCR / March 2024 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "of buyers 6,425 10,074 3,375 19,874 Total number of buyers (for whom insurance is available in following year) 5,579 5,418 NA 10,997 Total number of buyers (in villages where there was at least one buyer the following year) 2,462 1,739 NA 4,201 Number of buyers who repurchase in following year 453 364 NA 817 Buyers receiving payouts 351 1,346 529 2,226 Average Average sum insured (Rs) 3,055 1,612 3,547 2,738 Average payout (Rs) 11 60 88 53 Average payout (Rs, if payout _>_ 0) 195 360 553 370 _Notes_ : This table lists summary statistics for the individual sample. The sample only includes people who purchased rainfall insurance from BASIX in a given year. _Source_ : Authors’ analysis based on data from BASIX. For rainfall data, I use a historical daily grid of rainfall, which is interpolated based on readings from thousands of rainfall stations throughout India. The data are provided by the Asian Precipitation Highly 3 The states are, in descending order of number of buyers, Andhra Pradesh, Maharashtra, Jharkand, Karnataka, Madhya Pradesh, and Orissa. 4 Note that BASIX also sold many policies in the district of Deogarh in Jarkhand, and those buyers are omitted from this analysis. The", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "historical daily grid of rainfall"}, {"text": "data from BASIX"}], "vague_data": []}}}
{"input": "the OECD, a highly skilled workforce, and a transformative digitalization and management agenda. **Foundational Learning** 5. **National assessments show weakness in foundational learning, and learning outcomes are strongly correlated** **to socioeconomic conditions, which points to the need for foundational learning with deeper attention to the education** **outcomes of students from poorer families.** Costa Rica reactivated standardized national assessments in 2023; the first results from 2023 were released in March 2024 and indicated that about a third of the students at the end of Primary schooling are at the “basic” level of learning. Internationally comparable Programme for International Student Assessment (PISA) data for Costa Rica for 2018 shows that while 28 percent of children from families in the top quintile of the PISA index for economic, social and cultural status were below Level 2 on Reading in PISA (considered the minimum of adequate performance), 72 percent of children from families from the lowest quintile of the PISA index were below level 2. Foundational learning (literacy and numeracy) in early grades paves the way for future learning, and differences in educational attainment become magnified through youth and adult life in the acquisition of human capital. Without any claims regarding causation, it is", "output": {"entities": {"named_data": [{"text": "Internationally comparable Programme for International Student Assessment"}], "descriptive_data": [], "vague_data": [{"text": "PISA index for economic, social and cultural status"}]}}}
{"input": "**The World Bank** Uganda Development Response to Displacement Impacts Project Phase II (P510476) **I.** **STRATEGIC CONTEXT** PROJECT APPRAISAL DOCUMENT **A.** **Project Strategic Context** 1. **The Government of Uganda’s (GoU’s) progressive refugee response model has generated a development** **dividend for hosting districts, but they still face major development challenges and refugees are well short of achieving** **self-reliance.** Increasing refugee inflows continue to place a strain on host communities at a time of declining humanitarian aid. Since Phase I of the Development Response to Displacement Impacts Project (DRDIP) in the Horn of Africa was approved in May 2016, the refugee population in Uganda has increased markedly from 220,000 to over 1.8 million. [1] More inflows are expected given the ongoing instability in the region. Most refugees are hosted in rural communities that are struggling with poverty and unemployment, human capital and service delivery deficits, limited basic infrastructure, and a degraded natural resource base. Despite the opportunities and rights afforded them, refugees in Uganda lack employment opportunities and suffer from poverty rates almost three times higher than Ugandan nationals. Given the huge population, self-reliance of refugees and host communities is an important development priority for Uganda. As a regional and global example of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "MEP reforms are geared towards sustainability** . [22] An important consideration of the reform program is that the planned interventions do not require a level of investment that would put inordinate fiscal pressure regarding the MEP budget. Expenditures such as the investments planned for the digitalization agenda of the MEP are expected to be absorbed into the MEP budget at the end of the proposed Project. Efficiency enhancement under the reform would enable enhancement of the quality of service delivery as well as aid sustainability overall - an example is the reform of the functioning of local school councils, supported better by MEP through modernized information systems. These reforms would result in better maintenance of the physical plant and enhance sustainability of investments. **C. Relevance to Higher Level Objectives** 17. **This Project is aligned with High-Level Outcome 2 (Strengthened and Preserved Human Capital) of the World** **Bank Group’s Country Partnership Framework (CPF) for Costa Rica (FY24-FY28), discussed by the Board on April 30,** 22 [https://www.imf.org/en/News/Articles/2024/04/12/pr-24112-costa-rica-6th-review-of-eff-arrangement-and-3rd-review-of-rsf-arrangement](https://www.imf.org/en/News/Articles/2024/04/12/pr-24112-costa-rica-6th-review-of-eff-arrangement-and-3rd-review-of-rsf-arrangement) Page 6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "weather station level. ***p _<_ 0.01, **p _<_ 0.05, *p _<_ 0.1. _Source_ : Authors’ analysis based on data from BASIX and APHRODITE. Column 1 presents the baseline regression, which shows that villages that experienced a rainfall shock in 2004 actually had an average of 3.8 _fewer_ purchasers in 2005. One worry with this regression may be that because the insurance policies and rainfall patterns of each location are different, the definition of a 11 The APHRODITE weather data provides information about how many local weather stations contributed to a certain rainfall reading. Since some of the rainfall observations are likely to be more accurate than others, I weight them according to accuracy. If there are no rainfall stations contributing to the APHRODITE data in 2004 within a .75°×.75° grid around the desired BASIX weather station, the observation is given a weight of 1. If there is a least one weather station in this .75°×.75° grid, the observation is given a weight of 1.5. If there is a rainfall station within the .25°×.25°grid, the observation is given a weight of 2. The weighted results do not differ significantly from the unweighted results. 12 Note that while it is reasonable to", "output": {"entities": {"named_data": [{"text": "BASIX"}, {"text": "APHRODITE weather data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "The World Bank Economic Review 693 low rates of rainfall insurance uptake in Andhra Pradesh, India, Giné, Townsend, and Vickery (2008) suggest that “over time, lessons learned by insurance ‘early adopters’ will filter through to other households, generating higher penetration rates among poor households.” This paper seeks to understand how previous insurance payouts can affect future insurance purchasing decisions, and what mechanisms can explain this behavior. Using data on three years of insurance purchasers from the Indian microfinance institution BASIX, I find that customers who received an insurance payout are 9 to 22 percent more likely to repurchase in the following year than customers who did not receive any insurance payments. I show that this effect cannot be accounted for by neo-classical explanations, such as wealth effects, changing expectations about weather, or trust in the insurance company. Instead, I argue that it is caused by the behavioral effects of receiving an insurance payout. I test two main hypotheses as to why receiving payouts could increase insurance demand the following year. First, several studies have shown that weather shocks themselves could have an effect on insurance demand (Kunreuther, Sanderson, and Vetschera 1985; Eling, Pradhan, and Schmit 2014; Turner, Said, and Afzal", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "exposure and vulnerability towards natural hazards: the Disaster Risk Index. Natural Hazards and Earth System Science. Vol. 9, pp. 1149–1159, Rentschler, J, de Vries Robbé, S, Braese, J, Huy Nguyen, D, van Ledden, M, and Pozueta Mayo, B. 2020. Resilient Shores: Safeguarding Vietnam’s Coastal Development in the Face of Disaster Risks. Washington, DC: The World Bank. Smith, A., C. Sampson, P. Bates (2015) Regional flood frequency analysis at the global scale. Water Resources Research. Vol.51, 539–553 Smith, A., P. Bates, O. Wing, C. Sampson, N. Quinn, J. Neal (2019) New estimates of flood exposure in developing countries using high-resolution population data. Nature Communications Vol.10, pp. 1814 UNDRR (2017) Global Assessment Report 2017. Geneva: United Nations Office for Disaster Risk Reduction World Bank and Australian AID, 2014. “’Where Are We During Flooding?’ A Qualitative Assessment of Poverty and Social Impacts of Flooding in Selected Neighborhoods of HCMC.” Washington, DC. 26", "output": {"entities": {"named_data": [{"text": "Disaster Risk Index"}], "descriptive_data": [], "vague_data": [{"text": "high-resolution population data"}]}}}
{"input": "process. 60. **The Inspectorate of Government (IG) will remain engaged in implementation arrangements** at the national and local government level to strengthen transparency and accountability and to prevent and respond to corruption. **B. Results Monitoring, Evaluation, and Verification Arrangements** 61. **M&E System.** OPM will have overall responsibility for M&E, including the preparation of consolidated quarterly progress reports and an Annual Report to the World Bank. The PIST will have a dedicated M&E specialist responsible for collecting and collating data on project outputs and outcomes. Reporting templates will be reviewed for Phase II and included in an updated M&E section in the PIM. The existing Project MIS will continue to be utilized, including use of the Page 16", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "During pre-testing of the survey instrument [4], it was determined that some African farmers cultivated at least two plots of land. Subsequently, the survey data collected crop data, including production quantities, amount sold, and sale receipts from crops for the largest single plot of cultivated land (referred to hereafter as the main plot) and all others (referred to as the secondary plot). In the following analysis we therefore contend with two plots. In the first stage of the analysis, we estimated a probit model of whether to irrigate or not (Table 2). We relied on the 10880 plots (out of a total of 10933) for which we have complete information for the regression. The explanatory variables in the first stage included seasonal climate variables, various soils, and flow (millions of m [3] ). We included only the linear climate variables in the first stage. We tested the inclusion of quadratic climate variables but found the linear model to be more reliable. (Log pseudolikelihood = -2340.59 and r-squared 0.51 versus -2187.4434 and 0.54, respectively, for the quadratic probit model.) The Chow test for determining the null hypothesis that the estimated parameters are jointly the same is rejected (chi [2] (30) =", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "survey data collected crop data"}, {"text": "crop data, including production quantities, amount sold, and sale receipts from crops"}]}}}
{"input": "Phase II. A minimum of US$50 million under the sub-component will be allocated to economic infrastructure, such as roads, bridges, markets, and storage facilities to support income generation and deepen integration with economic opportunity activities under Component 3. Economic infrastructure will also include the construction, upgrading, and/or rehabilitation of TVET centers and secondary schools to address limited access to job skills training and low school transition rates. DRDIP II will strengthen the administrative capacity and protection role of the Department of Refugees (DoR) by financing a new office building in Kampala, and the rehabilitation or upgrading of Refugee Settlement Commandant offices will also be included in the menu of options. Based on experience from DRDIP Phase I, investments in socioeconomic infrastructure are expected to account for approximately 80 percent of the sub-component's financing, while 20 percent will finance equipment. 26. **Subproject budget ceiling.** Sixty percent of the budget will be allocated to Community Investment Fund (CIF) subprojects, with a budget ceiling of US$300,000, an increase of US$50,000 over Phase I. The remaining 40 percent will be for larger Strategic Investment Fund (SIF) subprojects, the budget for which will range from US$300,000-US$900,000, compared to US$250,000-US$600,00 under Phase I. [20] The budget", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "we would expect accelerated outmigration from newly-impacted communities and, perhaps, deceleration in communities where cyclone strikes have declined. These changes would reflect both damage from actual impacts and revised expectations about future impacts. In this context, robust tests of expectations formation have two requirements. The first is a georeferenced panel database of the type assembled for this exercise. The second is significant temporal and spatial variation in cyclone impacts, which enable them to serve as effective statistical controls in multivariate analyses of household and community changes over time. To determine whether our data meet the second requirement, we perform an intertemporal assessment using the seven previously-defined periods for 1877-2016. Within each period, we consider the full set of spatially-ordered coastline points numbered 0 (the southernmost coastal point of Odisha) to 11,327 (the southernmost coastal point of Bangladesh). We register each coastal landfall at the closest point of initial strike and compute distribution statistics for spatial order numbers. Figures 3 and 4 display our results for the landfalls of 178 cyclonic storms from 1877 to 2016. Figure 3 provides a geographical perspective by mapping median landfall points for each period. Two conclusions are immediately clear. First, the locus of cyclone landfalls", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "georeferenced panel database"}], "vague_data": [{"text": "georeferenced panel database"}]}}}
{"input": "or extension process. In line with previous reports, the main challenges related to applying for Temporary Protection were long waiting times to receive a decision (44%), a lack of required documents (such as ID or proof of address) to complete the registration process (40%), and, despite its overall decrease in prevalence, a lack of interpretation (20%). Awareness of the process continues to be relatively high with only 16% of respondents reporting lack of information on the registration or extension of their status. **Access to documentation:** With respect to identity documents, 24% of respondents reported at least one household member not having documentation or holding expired documents. The main type of missing document was an international passport (88%) and the most common reason for the inability to renew or replace the missing or expired document was the unavailability of service (70%). 47% of households with missing documents indicated being impacted by this, most often by not being able to move freely or to access basic services. #### Protection Risk II **Access to adequate housing:** As for Q3 findings from Protection Monitoring interviews highlighted accommodation as the highest priority need for respondents (147 respondents, 34%). ## 34% reported accommodation as their highest", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "participation, few disputes, and at reasonable cost. Coverage was almost complete, allowing issuance of long-term or permanent contracts for most of the land. **3.1 Descriptive statistics** Table 1 reports descriptive statistics on household characteristics, welfare, agricultural production, and time use for the pre- and post-reform periods inside and outside Chengdu (col. 1-4), estimated pre-reform trends (cols. 5 and 6), and a test of the significance of differences in such trends between households inside and outside the Chengdu border. We note that households in the treatment and control are comparable with respect to basic characteristics: they comprise 3-4adults, had a head born in the late 1950s, education between junior high and high school, some 8% of female heads. At the same time, three sets of differences emerge. First, households in Chengdu had higher levels of assets, income, and consumption (Y16,063 and Y40,025, Y4,928 and Y8,549, and Y3,150 and Y6,078 in pre- and post-reform periods, respectively) than those outside (Y11,564 and Y29,752, Y3,770 and Y8,069, and Y2,668 and Y4,997). They also allocated labor differently across sectors, presumably due to proximity to urban income earning opportunities: with a time commitment of 43% and 50% in 2005/06, farming was the most important activity for", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "traditional _mailo_ areas as well. The 1998 Land Act includes far-reaching steps to increase tenure security for occupants who had only use rights, customary land users, and women. Regarding the latter, the Land Act provides for formal recognition of customary land ownership and establishes procedures for customary owners to obtain a “certificate of customary ownership” that can be transferred through sale, rent, gift, or mortgage, and converted into freehold titles in an administrative process. It also aims to significantly strengthen women’s land rights. However, effectiveness of these progressive features, many of which are effective without any formal process or survey, is hampered by flaws in the institutional designs for implementation (Hunt 2004). As a consequence, almost a decade after the Act’s passage, hardly any implementation has happened, despite considerable grassroots demand (Rugadya _et al._ 2004). Inability to resist political demands for reinstating _mailo_ as a separate land ownership category or to abandoni _kibanjas_ outside of _mailo_ areas precluded award of full ownership to tenants, thus leaving overlapping land ownership structures intact. At the same time, attempts were made to attenuate disincentive effects from overlapping rights by granting far-reaching protection to tenants. _Bona fide_ occupants, defined as those who had peacefully", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "of the Table 2 Hazard map scenarios for which the modeling was conducted for Vietnam Scenario Coastal Fluvial/Pluvial 1 in 25 1 in 25 1 in 25 1 in 25 Future – Low 1 in 25 + 28 cm 1 in 50 1 in 25 Future – Medium 1 in 25 + 6 cm 1 in 75 1 in 25 Future – High 1 in 25 + 98 cm 1 in 100 1 in 50 1 in 50 1 in 50 1 in 50 Future – Low 1 in 50 + 28 cm 1 in 75 1 in 50 Future – Medium 1 in 50 + 6 cm 1 in 100 1 in 50 Future – High 1 in 50 + 98 cm 1 in 200 1 in 100 1 in 100 1 in 100 1 in 100 Future – Low 1 in 100 + 28 cm 1 in 200 1 in 100 Future – Medium 1 in 100 + 6 cm 1 in 250 1 in 100 Future – High 1 in 100 + 98 cm 1 in 500 1 in 200 1 in 200 1 in 200 1 in 200 Future – Low 1 in 200 + 28", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "100 90 80 70 60 50 40 30 20 10 0 0 20 40 60 80 100 120 **Share of population with flood exposure (percent)** _Figure 22. Scatterplot of share of population exposed by income (2011 PPP USD/day)_ **5.5.** **From global aggregates towards local flood risk assessments** The results in previous subsections that are presented at the subnational, national, regional and global scales are aggregates of flood exposure maps that were generated as part of this study for all countries. These exposure maps with higher spatial resolutions have been retained and can be used to derive more granular insights at the local level. [2] For illustration, Figure 23 shows the population flood exposure estimates for Vietnam in an aggregate form at the national and subnational scales, as well as in its high-resolution raster format for example areas. The raster displays the number of people exposed to flood risk of each 90m x 90m pixel. The map shows a high concentration of flood-exposed populations in Hanoi, as well as urbanized areas along the Red River. The granularity offered by these pre-processed population exposure maps could be valuable for various applications; e.g. for the development of disaster mitigation plans prior to a", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "flood exposure maps"}, {"text": "population flood exposure estimates"}, {"text": "population exposure maps"}], "vague_data": []}}}
{"input": "rapid coastal urbanization, and climate change are bound to result in increasing exposure of people and their livelihoods. In this study we estimate the number of people who are directly exposed to the risk of intense flooding in 189 countries. We do so by using high-resolution flood and population data that enable a global yet detailed analysis of flood risks. We find that 2.2 billion people, or 29 percent of the world population live in areas that would experience some level of inundation during a 1-in-100 year flood event. About 1.47 billion people, or 19 percent of the world population, are directly exposed to inundation depths of over 0.15 meter, which would pose significant risk to lives, especially of vulnerable population groups. While the largest number of exposed people live in East and South Asia (1.36 billion people), subnational poverty estimates highlight another regional hotspot of risk: At least 71 million people in Sub-Saharan Africa are estimated to live in both extreme poverty (using a $1.9 a day definition) and significant flood risk – thus making them particularly vulnerable to prolonged adverse impacts on livelihoods and well-being. The remainder of this study is structured as follows. Section 2 offers an", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "high-resolution flood and population data"}], "vague_data": []}}}
{"input": "average historical payout, the total number of historical payouts, and the standard deviation of rainfall. Historical variables are calculated for the period 1962-2004. Observations are weighted by the quality of rainfall data. If there are no rainfall stations contributing to the APHRODITE data in 2004 within a .75°x.75° grid around the desired BASIX weather station, the observation is given a weight of 1. If there is a least one weather station in this .75°x.75°, the observation is given a weight of 1.5. If there is a rainfall station within the .25°x.25° grid, the observation is given a weight of 2. The weighted results to not differ significantly from the unweighted results. The number of observations is 733 out of a total of 949 villages in the sample in 2005, as APHRODITE data was available for only a subset of locations. All specifications include state fixed effects. Errors clustered at the weather station level. ***p _<_ 0.01, **p _<_ 0.05, *p _<_ 0.1. _Source_ : Authors’ analysis based on data from BASIX and APHRODITE. Column 1 presents the baseline regression, which shows that villages that experienced a rainfall shock in 2004 actually had an average of 3.8 _fewer_ purchasers in 2005.", "output": {"entities": {"named_data": [{"text": "APHRODITE data"}], "descriptive_data": [{"text": "data from BASIX and APHRODITE"}], "vague_data": [{"text": "quality of rainfall data"}]}}}
{"input": "or _gold_period_district_, which equals total production for the years before the survey. For the 1993 survey, the period is 1990–93, for 1998 it is 1994–98, and so on. Using production levels instead of an indicator of having any production in the district has the advantage of capturing the intensity of mining production. Since it is somewhat unclear when mining production spills over to other types of employment, we use two measures of mining production. Panel A of table 13 shows the results of mining production in the period before the survey, including the survey year, on female employment, and we see that mining production leads to less agricultural employment but more employment in services and sales, as well as in professional work. Panel B shows that the effects are larger but not as precisely estimated for the yearly measure. That they are larger is not surprising, since a 10-ton increase one year is much more than a 10-ton increase over a longer time period. The precision is also probably lower since it is unclear what year the production spills over to other activities. In any case, we see that the effects are similar across these two specifications. [18] 18 The", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "old age was available (Ong 2014). Failure to capture the gains in land value from changing from rural to urban land use in a more sustainable way also undermines local governments’ ability to provide social services. A tax on land or capital gains could help to do so but can only be implemented if institutional preconditions are met, in particular if a proper cadastral database is in place (Nitikin _et al._ 2012). This suggests that viable reforms would need to pursue a multi-pronged approach, including (i) registration of all rural land; (ii) a possibility for migrants to get an urban _hukou_ that provides access to social services, especially if they give up part or all of their rural land rights; (iii) allowing rural collectives or individuals to enter into direct land transactions at freely negotiated prices, subject to compliance with planning standards; and (iv) taxation of land so as to generate the revenue to support urban welfare packages while also contributing to more efficient land use (Tao and Xu 2007). Several experiments were undertaken to explore available options. These include integration of construction and collective land markets in Shenzen, land security development in Chongqing, urban fringe redevelopment in Beijing, land", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "proper cadastral database"}], "vague_data": []}}}
{"input": "experience into composite strike intensities for 1877 2016. Over 140 years, the highest-intensity zones have been in West Bengal and northern Odisha, with a relatively clear pattern of incremental intensity decline in both directions. **5.4 Mean Maximum Wind Speed** Assessing the significance of a cyclone strike requires information about the storm’s power, which is measured by maximum wind speed in our database. Figure 6 shows that mean maximum wind speeds are generally highest in sections of the mid-coastal region during 1877-1900 and 1901-1920. Conditions vary considerably during the next three periods. During 1921-1940, higher wind speeds appear in Odisha, the mid-coastal region and Bangladesh’s eastern coast. Wind speeds generally decline in 1941-1960, with notable cyclone-free areas in southern Odisha, the central coastal region, and eastern Bangladesh. Conditions reverse during 14", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "should direct short- and long-term assistance to both the displaced and host communities. This can help reduce real and perceived inequalities and prevent host communities from forming negative attitudes about newly arriving displaced persons. Phase II of Jya Mbere continues the area-based approach of Phase I, providing multi-sectoral support to respond to the impacts of forced displacement, covering refugees and host communities. The mid-term survey for Phase I indicated positive results from this approach for social relations between refugees and local residents, mirroring results from independent impact evaluations of the Development Response to Displacement Impacts Project (DRDIP) in Ethiopia (P152822) and Kenya (P161067). 47. **By creating new challenges and new opportunities, the presence of refugees transforms the environment** **in which host communities are pursuing their own development efforts.** This requires an approach that supports hosting areas rather than focusing on refugees alone. Investments are needed to mitigate the downside of hosting refugees – overcrowded basic services, environmental degradation, competition over natural resources and, sometimes, over employment opportunities – while taking advantage of the benefits their presence may generate through their human capital, financial resources and the humanitarian and development assistance they can Page 13", "output": {"entities": {"named_data": [{"text": "Development Response to Displacement Impacts Project (DRDIP)"}], "descriptive_data": [], "vague_data": []}}}
{"input": "place for the proposed project implementation). 51. **The PIU to be established at the MEP is expected to undertake the FM aspects of the proposed Project.** These encompass the following main tasks: (i) budget formulation and monitoring; (ii) cash flow management (including processing payments and submitting loan withdrawal applications to the Bank); (iii) maintenance of accounting records, including an inventory of fixed assets for the Project, (iv) administration of adequate information systems; (v) preparation of in-year and year-end financial reports; and (vi) contracting the external audit. The FM arrangements for the project will rely on country systems for budgeting, accounting and treasury, which are considered adequate [30] will be used as the project’s FM arrangements. Loan proceeds will be disbursed to an account in the Central Bank of Costa Rica named General Fund. Unaudited semi-annual financial statements will be submitted 45 days after the end of each calendar semester. Annual financial statements which will be audited under terms of reference and by an external firm, both acceptable to the World Bank, will be produced for the project. Basic arrangements to ensure control, recording, and reporting are further described in Annex 1. 52. **Procurement** . Procurement for the Project will be", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "take-up the following year. There is some evidence for this happening in developed markets; for example, Kunreuther, Sanderson, and Vetschera (1985) note that purchases of flood and earthquake insurance in the United States spike after a recent event, even if people were not insurance customers before. There are a number of theories that could explain this behavior. First, recent experiences with rainfall could change subjects’ beliefs about the probability of a rainfall shock the following year (this is proposed as “recency bias”in Karlan et al. [2014]). If there is actual autocorrelation of rainfall events or if the subject has limited knowledge about the effects of rainfall shocks, people may update their beliefs about shocks and therefore have more desire for insurance the following year. Alternatively, recently experiencing a rainfall shock could make shocks more salient, increasing the chance they will buy insurance the following year. Also, rainfall shocks may affect the wealth of the farmers. If farmers become poorer because of bad rainfall, CRRA utility would suggest that they would be even more risk averse the next year as a second shock would cause greater disutility. I start by examining whether there is actual autocorrelation in the rainfall data. To", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "rainfall data"}]}}}
{"input": "will include enhancing its operational framework, providing staff training on risk management and financial advisory services, and equipping CPEC with digital tools, building on multi-year technical assistance from the World Bank and other donors, to leverage CPECs proven capabilities and streamline advisory services to the C4N beneficiaries as well as those that will benefit from the FISs. **Sub-component 1.3: Strengthening the Social Registry (total IDA US$2 Million equivalent, including WHR US$0.3** **Million)** 38. **This sub-component will finance the scale-up of the SR among all Djiboutians, refugees and host communities,** **toward full coverage which will be a critical foundation for coordinating support across ministries and development** **partners.** The social registry will play a crucial role in coordinating existing funding and mobilizing additional resources to 22 Malaeb, B.; Duplantier, A., Maarraoui, G., Fluet, E. (2023). Towards a More Equitable Development: Constraints and Opportunities of Women in Djibouti. The World Bank, Washington Page 11", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "and concludes the paper. **2. Georeferenced Database Construction** We combine data from BMD, IMD and IBTrACS to document all recorded cyclonic storms in the Indian Ocean region from 1877 to 2016. We construct a panel database; the component for each storm includes a unique identification number; year and month of occurrence [1] ; maximum wind speed (kt); radial distance (km) from storm center to zone of maximum wind speed; IMD storm classification derived from wind speed; time indices for successive observation points [2] ; and latitude/longitude for each point. We use ArcGIS to construct individual storm-track polylines by interpolation from time indexed latitude/longitude observations for each storm. Then we determine maximum-impact 1 The first month for storms that occur in two months. 2 Incommensurate day/time tracking in the three databases (BMD, IMD, IBTrACS) could be addressed in a more complete exercise. For our purposes, identifying successive observations by cardinal units [1,2,3, ...] is sufficient for constructing GIS polylines that trace individual storm tracks. 4", "output": {"entities": {"named_data": [{"text": "IBTrACS"}], "descriptive_data": [{"text": "IMD"}, {"text": "BMD"}], "vague_data": []}}}
{"input": "have a stronger focus on all households’ members, rather than focusing only on women and young children. In addition, they provide more detailed information on labor market participation, such as exact profession (where, for example, being a miner is a possible outcome), hours worked, and a wage indicator. The data estimate household expenditure and household income. Wages, income, and expenditure can, however, be difficult to measure in economies where nonmonetary compensation for labor and subsistence farming are common practices. **4 Empirical Strategies** **4.1 Individual-level difference-in-differences** Time-varying data on production and repeated survey data allow us to use a difference-in differences approach. [7] However, due to the spatial nature of our data and the fact that some mines are spatially clustered, we use a strategy developed by Benshaul-Tolonen (2018). The difference-in-difference model compares the treatment group (close to mines) before and after the mine opening, while removing the change that happens in the control group (far away from mines) over time under the assumption that such changes reflect underlying temporal variation common to both treatment and control areas. We limit the data to include households within 100 km of a mine location and estimate the following: _Yivt = β0 + β1", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "repeated survey data"}]}}}
{"input": "use, a shift in crop composition towards higher-value crops, and more active rental markets to transfer land from less to more productive users. This suggests removal of earlier threats of expropriation encouraged more effective use of highly productive peri-urban land to intensify agricultural production and, by doing so, increased job opportunities and resulted in changes of labor supply. Young individuals shifted from migration to agricultural activities while the old shifted from farming to off-farm activities. The paper is structured as follows. Section two provides context, discusses some of the salient features of the Chengdu experiment, and introduces analytical methodology and data sources. Section three presents descriptive statistics from the household survey as well the nature and cost of the land certification process in Chengdu. Section four discusses impacts on household welfare, individual labor supply, and agricultural productivity and crop composition. Section five concludes with implications for policy and future research. **2. Motivation and background** Between 2000 and 2010, rural-urban land conversion in China expanded at rates that are among the highest in East Asia. As such changes are not easily reversed, this poses vast challenges for China’s development for decades to come. While piecemeal efforts to change this pattern had", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "household survey"}], "vague_data": [{"text": "household survey"}]}}}
{"input": "households inside Chengdu and 453 and 382 households in neighboring counties (Meishan and Ziyang) in the pre-and post-reform sample, respectively. Using a triple-difference approach, reform effects are identified based on difference between (i) years one and two within the same household; (ii) pre- and post-reform periods; and (iii) treated and non-treated households. The basic equation of interest can be written as ���� ��������� ���������� ������� ���������� ����������� ��������������� ������� ������� ��� �����(1) where _Yijt_ is the outcome of interest for household _I_ in village _j_ in year _t_ ; [12] _Xijt_ is a vector of time-varying household characteristics including the number of children, adults and old people, highest education, the head’s gender and age, and the amount from pension and medical schemes as well as crop subsidies received; _Vijt_ is a vector of time-varying village characteristics including total working age population, land area used for agriculture, distances to educational, health, and administrative institutions; _δij_ is a household fixed effect, _εijt_ is an error term; _Rijt_ is a binary indicator taking a value of 1 if the observation is post-reform (2011/12) and 0 otherwise; _Cij_ is an indicator that is 1 for households within Chengdu prefecture and 0 otherwise; _Tijt_ is", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "communities close to mines that have not started producing, evidenced by the fact that infant mortality is 8 percent compared to 7 percent farther away, and 6 percent in communities with active mines. The anthropometrics height-for-age (stunting or chronic malnutrition), weight-for-age (wasting or acute malnutrition), and weight-for-height (underweight) show that the children living in mining communities before the mine started operating have the lowest scores of all four groups. The outcomes seem to improve with mining, although not enough to offset the initial adverse situation. To test for exogeneity, we run regressions using baseline individual-level data to explore changes in observable characteristics among women (the main part of the sample). Table 3 shows that there are no significant effects of the mine opening on the age structure, migration history, marital status, fertility, or education, using the difference-in-difference specification with a full set of controls. If anything, it seems that women in active mining communities are marginally older, more likely to never have moved, and more likely to be or have been in a cohabiting relationship or married. Given the women’s slightly higher age, it is not surprising to find that they have higher fertility and lower schooling (assuming that schooling", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "baseline individual-level data"}]}}}
{"input": "on industrial transformation and value-chain production. In 2023, the GRZ launched its National Adaptation Plan (NAP), a long-term strategic plan formulated to address identified risks and vulnerabilities in various sectors to enhance Zambia’s resilience to the impacts of climate change. **B. Sectoral and Institutional Context** 6. **Zambia has a long history of hosting refugees lasting over six decades.** Between 1985 and 2007, the country hosted more than 100,000 refugees and asylum seekers. The largest portion fled to Zambia from Angola during the longrunning civil war that occurred after the country’s achievement of independence in 1975. Other significant refugee populations have arrived following the civil conflicts in the Democratic Republic of Congo, Rwanda, and Burundi. Following the end of Angola’s 27-year civil war in 2002, more than 74,000 Angolan refugees returned home under a voluntary repatriation program that concluded in 2007. 7. **There are currently approximately** **101,837 refugees, asylum seekers, and former refugees in Zambia.** **[10]** The majority of refugees and asylum seekers originate from the Democratic Republic of Congo; other significant refugee populations are from Burundi, Somalia, Angola, and Rwanda. Zambia continues to receive new arrivals of refugees and asylum seekers—approximately 600–800 refugees arrive each month from the South Kivu,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Integrated Community Resilience Project (P506969) PROJECT APPRAISAL DOCUMENT enhance Djibouti’s responsiveness to shocks, such as economic crises and natural disasters. To achieve this, the project will expand interoperability between the social registry and other essential databases, including civil registries and public health systems, thereby improving the accuracy and efficiency of targeting vulnerable households while reducing errors of exclusion and inclusion. Based on the piloting undertaken under the PITCH and the Social Protection Emergency Crisis Response Project, inclusion of refugees will be enhanced with the objective of enrolling more refugees, facilitating their access to services. The MASS in collaboration with ANSIE are undertaking a comprehensive audit of the SR that will result into a comprehensive plan for revising its operational manual, a plan of action of which will inform key stakeholders. This initiative will also support better coordination with United Nations humanitarian agencies and development partners, ensuring that refugee populations are better documented and ascertained so that they can benefit from a wider range of integrated services. Interoperability with other databases will also enhance responsiveness in the event of a natural disaster. 39. **In addition to reinforcing the social registry, the sub-component will support enhancing the operational capacity**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "the social registry"}, {"text": "civil registries"}]}}}
{"input": "## Background ## OBJECTIVES Study a select number of protracted refugee populations in Tanzania, Uganda, Rwanda and DRC and assess their risk of statelessness arising from prolonged exile. Develop recommendations for local integration pathways that mitigate risks of statelessness and ensure the realization of the right to a nationality, including access to legal identity documentation, in support of durable solutions. Inform the development of a comprehensive durable solutions strategy for forcibly displaced persons, including refugees in the Great Lakes region. The Great Lakes sub-region is characterized by a number of protracted refugee situations. In some situations, several generations of refugees have been born in exile in their country of asylum. Statelessness canaarise as both a cause and consequence of displacement, particularly for forcibly displaced populations who have spent a prolonged time in exile. In some instances, refugees have lost their ties with their country of origin, are unable to prove their legal ties to their country of origin, or might no longer be considered citizens by their country of origin, and remain without guaranteed access to the citizenship of their country of asylum and thus might be at risk of statelessness. In the spirit of the 2019 Munyonyo Outcome Document", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Conversely, NGOs, the media and Israeli officials have held Israel accountable to the high standards of its international commitments. Thus, in parallel to employing harsh deterrence measures, Israel has also offered limited and differing degrees of protection. Over time, the government has issued a few thousand work permits to Sudanese and Eritreans, exercising a degree of tolerance and recognition of their needs, although these were exceptional permits that had to be renewed. But the majority of asylum seekers have not received such permits and have been forced to work illegally to survive. Such uneven, contradictory action exempts the state from declaring its allegiance either to deterrence or tolerance. 7UNHCR made the initial identification and interview of the asylum seeker. On the basis this process, a recommendation was given to the National Status Granting Body (NSGB), an inter-ministerial committee responsible for considering UNHCR recommendations. The final decision was taken by the MOI. 5", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "percent of students from lower secondary to short-cycle tertiary enroll in vocational education and training, compared to 32 percent 9 [https://thedocs.worldbank.org/en/doc/64e578cbeaa522631f08f0cafba8960e-0140062023/related/HCI-AM23-CRI.pdf](https://thedocs.worldbank.org/en/doc/64e578cbeaa522631f08f0cafba8960e-0140062023/related/HCI-AM23-CRI.pdf) 10 OECD Education at A Glance, 2023, Table A4.2. The correlation (not causation) between socio-economic conditions, academic achievement and labor market outcomes is a global phenomenon. For the OECD countries as a whole in 2018, the percentage of below Level 2 performers from the top quintile of the PISA index for economic, social and cultural status, was 8%; while for the bottom quintile, the figure was 49%. For the labor market figures quoted in the text, 30% of 25-64 year olds for the OECD countries correspond to the 32% mentioned in the text for Costa Rica. [11 Encuesta de expectativas de empleo, Q1 2024, ManpowerGroup: https://go.manpowergroupcca.com/meos-cr.](https://go.manpowergroupcca.com/meos-cr) 12 OECD Economic Surveys - Costa Rica, February 2023. Page 2", "output": {"entities": {"named_data": [{"text": "Encuesta de expectativas de empleo"}, {"text": "PISA index for economic, social and cultural status"}, {"text": "PISA index"}], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Uganda Development Response to Displacement Impacts Project Phase II (P510476) PROJECT APPRAISAL DOCUMENT interventions on anti-corruption and accountability, which will continue to play (as in DRDIP I) an important role in mitigating political and governance risks. 94. **Institutional capacity for implementation and sustainability (Substantial).** OPM implemented DRDIP I to a high standard, but the long gap between the closure of Phase I and commencement of Phase II means many project staff have moved on to new positions. The main project delivery mechanism is CDD, which means communities lead on planning, subproject identification, procurement, and FM. While this approach has proven effective, it requires extensive technical support to succeed. The success of the project also depends on intensive coordination across line agencies, districts, and humanitarian agencies, adding to complexity. The World Bank will provide hand-on support to the government teams on core project management functions, such as FM, procurement, and E&S management. At the community level, the project will contract partner organizations to build local implementation capacity. 95. **Fiduciary (Substantial).** The FM risk is Substantial and the procurement risk is Moderate. The major risks are delays in disbursing to communities and making payments as well as accounting for", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "policies, including a large-scale governmental deportation campaign targeted at authorised workers who overstayed their visas and became unauthorised (Willen 2007). The third transformation is the ongoing influx of African migrants. Against this backdrop, the 2006 refugee influx met heightened anxiety over the transforming ethnonational character of the Israeli nation-state. The idea that mass influx involves demographic change has deep roots and was tactically used by Jews themselves prior to establishment of the state and during the British mandate (Neuman 1999). This language was engaged again, intensified by these changing patterns of migration and the ongoing focus on state security, to represent asylum seekers as a serious threat to both social cohesiveness and security - conveyed through the transportable, easy-to-use refugee template. Politicians and public officials further inflamed the debate by releasing controversial statements. PM Netanyahu employed rejectionist rhetoric: ―infiltrators cause cultural, social and economic damage, and pull us towards the Third World‖ and, in a slip of tongue, he later referred to the infiltrators as ―surge of refugees who threaten to wash away our achievements and damage our existence as a Jewish democratic state‖ (Goldstein 2010). The head of the SCPFW has called for a stop to the ―illegal infiltration‖", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "##### **Introduction** Coastal wetlands, which are comprised of marshes, swamps, mangroves and other coastal plant communities, provide a large number of goods and services that contribute to the economic welfare of the local and global communities (Millennium Ecosystem Assessment, 2005). [4] Examples of ecosystem services include the protection of shorelines from erosion, storm buffering, sediment retention, water quality maintenance, nutrient recycling, preservation of biodiversity, provision of natural environmental amenities, climate regulation, carbon sequestration, as well as cultural heritage and spiritual benefits (Larson et al., 1989; Barbier, 1991; Williams, 1990; Barbier et al., 1997; Brouwer et al., 1999; Woodward and Wui, 2001; McLeod et al., 2005; Brander et al., 2006). However, coastal wetlands are declining rapidly. Recent estimates indicate that approximately 1% of the global coastal wetland stock was lost each year in the late 20 [th] century (Nicholls, 2004; Hoozemans et al., 1993). The causes of wetland loss are numerous and often complex. [5] The rapid loss of the global coastal wetland stock in the 20 [th] century was primarily caused by direct land reclamation. While significant losses due to human actions are likely to continue in the future, it is projected that stresses on wetland areas may be further", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Ukraine Emergency](https://www.unhcr.org/emergencies/ukraine-emergency) webpage **Operational data portals:** - [Ukraine Refugee Situation](https://data.unhcr.org/en/situations/ukraine) - [Europe Sea Arrivals](https://data.unhcr.org/en/situations/europe-sea-arrivals) webpage **Contact:** UNHCR Regional Bureau for Europe [rbeext@unhcr.org](mailto:rbeext%40unhcr.org?subject=) **[Join our mailing list](https://manage.kmail-lists.com/subscriptions/subscribe?a=VYAYG5&g=QZGRtb)** www.unhcr.org/europe Page 7 **U N H C R R E G I O N A L B U R E A U F O R E U R O P E,** O C T O B E R 2 0 2 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "robust results for Africa. This assumption in turn implies that the next three months would be spring, the three months after that would be summer, and August, September and October would be fall (in the north). These seasonal definitions were chosen because they provided the best fit with the data and reflected the mid-point for key rainy seasons in the sample. We adjusted for the fact that seasons in the southern and northern hemispheres occur at exactly the opposite months of the year. Soil data was obtained from FAO (2003). The FAO data provides information about the major and minor soils in each location. Data concerning the hydrology was predicted from a hydrological model for Africa (Strzepek & McCluskey 2006). The model calculated the water flow through each district in the surveyed countries. Data on elevation at the centroid of each district was obtained through GIS manipulation using data from the United States Geological Survey (USGS, 2004). The USGS data are derived from a global digital elevation model with a horizontal grid spacing of 30 arc seconds (approximately one kilometer). 7", "output": {"entities": {"named_data": [{"text": "data from the United States Geological Survey"}], "descriptive_data": [], "vague_data": [{"text": "FAO data"}, {"text": "USGS data"}]}}}
{"input": "of 510 million square kilometers, which implies the processing of 63 billion pixels. **3.** **Assign flood risk categories to population headcounts at the pixel level and aggregate to the** **administrative unit:** As the flood hazard and population density maps are converted into the same spatial resolution, each population map cell can be assigned a unique flood risk classification – these cells can then be aggregated to the administrative unit level (e.g. province or district level). This allows the calculation of population headcounts for each flood risk category and for each (sub-)national administrative unit. A detailed description of how this process is implemented in practice is provided in Section 4.2. This process yields an estimate of the number and share of people exposed to no-, low, moderate, high, and very high flood risk during an intense flood event. These estimates are available globally with a resolution of 90 meters, but they are also aggregated to administrative units, including for each country and subnational unit. These estimates are also aggregated to yield regional and global estimates. **4.** **Compute the number of poor people exposed to flood risk:** While poverty estimates are not available at the pixel level, the World Bank’s GMD database", "output": {"entities": {"named_data": [{"text": "GMD database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "in particular that of venturing into areas affected by ED in search of means of subsistence or even collecting scrap metal found on explosive remnants of war for resale. In the face of a growing threat from ED, mine action capacities remain limited in Niger. Considerable challenges exist both in programmatic actions and in the coordination of interventions. No mine action coordination mechanism is functional either at the national level or in the regions affected by ED. This makes it difficult to strategically harmonize, target and prioritize mine action interventions. The objective of this note is to strengthen advocacy with state authorities, the various technical and donor partners in order to support mine action in Niger, protect communities and humanitarian actors against the risks associated with ED and enable them to enjoy their fundamental rights and freedoms. ## **II. Analysis of the evolution of ED incidents and their impact** From the last quarter of 2022 to the 2nd reported mainly in the regions of Tillabery **2023, which indicates a worrying increase** **in the threat of ED in Niger.** This threat 1 UNHCR Niger montlhy PoC statistics, Juin 2023 2 Population displacement statistics, Ministry of Humanitarian Action and Disaster Management, july", "output": {"entities": {"named_data": [{"text": "UNHCR Niger montlhy PoC statistics"}], "descriptive_data": [{"text": "Population displacement statistics"}], "vague_data": []}}}
{"input": "region – which is itself a region of emigration. # 30.7 % 5 Non-Ukrainian nationals; of these, 52 per cent were in Bosnia and Herzegovina; 25 per cent in Serbia; 7 per cent in Kosovo; 6 per cent each in Albania and Montenegro; and 4 per cent in North Macedonia. In North Macedonia, this number includes individuals outside government-run centres, with forcibly displaced and stateless people accommodated in government or IOM-run centres, asylum centres, and transit facilities. UNHCR utilises arrival data to estimate the numbers involved. Note: References to Kosovo shall be understood to be in the context of Security Council Resolution 1244 (1999). Page 5 **U N H C R R E G I O N A L B U R E A U F O R E U R O P E,** O C T O B E R 2 0 2 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "arrival data"}]}}}
{"input": "**The World Bank** Uganda Development Response to Displacement Impacts Project Phase II (P510476) PROJECT APPRAISAL DOCUMENT Knowledge and technology transfer from TSPs to CRPs will be crucial for long-term sustainability at scale. Training content for CRPs and project beneficiaries will focus on climate resilience through adoption of improved inputs, technologies, and practices, while ensuring availability of information services on soil, weather, and markets for risk mitigation. Building on global lessons from World Bank-financed CDD projects, two-three specialized CRPs will be developed in each village in line with priority value chains under implementation. CRP networks will include refugees in the settlements. 44. **Collaboration with other World Bank-financed projects will be prioritized to maximize impacts.** DRDIP II will collaborate with INVITE and NUSAF IV to identify common economic infrastructure development and job creation opportunities. Several strategies will be implemented to prevent beneficiary overlap between NUSAF IV and DRDIP II in RHDs: (a) NUSAF IV will focus on the poorest individuals, while DRDIP II will target ‘active individuals’ identified through national wealth ranking data; (b) DRDIP II will concentrate on regions with a high refugee population, freeing up NUSAF IV to operate in other areas; (c) data sharing will be facilitated through interoperability", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "national wealth ranking data"}], "vague_data": []}}}
{"input": "in the country live in flood hazard zones. In other words, high-income provinces and districts tend to be more exposed to flood risks. However, a different study finds that in Ho Chi Minh City, the poor are disproportionally exposed to flooding (Narloch and Bangalore 2018). How do these results fit together? Indeed, at the local level the relationship between poverty and flood exposure can be inversed. Flood hazards tend to be highly localized, with some neighborhoods being at risk from frequent inundation, while other nearby neighborhoods may benefit from higher elevation or better drainage systems. Hallegatte et al. (2017) review the literature and conclude that land and housing markets often push poorer people to settle in these riskier areas, especially where land is scarce. Indeed, a meta-analysis of the literature suggests that a 1 percentage point increase in the yearly probability of flooding is associated with a 0.6 percent decrease in housing prices (Daniel, Florax, and Rietveld 2009). In Ho Chi Minh City, for instance, qualitative surveys suggest flood-prone areas can be much cheaper than non-flood-prone areas for the same quality of accommodation (World Bank and Australian AID 2014). Using a household survey in Dar es Salaam, Tanzania, Erman et", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "household survey in Dar es Salaam, Tanzania"}, {"text": "household survey"}]}}}
{"input": "# **PROTECTION** **BRIEF** **CZECHIA** ## Operational Context Based on the number of refugees who applied for an extension of Temporary Protection in 2024 (320,000), the figures of Temporary Protection holders in Czechia, including new arrivals, were updated to **338,736** people as of 31 March 2024, compared to 373,745 at the end of 2023 (source: Ministry of the Interior). In January 2024, _Lex Ukraine_ was amended to extend Temporary Protection until March 2025. Changes introduced include an adjustment of the initial level of humanitarian benefits, maintaining support for the most vulnerable individuals, and the reduction of cost-free accommodation for all new arrivals from 150 to 90 days. This report presents an overview of refugees’ demographic profiles and displacement patterns as well as main findings regarding protection risks, priority needs and intentions of refugees from Ukraine in Czechia. The analysis is based on 480 Protection Monitoring interviews and findings from focus group discussions with refugees from Ukraine across the country in the first quarter of 2024. ## Key Figures 338,736 320,000 ## 338,736 320,000 Temporary Protection holders in Czechia among whom have registered for an extension ## 92% of Protection Monitoring respondents are Temporary Protection holders ## 32% of respondents have at", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "are found in the Mekong Delta, the Red River Delta, and the Southeast Coast (Figs. 5, 6, and 7). But the relative exposure (that is, the percent of the district population which is exposed to floods) shows a larger spread (Figs. 8, 9, 10). Most areas in the country – including the North Central Coast and the Northeast – have high percentages of their populations residing in flood-prone areas (Fig. 8). Flood Exposure and Poverty To examine the question of how many poor people in Vietnam are exposed to flooding, we multiply the population exposure estimates by the district’s poverty headcount rate (the percentage of people living below USD 1.25 per day), as calculated in (Lanjouw et al. 2013). For a 25-year historical flood, 30% of today’s poor population is exposed. This number increases by between 16 and 28% given climate change impacts. For a 50-year return period under a high climate scenario, 40% of today’s poor people in Vietnam are exposed to flooding. For a 200-year return period under a high climate scenario, more than half of today’s poor are exposed. Similar to the population analysis, the impact of climate change on the number of poor people exposed is", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "district’s poverty headcount rate"}], "vague_data": []}}}
{"input": "will be biased (Heckman 1979; Lee 1983). In Section 2 we develop a theoretical model that improves on past efforts to model irrigation with the Ricardian approach by explicitly addressing farmer choice and selection bias. We tested this model empirically using a sample of over 8400 farmers from across 11 African countries. The results reveal that the choice of irrigation is endogenous. Farmers select irrigation rather than dryland to maximize profits. As temperatures warm or precipitation declines, farmers turn to irrigation to keep their farms viable. As long as there is a sufficient flow of water, irrigation is an important adaptation strategy. We then used this empirical model to examine the welfare impacts of climate change on African agriculture. Using a mild and a severe climate scenario, we examined how irrigation and net revenues will be affected. We compared the results of our model with endogenous irrigation with a model that assumes irrigation is exogenous. We found evidence of selection bias but, more importantly, we found that treating irrigation as though it is exogenous leads to biased welfare estimates. The paper concludes by summarizing the results and discussing some policy implications. 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**REFERENCES** Basist A et al., 2001. Using the Special Sensor Microwave Imager to monitor surface wetness. _Journal of Hydrometeorology_ 2: 297–308. Cline WR, 1996. The impact of global warming on agriculture: Comment. _American_ _Economic Review_ 86: 1309–1312. Darwin R, 1999. The impacts of global warming on agriculture: A Ricardian analysis: Comment. _American Economic Review_ 89: 1049–1052. Dubin JA & McFadden DL, 1984. An econometric analysis of residential electric appliance holdings and consumption. _Econometrica_ 52(2): 345–362. FAO (Food and Agriculture Organization), 1997. Irrigation potential in Africa: A basin approach. _FAO Land and Water Bulletin,_ 4, FAO Land and Water Development Division, Rome. FAO (Food and Agriculture Organization), 2003. The digital soil map of the world: Version 3.6 (January), Rome, Italy. Heckman JJ, 1979. Sample selection bias as a specification error. _Econometrica_ 47: 153–161. Heltberg R & Tarp F, 2002. Agricultural supply response and poverty in Mozambique. _Food_ _Policy_ 27: 103–124. Kurukulasuriya P & Mendelsohn R, 2005. A regional analysis of the impact of climate change on African agriculture, Mimeo, Yale University. Lee LF, 1983. Generalized econometric models with selectivity. _Econometrica_ 51: 507–512. Mendelsohn R & Dinar A, 2003. Climate, water, and agriculture. _Land Economics_ 79(3): 328–341. Mendelsohn R & Nordhaus W,", "output": {"entities": {"named_data": [{"text": "the digital soil map of the world"}], "descriptive_data": [], "vague_data": []}}}
{"input": "period hazard maps used for each of the future scenarios are outlined in Table 2. Although simplistic, this method allows areas that may be impacted by increasing riverine and extreme rainfall driven flooding to be identified. Clearly there are some significant assumptions and uncertainties arising from this method. However, given the impracticalities of modeling future flood hazard in Vietnam, this approach provides a plausible and practical attempt to estimate changing flood hazard at the national scale. For each of the four return periods, four scenarios are modeled (historical, future with low sea level rise, future with medium sea level rise, and future with high sea level rise), combining the coastal and fluvial/pluvial hazard layers (Table 2). For full details on the methodology used to produce these hazard maps, see the online supplementary materials. Importantly, the flood hazard models do not include flood protection (such as dikes and drainage systems), which can make a large difference in the flood hazard particularly in well-protected areas. In these wellprotected areas, our flood maps may overestimate the flood hazard. This is a data limitation that affects many studies of flood exposure: even in high-income countries like the US, flood protection databases are incomplete and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "flood protection databases"}]}}}
{"input": "prevalence of ED incidents related also leads to restrictions on the mobility of civilian populations on the roads to weekly markets, and the main cities of communities/departments. About 36% of those interviewed [6] say they encounter mobility constraints due to the activities of the NSAGs and military operations. This indicator varies from one region to another. In the regions of Diffa and Tillabery, 56% of respondents say they encounter mobility constraints, one of the main reasons being the presence of ED. This considerably limits the periodic supply of households with means of subsistence and necessities in addition to the fear and psychological distress that the unpredictable presence of ED inflicts on communities. It is also important to highlight that of the 11 affected departments in the Diffa and Tillabéry regions, 9 (82%) are also affected by the food insecurity [7] . This could exacerbate 4 CNCCAI: The disaggregation by sex and age of the 2023 data for victims is not yet available. However, according to the Child Protection Sub-cluster, the Child Protection Working Group of the Diffa region recorded 18 child victims of ED in 2022, the majority of whom (74%) are girls who went to look for firewood. 5", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "2023 data for victims"}], "vague_data": []}}}
{"input": "the last quarter of 2022 to the 2nd reported mainly in the regions of Tillabery **2023, which indicates a worrying increase** **in the threat of ED in Niger.** This threat 1 UNHCR Niger montlhy PoC statistics, Juin 2023 2 Population displacement statistics, Ministry of Humanitarian Action and Disaster Management, july 2023 3 Source : National Commission for the Collection and Control of Illicit Weapons (CNCCAI in french)", "output": {"entities": {"named_data": [{"text": "UNHCR Niger monthly PoC statistics"}], "descriptive_data": [{"text": "Population displacement statistics"}], "vague_data": []}}}
{"input": "already causes major problems in Vietnam, with some segments of the population more vulnerable than others (Adger 1999; World Bank 2010; World Bank and Australian AID 2014). In particular, evidence suggests poor people are more vulnerable than the rest of the population to natural disasters such as floods, as their incomes are more dependent on weather, their housing and assets are less protected, and they are more prone to health impacts (Hallegatte et al. 2016, Chapter 3). Poor people also have a lower capacity to cope with and adapt to shocks due to lower access to savings, borrowing, or social protection; and climate change is likely to worsen these trends (Hallegatte et al. 2016, Chapter 5). Therefore, it is important to quantify how many people are exposed to floods, how this distribution of exposure falls upon regions and socioeconomic groups, and how climate change may influence these trends. In the spirit of a Bstress-test^ to examine the seriousness of the issue, this paper employs flood hazard maps and spatial socioeconomic data to examine the following questions in context of Vietnam: 1. How many people are exposed currently? How might this change under climate change? 2. Where is exposure highest currently?", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "flood hazard maps"}, {"text": "spatial socioeconomic data"}], "vague_data": []}}}
{"input": "Additionally, climate change exacerbates existing pressures, with rising temperatures and erratic rainfall further straining local resources and food security. 2. **These economic and climate constraints contribute to persistently high levels of inequality and social** **vulnerability** . Using the World Bank poverty line for Low Middle-Income Countries (LMIC) of US$3.65 a day (2017 purchasing power parity), the extreme poverty rate for 2022 is estimated at 39 percent (World Bank 2023a). Inequality in Djibouti is among the highest in the Middle East and North Africa, with an estimated Gini coefficient of 0.42 in 2017. The highest income decile of the population consumes approximately 16 times as much as the lowest decile and twice that of the ninth decile (World Bank 2019a). Extreme poverty is particularly severe in rural areas, where it reaches 62.6 percent, much higher than in urban Djibouti. Water management and planning performance, integrating cooling systems, diversifying livelihoods, and responsive safety nets were key recommendations from the Climate Change Development Report (2024) for Djibouti. 3. **Low human capital further constrains economic and climate resilience and limits opportunities for inclusive** **growth.** Djibouti’s LMIC status contrasts sharply with its poor human capital outcomes (World Bank, HCR, 2024). Deficiencies are evident throughout the", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "World Bank poverty line for Low Middle-Income Countries"}], "vague_data": []}}}
{"input": "stem from the same occupational variable in the DHS data, and are mutually exclusive. The surveyed individual is told to report their main occupation. The coefficients can therefore be interpreted as relative increases of each specific sector. Women are more likely to earn cash for work, and the likelihood increases by 5.4 percentage points, which is equal to a 6 percent increase. While the directionality of the occupational outcomes is broadly in line with previous results (Kotsadam and Tolonen, 2016, for 29 African countries, and Benshaul-Tolonen, 2018, for 8 African gold-producing countries), the estimates are largely insignificant, potentially due to a limited sample size. Two categories have positive, albeit insignificant, coefficients: services and manual labor. The (insignificant) estimate for service jobs [9] is equivalent to 6.7% increased employment, and manual labor 10.2%, alongside which the likelihood that a woman earns cash for her work increases with 6%. For men (panel B of table 4), the estimates point toward an increase in agriculture, services, and professional (all statistically insignificant estimates), but a decreased likelihood of working in manual labor. Results for men in panel B are largely insignificant, and it is worthwhile noting that the sample size is only slightly above", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "DHS data"}]}}}
{"input": "these mines. **Figure 2 Gold mines and DHS clusters in Ghana** **Panel A Gold mines and 20 km buffer zones Panel B Gold mines, DHS clusters, and 100 km buffer zones** 4 The distances are radii from mine center point, and form concentric circles around the mine. 5 The DHS and the GLSS data are representative at the regional level, and not at the district level. Since the regional level is too aggregated, we do the analysis at the district level, but note that the sample may not be representative. 8", "output": {"entities": {"named_data": [{"text": "GLSS"}], "descriptive_data": [], "vague_data": []}}}
{"input": "regions alike. Figure 10 especially highlights high-risk regions in coastal regions and large river basins – such as the Mississippi, Nile, Ganges, Brahmaputra, or Mekong basins. _Figure 10. Share of total subnational population that is exposed to significant flood risk (percent)_ Pool (Congo Republic) Pathum Thani (Thailand) N'djamna (Chad) Sing Buri (Thailand) Red River Delta (Vietnam) Unity (South Sudan) Mekong Delta (Vietnam) Phra Nakhon Si Ayu (Thailand) Vientiane (Laos) Nonthaburi (Thailand) _Figure 11. Top 10 countries: Share of total subnational population that is exposed to significant flood risk_ **5.4.** **Income levels, poverty, and flood exposure** **The flood exposure of economic production value.** By taking into account per capita income levels, it is possible to obtain estimates of the value of economic activity that is exposed to flood risks around the world. Specifically, we multiply flood exposure headcounts with subnational estimates of daily income per capita (in $PPP terms, as obtained from the World Bank household survey database, Section 3.4). This yields the estimate that $5.3 trillion of 16", "output": {"entities": {"named_data": [{"text": "World Bank household survey database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "43.7 60.5 24.5 Number of trees per acre 71.1 99.8 15.1 79.7 138.3 12.8 Planted coffee trees during the past 5 years 8.7 11.7 2.8 7.3 12.8 1.1 Planted fruit trees during the past 5 years 16.2 21.2 6.5 12.3 20.9 2.6 Planted soil fertility trees past 5 years 3.8 4.8 2.0 2.8 4.8 0.5 Planted (any) trees during the past 5 years 18.6 24.4 7.3 14.5 24.6 3.0 Number of trees planted past 5 years 16.6 22.4 5.3 17.8 28.1 6.1 Soil cons. (bunds, terracing, mulching) 20.5 24.7 12.3 19.9 27.6 11.0 Use of manure during the past year 7.8 9.6 4.2 7.2 11.2 2.7 Number of observations (parcels) 13130 8652 4478 5448 2904 2544 _Source:_ Own computation from 2005/06 UNHS III 18", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "based on data from BASIX. In panel B, I restrict the analysis to villages that had at least one buyer the year after insurance outcomes, creating a sample analogous to the “Marketing Restricted Sample” in table 3. The logic behind this is, if a village had zero buyers, it is likely that insurance was not marketed in the village that year, and therefore customers did not have an opportunity to purchase insurance. Restricting the data set in this way gives a much clearer pattern. Column 5 now shows much stronger effects of payouts on repeat buying, though the pattern is the same as in column 2. Small payouts have a negative effect, whereas increasing the payout ratio increases repeat buying. The squared term on the payout ratio is now negative and significant, indicating that high payout ratios have diminishing effects. The coefficients for new buyers in column 6 are now all significantly different from the coefficients for repeat buyers. In fact, the coefficients in column 5 flip signs, suggesting that payouts have the opposite effect on people who did not receive payouts. These results suggest that low payouts actually induce more new buyers, but that these effects decrease and then", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Based on requests, the World Bank will transfer advances to the DAs. Subsequent replenishment of the DA will be based on the submission of application of withdrawal, accompanied by quarterly IFRs, which are reviewed and cleared by the World Bank. 57. **For activities implemented at the district level, MINEMA will disburse funds directly to each district into a** **separate operational project account denominated in RWF opened at the Central Bank.** Funds will be disbursed as per modalities stipulated in the TDIAs, which will include at a minimum an approved annual work plan and cash flow plan. Subsequent requests will be based on modalities defined in the PIM and the TDIAs. **IV.** **PROJECT APPRAISAL SUMMARY** **A. Technical, Economic and Financial Analysis** **Economic Analysis** 58. Based on the economic and financial analysis, the net present value (NPV) is estimated at US$25.2 million at a 12 percent discount rate, and the economic rate of return (ERR) at 26 percent. [25] For the purpose of this analysis, we consider anticipated economic benefits as the income of the project investments—therein applying the discounted cash flow model for financial analysis of private investments within the context of a World Bankfinanced project. Key variables used as assumptions", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "quarterly IFRs"}]}}}
{"input": "incorporate our long-run panel of cyclone data may contribute important insights about climate change adaptation on the coastal “front line”. 23", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "long-run panel of cyclone data"}], "vague_data": [{"text": "cyclone data"}]}}}
{"input": "**Figure A1. Access to infrastructure: Varying the cutoff and spatial lag model** **Panel A Household has electricity** **Panel B Household has radio** **a. Varying cutoff** **a. Varying cutoff** **b. Spatial lag model** **b. Spatial lag model** **c. Spatial lag model by migration status** **c. Spatial lag model by migration status** _Note:_ The figure shows the main treatment coefficients ( _active*mine_ ) using the baseline estimation strategy (with DHS individual-level data; see table 4 for more information) in panel A, but with different distance cutoffs (10 km, 20 km, 30 km, 40 km, or 50 km). *** p<0.01, **p<0.05, *p<0.1. Panels Ab, Ac, Bb, and Bc show the result using spatial lag models, which divided the plane into different treatment bins (0–10, 10–20, 20–30, 40–50) and compares them with farther away distances. Panel B shows the result for all individuals, and panel C shows the main treatment result (active mine) when the sample has been split into migrants and nonmigrants. 44", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "DHS individual-level data"}], "vague_data": []}}}
{"input": "The World Bank’s Environment Strategy focuses on both the threat to biodiversity from human encroachment, and the value of biodiversity resources for human populations. Our indicator for this two-way relationship in each country is its total human population in critical biodiversity areas. For marine biodiversity, we draw on estimates of reef ecosystems at risk by Bryant, et al. (1998). Summing across all endangered reefs, we use each country's share of the total as our index of marine biodiversity threat. While terrestrial and marine threats are quite distinct geographically, we create a composite indicator to match the Bank's thematic category (biodiversity conservation). Since the two indices are weakly correlated (ρ = .27), assignment of relative weights has a significant impact on the result. We assign equal weights, because we have no scientific basis for a differentiated weighting scheme. 5", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "and good governance. Additionally, the project supports key findings from the World Development Report 2023 on Migrants, Refugees and Societies, [18] by enhancing the freedoms, self-reliance and inclusion of both refugees and host community within national delivery systems. Furthermore, each activity will integrate climate-resilient design to reduce material risks to an acceptable level, ensuring long-term sustainability in the face of the country’s exposure to identified climate risks (extreme heat, droughts, floods). 18. **The challenges faced by Djibouti are further highlighted in the Country Climate and Development Report (CCDR)** **(2024), which identifies key areas for intervention, including strengthening water management, integrating cooling** **systems, diversifying livelihoods, and enhancing responsive safety nets** . The Integrated Community Resilience Project (ICRP) aligns with these recommendations, supporting Djibouti’s efforts to build climate resilience while addressing urgent needs in rural areas, particularly through enhancing the adaptive capacity of vulnerable populations. 19. **The project is aligned with the National Adaptation Plan (NAP) (2019)**, aiming to reduce vulnerability to climate change and to facilitate integration of adaptation into all levels of development planning including (i) access to water for all; ii) the promotion of best practices in the agricultural, forestry, fishery, and tourism sectors and reduced vulnerability to the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "-0.094** -0.062 3.893 -0.064 -0.031 0.126*** (0.042) (0.040) (3.842) (0.066) (0.038) (0.042) _3. drop 2 years before_ active*mine -0.094** -0.062 3.708 -0.071 -0.026 0.125*** (0.041) (0.039) (3.459) (0.067) (0.036) (0.043) _4. mine FE_ active*mine -0.123** -0.094* 8.233 -0.068 -0.049 0.113** (0.057) (0.051) (5.425) (0.075) (0.044) (0.045) _5. mine clustering_ active*mine -0.086*** -0.055** 3.705 -0.058 -0.032 0.125** (0.025) (0.025) (2.898) (0.086) (0.032) (0.051) Mean dep var 0.715 0.705 45.71 0.491 0.259 0.028 _Note:_ The table uses GLSS data for Ghana for the survey years 1998, 2005, 2012. The sample is restricted to women and men aged 15–49. Robust standard errors clustered at the village or neighborhood level in parentheses (except if otherwise stated). All regressions control for year and district fixed effects, urban dummy, age, and years of education. Active is active status of mine in the survey year. The treatment distance is defined to 20 km. Rows 2 drop sample between 20 to 40 km of a mine, and rows 3 drop sample that was surveyed two years before mine opening. *** p<0.01, **p<0.05, *p<0.1. FE = fixed effects. 30", "output": {"entities": {"named_data": [{"text": "GLSS data for Ghana"}], "descriptive_data": [], "vague_data": []}}}
{"input": "poor households’ productivity and resilience to lift their consumption permanently above the official poverty line. 4. **The government has embraced the long-term development approach to refugee management, aligning with** **international good practice.** [6] Important gains over the last five years include: (a) almost all refugee children now attend national schools rather than camp-based schools; (b) most urban refugees have access to the government’s national health insurance scheme; (c) plans are in place to transition camp-based health clinics to government management to lower costs and support integration of refugees into national service delivery systems; and (d) the government is implementing an economic inclusion strategy for refugees and host communities. Investments made over the last five years have addressed many of the impacts of the refugee presence that had created tensions with host community members. Survey data from the mid-term review (MTR) of Jya Mbere Phase I showed that this has strengthened social cohesion between refugees and host communities, creating a strong foundation for future economic progress. 5. **Building on the gains made, the government’s strategic aim for refugee management is now to promote** **self-reliance.** As one of the four objectives of the GCR, self-reliance is also central to both the National", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Uganda Development Response to Displacement Impacts Project Phase II (P510476) PROJECT APPRAISAL DOCUMENT of sub-project sites. Monitoring will be enhanced in Phase II, including regular beneficiary phone surveys and quarterly technical supervision missions, targeting infrastructure subprojects that are more complex and challenging. 52. **Importance of collaboration and partnerships across the humanitarian-development nexus.** The scale of the refugee presence and the scope of interventions required to bring about inclusion and self-reliance necessitates collaboration between various stakeholders, including government, non-governmental organizations, and international partners. Specific activities under DRDIP II to strengthen government-led coordination efforts are intended to build strong partnerships to create a holistic and integrated response framework. 53. **Refugee situations tend to last for years and managing them exclusively through emergency and humanitarian** **programs is ineffective** . The main conclusion of the World Development Report 2023 on _Migrants, Refugees, and_ _Societies_ is that policies should be geared toward financial and social sustainability by means of internal mobility, selfreliance, and inclusion in national services. The design of DRDIP II fully aligns with these lessons through its focus on selfreliance and integration of refugees into national service delivery systems. 54. **Multi-sectoral development investments directed to forcibly displaced populations and host", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "u1 ~ N(0,1) u2 ~ N(0, σ2) u3 ~ N(0, σ3) corr(u1, u2) = ρ2 corr(u1, u3) = ρ3 Irrigation is observed only if it is more profitable than dryland farming. Thus, the observed dependent variable Y is: Y=1 if ΠI > ΠD Y=0 if ΠD > ΠI When ρ = 0, OLS (Ordinary Least Squares) regression provides unbiased estimates, but when ρ ≅ 0 the OLS estimates are biased. We consequently employ the estimated Mills ratio from the selection model in both the irrigated and dryland conditional regressions in order to control for selection (Dubin & McFadden 1984). We expect the signs on the coefficient of the estimated Mills ratio to be opposite in each regression. With the estimated Mills ratios, the selection model allows us to use information on whether farms irrigate or not to improve the estimates of the parameters in the regression model. That is, the selection model provides consistent, asymptotically efficient estimates for all parameters in the model (Dubin & McFadden 1984). **3. Empirical results** The empirical analysis is based on a household survey conducted of 11 countries across Africa: Burkina Faso, Cameroon, Egypt, Ethiopia, Kenya, Ghana, Niger, Senegal, South Africa, Zambia and Zimbabwe (for", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "household survey"}], "vague_data": []}}}
{"input": "early numeracy, to respond to the learning diagnostic (iii) Deployment of these didactic resources to classrooms at the Preschool, Primary, and Secondary levels (within each level and articulation between levels), and through MEP’s digital platform; (iv) Digital platform of a professional development plan for teachers, school principals, and pedagogical advisors for the deployment of foundational learning; (v) Development and implementation of a national foundational learning campaign emphasizing the joy of reading, writing, and numerical competency to involve parents and the larger education community; and (vi) Public provision of six monthly reports regarding the school and grade level accomplishment of literacy and numeracy. Educational resources and professional development plans for teachers will include considerations of gender equity and promote supportive and inclusive learning environments where all students feel encouraged to read, with specific measures outlined in the foundational learning strategy to close the gender gap in reading and in mathematics. This subcomponent will finance consultancy firms and individuals and procurement of the digital tools and the development, production, and dissemination of curricular and didactic materials for teachers and students. 29. _Subcomponent 2.2. Support of Digital Competencies and Hybrid Learning_ (US$95 million). This subcomponent will support the digitalization of learning through two", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "social cohesion between refugees and host communities, creating a strong foundation for future economic progress. 5. **Building on the gains made, the government’s strategic aim for refugee management is now to promote** **self-reliance.** As one of the four objectives of the GCR, self-reliance is also central to both the National Strategy for Sustainable Graduation and the draft Refugee Sustainable Graduation Strategy. Through successful implementation of the two strategies, the government expects to: (a) reduce expenditure on social safety net programs for Rwandese and humanitarian aid for refugees; and (b) unlock the potential of refugees to support economic development. This will also contribute to key results in Rwanda’s _National Strategy for Transformation 2 (2024-2029)_ on creating jobs, improving education and the quality-of service-delivery. Shifting to a development approach to achieve self-reliance is increasingly urgent in light of dwindling humanitarian assistance. For instance, funding for UNHCR in Rwanda fell from US$49 million in 2020 (only 49 percent of needs) to US$37 million in 2023 (41 percent of needs), despite almost no change in refugee numbers. 6. **Progress towards achieving refugee self-reliance is hampered by a lack of employment and income-** **generating opportunities.** A tailored Refugee Self-Reliance Index (RSRI) prepared by the GoR,", "output": {"entities": {"named_data": [{"text": "tailored Refugee Self-Reliance Index"}], "descriptive_data": [], "vague_data": []}}}
{"input": "we split the sample according to the wealth score provided by DHS. Given the data structure, which is repeated cross-section, we cannot follow a particular household that was identified as belonging to the bottom 40 percent in the initial time period. Instead, we identify the bottom 40 percent in four groups: far away, before mine or during mine, and close to mine, before mine or during mine. The summary statistics for selected main outcomes are presented in table 10. As the table shows, the bottom 40 percent in mining communities are more likely engaging in agriculture than the bottom 40 percent elsewhere. This could illustrate that agricultural workers are overrepresented among the less well-off in mining communities. However, women in this group still more often work in services than women did before in the same communities. 15 Fastgini is a user-written command in STATA that helps calculate the gini coefficient. 27", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "DHS"}], "vague_data": []}}}
{"input": "2015; Mallick et al. 2011; Mallick and Vogt 2013; Shameem and Momtaz 2014; Siddiqui et al. 2013; Sultana and Mallick 2015). With the notable exception of Dasgupta et al. (2016), these studies have seldom used household-level data to assess the impacts of past cyclones on communities and households, as well as their role in the formation of expectations about future impacts. Such research requires construction of a georeferenced panel database that specifies the dates of cyclonic storms, their coastal landfall points, subsequent interior paths, and measures of relative power. Construction of an appropriate spatial panel has therefore been a primary objective of this exercise. To support ongoing research, we focus on the coastal regions of Bangladesh and two contiguous Indian states -- West Bengal and Odisha. However, our approach could easily be extended to cover an arbitrarily-large set of coastal regions. 2", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "georeferenced panel database"}], "vague_data": [{"text": "household-level data"}]}}}
{"input": "**1 Introduction** The mining sector in Africa is growing rapidly and is the main recipient of foreign direct investment (World Bank 2011). The welfare effects of this sector are not well understood, although a literature has recently developed around this question. The main contribution of this paper is to shed light on the welfare effects of gold mining in a detailed, in-depth country study of Ghana, a country with a long tradition of gold mining and a recent, large expansion in capital intensive and industrial-scale production. A second contribution of this paper is to show the importance of decomposing the effects with respect to distance from the mines. Given the spatial heterogeneity of the results, we explore the effects in an individual-level, difference-in-differences analysis by using spatial lag models to allow for nonlinear effects with distance from mine. We also allow for spillovers across districts, in a district-level analysis. We use two complementary geocoded household data sets to analyze outcomes in Ghana: the Demographic and Health Survey (DHS) and the Ghana Living Standard Survey (GLSS), which provide information on a wide range of welfare outcomes. The paper contributes to the growing literature on the local effects of mining. Much of", "output": {"entities": {"named_data": [{"text": "Demographic and Health Survey"}, {"text": "Ghana Living Standard Survey"}], "descriptive_data": [{"text": "geocoded household data sets"}], "vague_data": []}}}
{"input": "**The World Bank** Zambia Refugee and Host Communities Project (P503941) 9. **External audit.** The project audit will be carried out by the Office of the Auditor General who is mandated by law to do so. The implementing agencies will prepare annual financial statements for their operations, including for the project at the end of each financial year. The audit TOR will be prepared by the implementing agencies and cleared by the World Bank before each year’s audit. The auditors will produce an audit report and management letter highlighting areas/issues which will require addressing. The MoHAIS will be required to submit the audit report together with the management letter to the World Bank not later than six months after the end of the financial year. 10. **FM supervision and implementation support.** FM supervision support will be conducted on a semiannual basis and will include interviews and desk reviews such as the review of the IFRs, statements of expenditure, and audit reports **.** **PROCUREMENT** 11. Standard Procurement Documents (SPD). The World Bank’s SPDs will be used for procurement of goods, works, and non-consulting services under the open international competitive procurement approach. Similarly, selection of consultant firms will use the World Bank’s SPDs,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Migration, pp. 1-23.](https://link.springer.com/article/10.1186/s40176-018-0138-2) 3 The self-reliance survey is part of the “Enhancing Self-Reliance and Preparedness for Forced Displacement in the Great Lakes Region” activity [(P500793) and draws on the global Refugee Self-Reliance Initiative index (www.refugeeselfreliance.org).](http://www.refugeeselfreliance.org/) 4 Phase I of Jya Mbere was approved on April 30, 2019, and will close on October 30, 2026. Of the total Phase I budget of US$84.41 million, US$68 million is from the IDA 18 Sub-window for Refugees & Host Communities and the IDA 19 Window for Host Communities & Refugees (WHR) and US$4.41 million was provided in co-financing by the Danish International Development Agency (Danida). 5 To meet WHR eligibility requirements, the Government submitted a Strategy Note on supporting refugees, which was discussed and agreed with the World Bank. Page 1", "output": {"entities": {"named_data": [{"text": "global Refugee Self-Reliance Initiative index"}], "descriptive_data": [{"text": "self-reliance survey"}], "vague_data": []}}}
{"input": "over time difficult. Valuation of a future loss is also complicated due to ambiguity in the rate of time preference. In light of these uncertainties, we estimated the economic value of the wetlands at risk for a single scenario of 1 m SLR using the current literature on valuation of wetlands. The economic value of the wetlands at risk from 1 m SLR in the 76 developing countries considered in this analysis is around USD 630 million per year (in USD 2000). It is hoped that the estimates of wetlands at risk from SLR reported in this paper would offer insights into the extent to which countries may be willing to invest to protect coastal wetlands or facilitate their migration as sea level rises. At the outset, we acknowledge several important limitations of our analysis. First, we have not assessed the time profile of 1 m SLR. We take this scenario as given, and assess the _exposure_ of the present wetland stock for each of the 76 developing countries and five regions. Second, the digital elevation (90m DEM V2) data we use in our analysis gives altitude in 1-meter increments, preventing us from sub-meter SLR modeling. [13] Third, the lack", "output": {"entities": {"named_data": [{"text": "digital elevation (90m DEM V2) data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "22,200 people per month in refugee-hosting areas of Djibouti [13] . 14. **Women are disproportionately affected by socio-economic disadvantages in Djibouti, facing significant gaps** **across different dimensions, including access to basic services, education and employment opportunities** . Multidimensional Poverty Index (MPI) is reported to be higher among women than men (27 percent vs. 18 percent in the 15-24 age group and 27 percent vs. 23 percent in the 25-39 age group), as well as food insecurity is reported to be higher among female-headed households [FHHs] (51 percent vs. 45.5 percent) [14] . Women, who are generally the primary caregivers of infants and children, tend to lack information on beneficial practices related to child nutrition, parenting practices, and child stimulation (the proportion of women with children less than six months of age practicing exclusive breastfeeding stands at 12 percent [15] ). Women also experience higher unemployment rates (36 percent vs. 22 percent for men) and are more likely to hold vulnerable, informal, or part-time jobs (44.5 percent vs. 18.5 percent for men). In rural areas, the employment gaps widen further. Overall, men have better access to credit and financial services, productive inputs, and business opportunities with consequences on female entrepreneurship [16]", "output": {"entities": {"named_data": [{"text": "Multidimensional Poverty Index (MPI)"}], "descriptive_data": [], "vague_data": []}}}
{"input": "the CRRF, which is served by a small secretariat under the Office of the Prime Minister (OPM). While the coordination structures are fully functional, more support is needed for operational coordination on the ground considering the growing refugee population and the increasing number of development projects supporting host-community-refugee inclusion. For instance, in 2016, DRDIP was the only World Bank-financed project on forced displacement in Uganda. By 2025, however, there are 11 projects funded by the IDA Window for Host Communities and Refugees (WHR), with a total budget of US$666 million. Continued strong government leadership from OPM will be required to facilitate effective coordination across these and related projects. 10. **The project is aligned with the World Bank Maximizing Finance for Development approach.** Private investment generated through Component 3 on Economic Opportunity counts as Private Capital Mobilization (PCM). Sub-component 3.1 on Resilient Value Chains and Enterprise Investments (US$77.5 million) will provide group-based revolving funds and start-up grants to approximately 234,500 beneficiaries to enhance their economic investments and value chain engagement. PCM of US$10 million has been added to the financing table based on beneficiaries' monthly collective 10 Climate Risk Profile: Uganda (2021): The World Bank Group. 11 “Uganda’s Intended Nationally Determined", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Integrated Community Resilience Project (P506969) PROJECT APPRAISAL DOCUMENT cash transfers, financial and productive inclusion as well as social services delivery to maximize the resilience of communities and households. 57. **Additionally, the project will draw on insight from the Yemen Emergency Crisis (ECRP) (2016-2022)** . **which** **sought to provide short-term employment and access to selected basic services to the most vulnerable and preserve** **existing implementation capacity of service delivery.** The project will strengthen private sector linkages, drawing from good practices identified in the ECRP, which demonstrated how participatory planning processes enabled the identification and prioritization of local economic needs. Djibouti’s project will similarly be community-driven, ensuring that refugees, host communities, and local entrepreneurs/microenterprises are actively engaged in identifying their needs and priorities. Drawing from Yemen’s example, the project will align productive facilities and local markets with SME operations to strengthen supply chain linkages and create sustainable economic ecosystems in targeted regions. [24] **III.** **PROJECT IMPLEMENTATION** **A. Institutional and Implementation Arrangements** 58. **The Ministry of Social Affairs and Solidarity (MASS)** **will serve as the primary implementing agency for the** **project, leading the implementation** **of Component 1: Social Safety Nets Systems**, **while the** **Djiboutian Social** **Development Agency (ADDS)** **will take", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Integrated Community Resilience Project (P506969) PROJECT APPRAISAL DOCUMENT support nutritional consumption needs - accompanied with SBCC to promote human development behavior change good practices; (ii) financial inclusion services (FIS) to strengthen the economic resilience of poor and vulnerable households; and (iii) support for strengthening the Social Registry (SR) so that it becomes a stronger underpinning for effective coordination of social programs, ensures better targeting of safety nets, and provides credible information for measurement of results and impacts for all vulnerable populations, including refugees and hosts. 30. **Sustainability of the social safety nets** . Sustainable financing is critical to building an effective and efficient safety net system in Djibouti that can mitigate the adverse impacts of the perennial crises on the poor and vulnerable. The government committed to making efforts to increasing government financing for social safety nets as project financing declines. This commitment is being renewed and related technical simulations will be mainstreamed into the technical assistance that is being provided by the World Bank under the Strengthening Adaptive Social Protection Systems (P166220). Recommendations from the Technical Assistance will be discussed with the MASS and the Ministry of Economy and Finance (MEFI) and be mainstreamed into the", "output": {"entities": {"named_data": [{"text": "Social Registry"}], "descriptive_data": [], "vague_data": []}}}
{"input": "the European Union (EU). The World Food Programme (WFP) has provided food assistance to refugees in Mantapala refugee settlement since 2017. The project’s three components will contribute to the building of a future policy framework and an operational model for the use of WHR resources that could be extended to assist refugees and host communities in other areas across the country. 44. **The project is timely.** National ownership and political will are prerequisites both for successful implementation and sustainability. The GRZ has demonstrated a commitment to both, and it is important that momentum is maintained to prevent any possible backsliding on the reform agenda. The World Bank in Zambia is active in all the sectors proposed as interventions under this project, which is aligned with sector approaches and designed to leverage cooperation with larger sector investments. **F. Lessons Learned and Reflected in the Project Design** 45. **Several key lessons pertinent to the objectives of the Window for Host Communities and Refugees (WHR) in** **Zambia have emerged from implementation of the CPF 2019–2024.** They include the importance of a multisectoral approach, the importance of stakeholder engagement, the challenges faced by the Government in addressing institutional constraints, and the need for simpler", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "this, most often by not being able to move freely or to access basic services. #### Protection Risk II **Access to adequate housing:** As for Q3 findings from Protection Monitoring interviews highlighted accommodation as the highest priority need for respondents (147 respondents, 34%). ## 34% reported accommodation as their highest priority need UNHCR / September 2024 2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "to be implemented, activity implementers will submit the payment details of the payee for payment from an appropriate bank account. Transfers to the Zambian Kwacha operational account will be made only when there are local currency payments to be made to avoid exchange losses being incurred by holding Zambian Kwacha balances. Other disbursement methods such as reimbursement, direct payment, and special commitment will be available on this project. The operation of all disbursement methods will be described in the Disbursement and Financial Information Letter (DFIL) (Figure 1.2). Page 39", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the scale of environmental problems faced by a country's institutions. If Brazil and Bhutan receive the same CPIA rating, for example, ignoring their scale difference will lead to assignment of identical lending in the optimization model. 6 We recognize that an equal-weighted index is only one of numerous plausible indicators for general environmental problems. In Appendix 2, we develop alternative indices and analyze their association with 6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "and maintaining ongoing dialogue with technical actors at national, regional, and global levels to bolster cash coordination. Additionally, they are responsible for developing and following a dynamic work plan that reflects the evolving priorities and discussions within the platform and across relevant sectors. This includes ensuring that the focus and deliverables of the platform remain relevant and contextually appropriate to the NIATF and the 3RP sectors. **Members:** The CBI TWG members are responsible to commit to fostering a transparent and cooperative environment by meaningful participation and sharing relevant operational delivery data (such as cash assistance delivered, beneficiaries assisted etc.). The members need to provide at least one focal point 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "operational delivery data"}]}}}
{"input": "collaborative and communication abilities; Science Technology, Art and Mathematics (STEAM) skills; and awareness of the environmental issues, energy efficiency, and eco-friendly innovation for their immediate community and the nation. By aligning education with the requirements of a low-carbon economy, Costa Rica 13 OECD (2021), Education at a Glance 2021: OECD Indicators, OECD Publishing, Paris, [https://doi.org/10.1787/b35a14e5-en.](https://doi.org/10.1787/b35a14e5-en) 14 MEP Data 15 Annex 1 reproduces a graphic showing the 67 modules across Pre-School to 12 grades of education that comprises the PNFT curriculum. Page 3", "output": {"entities": {"named_data": [{"text": "MEP Data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "## Regional Advisory Group refugees, statelessness, and citizenship. report. Lakes region. ## Regional Study Process Expected Outcomes and Impact The study will contribute to greater awareness of the causes, specific risk profiles and scale of statelessness arising from protracted refugee situations in countries of asylum in Great Lakes. The findings of the study will contribute to improve the overall situation of refugees in prolonged exile as part of finding durable solutions, by developing concrete recommendations for local integration with sustainable alternative legal status in host countries to mitigate risk of statelessness, realize the right to a [nationality and ensure access to proof of legal identity in line with S DG Target 16.9.](https://unstats.un.org/sdgs/metadata/files/Metadata-16-09-01.pdf) The analysis and recommendations will further inform the development of a comprehensive strategy on durable solutions for forcibly displaced persons including refugees in the Great Lakes,supporting the effortsof the ICGRL Member States to address protracted refugee situations and risks of statelessness, which arise from prolonged exile", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**APPENDICES** **Appendix A: Temperature normals (Sample means)** **`country`** **winter** **spring** **summer** **fall** `burkinafaso` 23.55 28.34 28.87 24.48 `cameroon` 19.38 21.38 19.97 18.87 `egypt` 11.67 13.17 24.11 23.38 `ethiopia` 18.64 21.53 19.71 18.07 `ghana` 21.79 24.81 22.63 21.16 `kenya` 18.75 19.72 18.36 19.12 `niger` 26.28 30.83 33.91 29.18 `senegal` 24.54 29.13 31.53 26.67 `south africa` 11.53 15.47 20.73 19.37 `zambia` 16.69 21.72 21.09 19.58 `zimbabwe` 16.58 21.29 22.49 20.63 **`total`** **19.82** **23.35** **24.52** **22.23** **Appendix B: Precipitation normals (Sample means)** **`country`** **winter** **spring** **summer** **fall** burkinafaso 2.6 15.83 113.78 133.12 cameroon 60.25 101.94 185.08 228.55 egypt 12.81 7.02 2.3 3.51 ethiopia 19.42 49.21 123.71 117.51 ghana 30.87 59.66 112.4 111.74 kenya 88.38 103.02 84.31 59.95 niger 0.75 3.15 64.05 70.55 senegal 2.23 1.05 47.93 112.72 south africa 31.79 54.96 86.38 68.79 zambia 48.26 57.7 108.58 100.67 zimbabwe 7.54 15.4 138.75 89.98 **total** **25.85** **39.83** **96.05** **102.4** 13", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "refugee populations are better documented and ascertained so that they can benefit from a wider range of integrated services. Interoperability with other databases will also enhance responsiveness in the event of a natural disaster. 39. **In addition to reinforcing the social registry, the sub-component will support enhancing the operational capacity** **of existing social counters (** _**guichets sociaux**_ **) in urban areas and regions.** These social counters will be upgraded to reach a greater number of individuals, enabling the registration of additional households, as well as the regular updating of data. The enhanced social counters will be equipped to handle grievances, ensuring timely and effective responses. These centers will also serve as key points for connecting refugees with essential services, facilitating their inclusion in national programs for social protection and economic empowerment. The centers will evolve into fully integrated one-stop service hubs, serving as entry points for basic services, beneficiary monitoring and grievances management. By implementing these measures, the project aims to create a robust and dynamic social registry that will not only address current needs but also adapt to future challenges. **Component 2: Access to Socio-Economic Infrastructure and Development of Economic Opportunities (** _**total IDA**_ _**US$14 Million equivalent, including WHR", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "the social registry"}], "vague_data": []}}}
{"input": "(1.805) (0.039) (0.054) (0.029) (0.021) (0.029) (0.021) Active 0.007 0.001 0.050** 0.034** -0.032 0.054** -0.023 (1.012) (0.026) (0.024) (0.017) (0.021) (0.026) (0.022) Observations 9,790 9,790 12,226 12,216 12,227 12,227 12,227 R-squared 0.128 0.180 0.453 0.148 0.208 0.171 0.095 mean of dep var 0.407 14.84 0.565 0.652 0.151 0.732 11.6 _Note:_ Robust standard errors clustered at the DHS cluster level in parentheses. All regressions control for year and district fixed effects, urban dummy, age, and years of education. Active is active status of mine in the survey year. *** p<0.01, **p<0.05, *p<0.1. OLS = ordinary least squares. Overall, we estimated in table 8 that a household’s access to electricity decreased when a mine became active. This finding is surprising if we assume that electricity infrastructure is seldom destroyed, so that with time, access has generally been increasing. [13] Figure A1 (Annex) further decomposes the effect, and panel Aa of the figure confirms that the coefficient for electricity access is negative using the treatment distance 20 km. However, with a treatment distance of 10 km, the effect is marginally positive and insignificant. If we use a treatment distance of 50 km, we no longer see a significant effect. In panel Ab, the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "exposure and awareness of flood risk in England and Wales. Disasters. Vol. 36(3), pp.477-494 Freire, Sergio; MacManus, Kytt; Pesaresi, Martino; Doxsey-Whitfield, Erin; Mills, Jane (2016): Development of new open and free multi-temporal global population grids at 250 m resolution. Geospatial Data in a Changing World; Association of Geographic Information Laboratories in Europe (AGILE). AGILE 2016. Daniel, V. E., R. J. G. M. Florax, and P. Rietveld. 2009. “Flooding Risk and Housing Values: An Economic Assessment of Environmental Hazard.” Ecological Economics 69 (2): 355–65. Durand-Lasserve, A., H. Selod, and M. Durand-Lasserve. 2013. “A Systemic Analysis of Land Markets and Land Institutions in West African Cities: Rules and Practices—The Case of Bamako, Mali.” Policy Research Working Paper 6687, World Bank, Washington, DC. [Hallegatte, S., A. Vogt-Schilb, J. Rozenberg, M. Bangalore, C. Beaudet (2020). \"From Poverty to Disaster](https://ideas.repec.org/a/spr/ediscc/v4y2020i1d10.1007_s41885-020-00060-5.html) [and Back: a Review of the Literature,\" Economics of Disasters and Climate Change, Springer, vol.](https://ideas.repec.org/a/spr/ediscc/v4y2020i1d10.1007_s41885-020-00060-5.html) 4(1), pages 223-247 Hallegatte, S., C. Green, R. Nicholls, J. Corfee-Morlot (2013). Future flood losses in major coastal cities. Nature Climate Change. Vol. 3, 802–806 25", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "open and free multi-temporal global population grids"}], "vague_data": []}}}
{"input": "The modeling of all coastal wetlands by McFadden et al. (2007) suggests that global wetland losses are 32% and 44% by the 2080s for a 50 cm and 1 m rise in sea level between 1990 and 2100 accounting for human impacts, such as dike construction or wetland nourishment. The estimates presented by McFadden at al. (2007) are not delineated by types of wetlands or by regions of the world. As for McFadden et al. (2007), the estimates of Nicholls (2004) and Nicholls et al. (1999) are also not disaggregated by types of wetlands. Furthermore, while Nicholls (2004) asserts the largest loss of coastal wetlands to be expected around the Atlantic coast of Central and North America, the small Caribbean islands, and most particularly the Mediterranean and the Baltic, the paper does not present estimates of lost wetlands by regions of the world. It should also be noted that neither of these analyses present estimates of the economic values, which may be associated to these lost wetland areas around the world. The valuation studies by Tol (2007) and Anthoff et al. (2010) are also based on wetland losses derived from the Global Vulnerability Analysis (Hoozemans et al. 1993). Wetland value", "output": {"entities": {"named_data": [{"text": "Global Vulnerability Analysis"}], "descriptive_data": [], "vague_data": []}}}
{"input": "needed.** The project will provide targeted support to strengthen M&E capacity within MASS and ADDS. Where feasible, the project will finance consultants to assist MASS and ADDS in developing a detailed M&E and reporting system plan. In addition, consultants will provide on-the-job training for M&E specialists across MASS, ADDS, and other implementing agencies, as well as any other support required to establish and maintain an effective M&E system. 64. **The MASS and ADDS have demonstrated capacity to undertake beneficiary assessments (BA) and technical** **audits (TA) to inform implementation and obtain stakeholder and beneficiary feedback as good practice** . Two BAs and TAs are anticipated to determine feedback and inform the pre and post MTR implementation. The BAs will provide feedback on satisfaction levels among key beneficiaries, identify challenges in implementation and make recommendations for improvements. The TAs which have been undertaken to ascertain delivery of cash transfers, will now cover a broader range of interventions including the financial services and SBCCs. **C. Disbursement Arrangements** 65. **Given the high-risk environment, the report-based disbursement will not be applicable.** Therefore, upon project effectiveness, transaction-based disbursements will be used. An initial advance up to the ceiling of the Designated Account (DA) will be made", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "(Eds.) _Climate Change 2007: The Physical_ _Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the_ _Intergovernmental Panel on Climate Change_ [Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Krabill, W, Hanna E., Huybrechts, P., Abdalati, W., Cappelen, J., Csatho, B., Frederick, E., Manizade, S., Martin, C., Sonntag, J., Swift, R., Thomas, R., and J. Yunge. 2004. Greenland ice sheet: increased coastal thinning. _Geophysical Research Letters_, 31: L24402 Larson, J.S., Adamus, P.R. and E.J. Clairain Jr. 1989. _Functional Assessment of Freshwater_ _Wetlands: A Manual and Training Outline_ . Glaud, Switzerland: WWF Publication 89-6: 62pp. Lehner, B. and P. Döll. 2004. Development and validation of a global database of lakes, reservoirs and wetlands. _Journal of Hydrology_, 296(1-4), 1-22 Maslanik, J. A., C. Fowler, J. Stroeve, S. Drobot, J. Zwally, D. Yi, and W. Emery, 2007: A younger, thinner Arctic ice cover: Increased potential for rapid, extensive sea-ice loss _Geophysical_ _Research Letters_ **34** : L24501 McFadden, L., Spencer,T. and R.J. Nicholls, 2007. Broad-scale modelling of coastal wetlands: What is required? _Hydrobiologia_, 577, 5-15. McLeod. K.L., Lubchenco, J., Palumbi, S.R. and A.A. Rosenberg. 2005. _Scientific Consensus_ _Statement on Marine Ecosystem-Based Management. The Communication Partnership for_ _Science", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "global database of lakes, reservoirs and wetlands"}], "vague_data": []}}}
{"input": "Strzepek K & McCluskey A, 2006. District level hydroclimatic time series and scenario analysis to assess the impacts of climate change on regional water resources and agriculture in Africa. CEEPA Discussion Paper No 13, Centre for Environmental Economics and Policy in Africa, University of Pretoria. USGS (US Geological Survey), 2004. Global 30 Arc Second Elevation Data, USGS National Mapping Division, EROS Data Centre. (These data files are downloadable from http://edcdaac.usgs.gov/gtopo30/gtopo30.asp) Weng F & Grody N, 1998. Physical retrieval of land surface temperature using the Special Sensor Microwave Imager. _Journal of Geophysical Research_ 103: 8839–8848. World Bank, 2003. Africa rainfall and temperature evaluation system (ARTES). World Bank, Washington DC. 12", "output": {"entities": {"named_data": [{"text": "Global 30 Arc Second Elevation Data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "its zone of maximum wind speed. We employ a standard IMD storm classification based on maximum wind speed intervals in kt: (Cyclonic Storm (CS) [34-47 kt]; Severe Cyclonic Storm (SCS) [48-63]; Very Severe Cyclonic Storm (VSCS) [64-119] and Super Cyclonic Storm (SuCS) [120+]. We have excluded all storms rated as tropical depressions because their maximum wind speeds are below 34 kt. The third distinctive feature of our exercise is use of the constructed database to explore temporal and spatial patterns in cyclone impacts that can provide the context for future household level research on adaptation by coastal communities. Our analysis is aggregative in this paper, but the source database can provide high-spatial-resolution cyclone incidence and impact measures for households and communities in both coastal and interior locations. We should introduce a cautionary note at the outset. During the past 140 years, technical support for cyclone tracking has evolved from land-based telegraphy in the 19th century, through 3", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "constructed database"}, {"text": "source database"}], "vague_data": []}}}
{"input": "and age of the 2023 data for victims is not yet available. However, according to the Child Protection Sub-cluster, the Child Protection Working Group of the Diffa region recorded 18 child victims of ED in 2022, the majority of whom (74%) are girls who went to look for firewood. 5 Departments of: Torodi, Say,Téra, Tillabéry, Gotheye, Bankilaré et, Ouallam (région de Tillabéry) et Diffa, Bosso, Mainé et N'Guingmi (region de Diffa) 6 According to protection monitoring data (P21) 1st semester 2023. 7 [Food security situation, june 2023](https://drive.google.com/file/d/1FVzLNdVSeHdrZ0iNx0YUf2LNiWuO5gBS/view?usp=sharing)", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "protection monitoring data (P21)"}], "vague_data": []}}}
{"input": "replace deteriorating reservoirs, extend the water distribution network, or enhance water storage and management. This would lead to increased risks of water shortages and contamination, endangering the health of the refugees. Substandard waste and sanitary management would also pose significant health hazards to the camp residents. Access to quality obstetric care and services as well as essential medicines will also be compromised. 1 _UN agencies use different points of reference for the population living in the Tindouf refugee camps. For example, UNHCR uses the number 90,000 to refer to the_ _‘most vulnerable refugees’ although recognizing that assistance needs are much higher. The Sahrawi Response Plan launched in November by the UN resident_ _coordinator in Algeria uses the higher 173,600 figure to ensure humanitarian assistance is comprehensive._ ### **EGYPT** **Health** As medical needs continue to rise among new arrivals from Sudan, public health services are overwhelmed, and many individuals face high out-of-pocket costs. Underfunding means UNHCR will not be able to support some 16,100 refugee patients, including those chronic diseases who depend on monthly medications. Without this support, many lives are at risk. **Education** Currently, around 54 per cent of all school-aged arriving from Sudan are out of school. Education grants", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "These flood risk categories are defined in line with an approximation of the risk to the lives of affected people. Up to 0.15 meter inundation depth, no significant risk to life is expected. Up to 0.5 meter, some risk to life must be expected, especially for vulnerable groups such as children and the disabled. Up to 1.5 meters, a significant share of the affected population could face risk to life, especially if flood waters have a current. Above 1.5 meters, most affected people could face substantial risk to life without rescue measures. Through this process, each 90 by 90 meter cell of a country will be assigned one of the five risk categories (e.g. a pixel that has an estimated inundation depth of 5 cm is classified as low risk, while a pixel with depth 4.3 meters is classified as very high risk). This is repeated for the world’s landmass of 510 million square kilometers, which implies the processing of 63 billion pixels. **3.** **Assign flood risk categories to population headcounts at the pixel level and aggregate to the** **administrative unit:** As the flood hazard and population density maps are converted into the same spatial resolution, each population map cell", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "flood hazard and population density maps"}], "vague_data": []}}}
{"input": "discount rates have also been provided as a measure of the sensitivity of the analysis. 46 This corresponds to the average village population in similar areas according to the International Organization for Migration (IOM). This information can be accessed at Village Assessment Survey County Profiles. [https://iomsouthsudan.org/tracking/sites/default/publicfiles/documents/Lakes.pdf](https://iomsouthsudan.org/tracking/sites/default/publicfiles/documents/Lakes.pdf) _._ 47 Burden of Road Injuries in Sub-Saharan African _,_ [htp://pubdocs.worldbank.org/en/356861434469785833/Road-Safety-Burden-of-Injuries-in-Africa.pdf](http://pubdocs.worldbank.org/en/356861434469785833/Road-Safety-Burden-of-Injuries-in-Africa.pdf) _._ Page 26", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Figure 14. Economic value at risk, computed as exposure headcount multiplied by subnational income_ _per capita. Note: no subnational income data are available for several countries, including China._ **Exposure headcounts by income groups.** To address the bias that high-income areas have higher flood exposure in monetary terms, we consider flood exposure headcount disaggregated by national income classifications. The results, presented in Figure 15, show that 710 million people (or 48 percent) of the world’s flood exposed population live in lower- or lower middle-income countries. About 159 million (11 percent) of flood exposed people live in high-income countries. Considering that the flood exposed population in high-income countries is more likely to benefit from flood protection systems, social post-disaster assistance, and other risk management support, these figures highlight that monetary exposure estimates (including GDP) offer a distorted account of the distribution of global flood risks. 0 500 1,000 1,500 Millions _Figure 15. Number of people exposed to significant flood risk, disaggregated by national income level_ _classification_ 18", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "subnational income data"}]}}}
{"input": "of the GoR’s strategy – together with support from humanitarian and development partners – research shows that the impact of refugees in Rwanda on basic services, the environment and livelihood can be mitigated. Indeed, the refugee presence is generally associated with improved local economic conditions and access to services, without creating major social tensions. [2] 2. **The government’s strategic goal for refugee management is to promote self-reliance, however, major gaps** **remain in achieving this aim.** Data from the 2022 national census (which included a refugee module for the first time) and from the first round of a World Bank-led survey on refugee self-reliance showed that refugees generally enjoy good access to basic services such as education, health and water, but remain well short of self-reliance with respect to employment and income. [3] High poverty rates, lack of economic opportunity and limited access to finance in the refugee-hosting districts (RHDs) constrain employment and income-generating prospects for refugees and host communities alike. Building on the success of the ongoing Phase I of the World Bank-financed Socio-economic Inclusion of Refugees and Host Communities in Rwanda Project (P164130) (known in Kinyarwanda as “Jya Mbere” or “move forward”), Phase II will support self-reliance for refugees", "output": {"entities": {"named_data": [{"text": "2022 national census"}, {"text": "first round of a World Bank-led survey on refugee self-reliance"}], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) **D. Results Chain** **Assumptions** **Figure 3: Results Chain** i. Political and Governmental Support: The government of Costa Rica will continue to prioritize education. ii. Stability of the Project Implementation Unit: The Project Implementation Unit will remain stable, with consistent leadership and staffing levels, and will be able to effectively coordinate with the IDB, internal and external stakeholders. iii. Community and Stakeholder Engagement: There will be buy-in from key stakeholders, including educators, students, parents, and the community at large, for the education technology reforms. **E. Rationale for Bank Involvement and Role of Partners** 39. **The Bank has a long-standing partnership with the Government of Costa Rica on education and can leverage** **global experience in the implementation of education sector reforms.** This Project builds on and complements prior Bank support to Costa Rica on education, including the Costa Rica Higher Education Improvement Project (P123146, Loan 8194CR) and on governance under the Costa Rica Fiscal Management Improvement Project (P172352, Loan 9075-CR). 40. **Collaboration with development partners will be key for the preparation and implementation of this Project.** The Project is designed in parallel to an IDB financed project. Both projects are self-standing and", "output": {"entities": {"named_data": [{"text": "Costa Rica Higher Education Improvement Project"}], "descriptive_data": [], "vague_data": []}}}
{"input": "an economically viable area. Results from various studies such as the 23 Zambia 2022 Census of Population and Housing, Central Statistical Office Zambia, 2023. 24 One Meheba Local Area Plan, Planning Survey and Issues Report, GRZ, 2023. 25 One Meheba Local Area Plan, Planning Survey and Issues Report, GRZ, 2023. 26 “Many girls choose not to attend classes at certain times due to the lack of appropriate washing and hygiene facilities,” School headmaster, Kalumbila District, February 2024. Page 16", "output": {"entities": {"named_data": [{"text": "23 Zambia 2022 Census of Population and Housing"}], "descriptive_data": [], "vague_data": []}}}
{"input": "strong spillover effects. The lack of visible spillover effects casts doubt on the theory that repurchases are being driven by increased trust in the insurance company or learning about insurance payouts. Notably, this result stands in contrast to recent results that do document spillover effects of insurance payouts (Cole, Stein, and Tobacman 2014; Karlan et al. 2014). Direct Effects of Payouts on Wealth and Liquidity The previous two sections discount the possibility that trust, learning, or weather effects are driving the result that receiving an insurance payout is correlated with purchasing insurance the following year. This points to the actual reception of money from the insurance company as being the driving force behind greater take-up. The most natural explanation for this phenomenon would be that receiving an insurance payout could directly affect choices the next year due to its effects on wealth and liquidity. For instance, if insurance is a normal good, then increased wealth would result in greater insurance demand. [18] Although the BASIX data set does not offer the opportunity to test the direct effects of a cash payment separately from an insurance payout, there are a number of reasons why it is unlikely that wealth or liquidity", "output": {"entities": {"named_data": [{"text": "BASIX data set"}], "descriptive_data": [], "vague_data": []}}}
{"input": "data on slum location to examine the distribution of exposure across poor and non-poor locations. While prior studies have examined flood risk in Vietnam, this paper provides two main contributions. First, we develop new high-resolution flood hazard datasets, which incorporate both riverine and coastal flooding and consider climate change. [1] When examining flood exposure, it is important to get as local as possible as impacts can vary widely across space - for instance, impacts can be different from one city block to the next (Patankar 2015). This 1 Prior use hazard data at a 1 km resolution and are restricted to a single district or city within Vietnam (Chinh et al. 2017; Apel et al. 2016). We develop new high-resolution flood hazard datasets on a 90 m × 90 m grid.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "high-resolution flood hazard datasets"}], "vague_data": [{"text": "data on slum location"}, {"text": "flood hazard datasets"}]}}}
{"input": "not owned, significant and quantitatively large investment disincentives persist and cause productivity losses of considerable magnitude. This makes it important to explore other ways of bringing investment levels on such land closer to the social optimum. To explore this, our survey asked households who occupied land under usufruct about their willingness to pay to acquire full ownership rights. Results, as reported in table 7, suggest that 40% of 2,804 owners were willing to pay for about 37% of the 4,478 occupied parcels overall or 43% of the 1,519 parcels under freehold or _mailo_ . The median willingness to pay, US$ 215/acre for customary and US$ 269 per acre for _mailo_ or freehold land is surprisingly large, both if compared to owners’ median self-assessed value of US$ 403/acre. It is also high in view of the fact that, at least in the case of _mailo_ or freehold, the economic value of landlords’ residual claims to a perpetual ground rent of about US$ 0.6 annually is minuscule. Although part of the stated willingness to pay could have its origin in non-economic values of land ownership, the fact that a large number of households are willing to spend large amounts of 19 As", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "United Nations Development Programme (UNDP) Needs Assessment, [27] UNHCR Socioeconomic Survey, [28] the UNHCR Gap Analysis, [29] and the outcome of a stakeholder consultation process revealed that rehabilitation of settlement roads is the priority development need across all communities. The project will improve the 38 km of rural road from the Meheba junction on the T5 Solwezi-Mwinilunga Road to the Mwafwe River located at the southern border of the settlement. Construction will be done to a climate-resilient standard, to withstand damage from flash flooding, including, for example, adopting a robust drainage and camber design and ensuring their periodic maintenance. The approach is in line with Zambia’s Climate Adaptation Plan which seeks to promote the application of climate-smart codes for roads development nationally. It will also provide a bridge over the Mwafwe River to facilitate access to communities in the Matebo Ward to the immediate south of the settlement [30] and improve their resilience to climate change impacts such as flash floods. An assessment will ensure that the bridge is engineered to withstand flooding and erosion risk. Rural road improvement will also contribute significantly to creating links—increasing the opportunity to access goods and services located in nearby Solwezi and other markets,", "output": {"entities": {"named_data": [{"text": "UNHCR Socioeconomic Survey"}, {"text": "UNHCR Gap Analysis"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Economics of Disasters and Climate Change paper contributes to the growing literature in economics on the assessment of local and disaggregated disaster impacts (e.g. Del Valle et al. 2018 using wind speed), and is the first to our knowledge examining flood risk at this scale in a developing country. Second, we analyze how flood exposure differs based on socioeconomic dimensions, in this case poverty, at the country and city-level. In both cases, we examine how flood exposure and poverty differs spatially across the country (at the district level) but also within HCMC (by identifying slums). The combination of these two datasets on hazard and poverty - typically kept separate in the literature – is another main contribution of this paper. The consideration of socioeconomic characteristics and the focus on the poor is an important one as not all segments of the population are equally exposed and vulnerable to floods. In some cases, people living in risky places may be richer than the average population: for instance, urban residents are on average wealthier than those living in rural areas (World Bank 2009). At a more local scale and especially within cities, land and housing markets often push poorer people to settle", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "IDA Credits and Grants”, dated October 15, 2006, and revised in January 2011 and as of July 1, 2016 (Anti-Corruption Guidelines), and beneficiary ownership disclosure requirements. The project will use the Systematic Tracking of Exchanges in Procurement (STEP) system to provide data on planned procurement activities, establish benchmarks, monitor delays, and measure procurement performance. 77. **A Project Procurement Strategy for Development (PPSD) has been prepared by the Recipient.** The PPSD highlights the market, procurement risks, procurement options, and selection methods to be followed by the IAs during implementation of the Procurement Plan. The Procurement Plan for the first 18 months is annexed in the PPSD and will be updated at least annually or as required to reflect changes in the AWPB. 23 The Auditor General’s report for DRDIP I for the year ending June 30, 2024, identified network challenges and unstable electricity in Madi-Okollo, Obongi, Terego, and Kibuuke districts. 24 The audit reports for 2022/2023 that had an unqualified (clean) audit opinion were for Isingiro, Kamwenge, and Obongi districts. 2023/2024 audit reports were not available on the Auditor General’s website. The audit reports for 2023/2024 that had an unqualified (clean) audit opinion were for Adjumani, Kikuube, Kiryandongo, Koboko, Kyegegwa, Lamwo,", "output": {"entities": {"named_data": [{"text": "Systematic Tracking of Exchanges in Procurement"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Economics of Disasters and Climate Change vulnerability even as the climate change hazard increases (Hallegatte et al. 2016). Along these lines, while we examine which regions within Vietnam have the highest flood exposure, we do not examine the determinants of vulnerability (other than poverty). Recent analyses suggest that the Northwest, Central Highlands, and Mekong River Delta have the greatest socioeconomic vulnerability (World Bank 2010). In the flood hazard maps developed for this paper, we assume no protection due to a lack of data and as a result the hazard maps present an upper bound of flood exposure. Work is currently ongoing to develop a global database of flood protection, and this information can be mobilized for future work (Scussolini et al. 2016). For the national-level analysis, flooded areas are defined as any area with inundation higher than 0. We have not yet explored the depth dimension, although the flood hazard maps developed for this study allow for this potential in future work. For the HCMC analysis, the location of the slum areas in the PUMA data set are mainly restricted to the old town. Furthermore, slum areas are often difficult to define (with PUMA only identifying potential slums) and the", "output": {"entities": {"named_data": [{"text": "PUMA data set"}], "descriptive_data": [{"text": "global database of flood protection"}, {"text": "flood hazard maps"}], "vague_data": []}}}
{"input": "zones by constructing a buffer around each storm polyline whose width is the storm’s radial distance from center to the zone of maximum wind speed. For high-resolution location of landfalls, we construct a coastal boundary polyline for Bangladesh, West Bengal and Odisha. Then we convert the coastal polyline into points spaced evenly at intervals of .001 decimal degrees (approximately 100 meters). The resulting set of ordered points along the coastline is numbered successively from 0 (southern tip of the Odisha coastline) to 11,327 (southern tip of the Bangladesh coastline). For each storm track, we identify the landfall as the closest ordered point where the track first intersects the coastline. [3] To guard against exclusion bias from regional bounding, we include intersecting storm tracks within 20 km of the southernmost coastal points in Odisha and Bangladesh. We identify a storm’s coastal impact zone as the set of ordered coastal points within the radius-buffered storm track polygon at its first coastal intersection. **3. Aggregate Results** **3.1 Trend in Cyclonic Storm Incidence, 1877-2016** Although we focus on the northern coast of the Bay of Bengal, our database includes all recorded tracks for the Bay of Bengal and Arabian Sea. This provides a very", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) **I.** **STRATEGIC CONTEXT** **A. Country Context** 1. **Costa Rica has been one of the most politically stable, progressive, and prosperous nations in the Latin America** **and the Caribbean (LAC) region.** Successive administrations have prioritized the social welfare and development of the Costa Rican people. Political stability, the social compact, and steady growth have resulted in one of the lowest poverty rates in LAC (2023 poverty headcount rate at upper middle-income poverty line was 12.7 percent). [1] The country of 5.33 million inhabitants became a member of the Organisation for Economic Co-operation and Development (OECD) in 2021. The economy is diverse, and based mainly on services, tourism, and exports of products such as electronics and medical devices. Trade (Exports+Imports) formed 80 percent of Costa Rica’s Gross Domestic Product (GDP) in 2022 (compared to 57 percent for LAC) [2] and the country has also built a world renowned “Green Trademark” centered on conservation, reforestation, and protected areas. 2. **The country has recovered quickly from the COVID-19 shock on key macroeconomic indicators, but it faces new** **challenges such as heightened migrant and refugee flows** . The unemployment rate reached a high of 20", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "### **ALGERIA** **Protection** CRITICAL FUNDING NEEDS IN MENA / 10 OCTOBER 2024 Critical funding need: **$5.5 million** Refugee access to crucial legal and identity documents will be diminished, severely restricting their access to essential services and increasing their vulnerability. For instance, UNHCR has registered 2,455 individuals so far in 2024, but the average waiting time for the asylum-seeking process is currently 126 days, while registration takes around 156 days. Without additional funding, these delays could be prolonged, leaving people in legal limbo and unable to work or access rights. GBV survivors and others at risk will not have access to safe shelters, psychosocial support, medical care, or access to economic opportunities to facilitate their effective reintegration into the community. **WASH** UNHCR supports the entire refugee population in the five camps near Tindouf – more than 90,000 refugees [1] - with lifesaving health and WASH activities. UNHCR will be unable to replace deteriorating reservoirs, extend the water distribution network, or enhance water storage and management. This would lead to increased risks of water shortages and contamination, endangering the health of the refugees. Substandard waste and sanitary management would also pose significant health hazards to the camp residents. Access to quality obstetric", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "EA were randomly sampled. As table 1 illustrates, 5,530 of the sample households were involved in agricultural activities. Of these, about 31%, or 1,728 with 5,448 parcels, are mixed owner/occupants who operated at least one parcel under full ownership and one under usufruct. This sub-sample forms the basis for our analysis. Descriptive statistics point towards a number of interesting features. First, cultivation of land that is only occupied rather than owned is widespread; only some 49% of cultivators are pure owners, 20% cultivate only occupied land, and about 31% are owner-cum-occupants who cultivate owned and occupied land simultaneously. Second, although per capita expenditure by those in agriculture is, with about 19 12 To check whether this introduces any non-randomness, we compare total asset endowments and their composition, monthly consumption expenditure, and basic demographic characteristics between households who are included and those who have at least some parcels dropped. And find no significant differences in either of them. 13 Information on crop output was collected at the crop level, separately for the two main agricultural seasons (July - December 2004 and January - June 2005). A diary was used for continuously harvested crops and prices, in addition to standard socio-economic information,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The Regional Bureau for East and Horn of Africa, together with the Child Protection Unit at HQ, organised a series of regional webinars for UNHCR staff on increasing the quality of alternative care and responding to the needs of newly separated children in the region, in addition to engaging community volunteers in the development of Best Interests Procedures. The Refugee Child Protection Online Community of Practice has been updated by the Child Protection Unit at HQ to provide COVID-19 related news, guidance, tools and other information. The Community of Practice encourages child protection workers and managers to contribute questions, recommendations, field practices, and guidance so that, collaboratively, continually improving child protection responses during the COVID-19 pandemic can be shaped and better outcomes achieved. With global partners, and support from the Swiss Government, UNHCR’s Child Protection Unit developed a Massive Online Open Course (MOOC) on adapting child protection case management during the pandemic. Targeting frontline workers, the six-week course provides practical guidance and peer exchange on key approaches to responding to the protection needs of individual children at risk. As of mid-July, over 7,000 individuals were registered to participate in the course. UNHCR also provided input into the Alliance for Child", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the importance of: (i) investing in often underserved host communities to strengthen social cohesion; (ii) communicating project benefits and managing misinformation; and (iii) mitigating the risks of traditional livelihood activities, due to their long production cycles and exposure to externalities, such as climate change. The project will also build on lessons from **the Integrated Cash Transfer and Human Capital Project (PITCH)** (P166220), implemented in Djibouti from 2018 to 2023, which: (i) established the foundations of a social registry (SR), addressing challenges like data accuracy and inclusion errors; (ii) demonstrated the effectiveness of integrating cash transfers with social behavior change communication (SBCC) and community-based measures to enhance outcomes in nutrition, child health, and education; and (iii) highlighted the success of training advising mothers in improving behaviors such as exclusive breastfeeding and health service utilization. The PITCH further demonstrated Djibouti’s capacity to implement small community-driven infrastructures while revealing communities' need for larger and more sustainable infrastructure. The project will also learn from other operations currently under implementation, which are implementing in underserved and refugee-hosting areas, including: (i) Skills for Development (P175483), which seeks to improve the employability and employment outcomes of technical and vocational education and training graduates, as well as (ii)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "systems, covering at least 11,200 hectares of land. 21 The AI Model was produced under the Enhancing Self-Reliance and Preparedness for Forced Displacement in the Great Lakes Region Advisory Services and Analytics (P500793). Data and analysis from the model, if rendered live, could also be used to support monitoring, evaluation, and analysis of change in public service pressure, forestry cover, poverty, and other social, economic and environmental issues. Page 9", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Regional and Global Vulnerability of Coastal Zones to Climate Change and Sea-Level Rise (DINAS-Coast) project. In particular: _Country boundaries and regions and coastlines_ . Country coastlines were extracted from the World Vector Shoreline, a standard National Geospatial Intelligence Agency (formerly Defense Mapping Agency) product at a nominal scale of 1:250,000. World Bank (2010) information is used in the regional classifications and boundaries. In addition, Exclusive Economic Zone data from VLIZ (2011) identifies the maritime boundaries. _Elevation._ For elevation, all coastal tiles of 90m Shuttle Radar Topography Mission (SRTM) data, which are 5 geographic degrees latitude and longitude (approximately 500 kilometers by 500 kilometers), were downloaded from http://srtm.csi.cgiar.org/. _Wetlands._ Data on wetlands were extracted from all wetlands Global Lakes and Wetlands Database (GLWD-3) produced by the Center for Environmental Systems Research (CESR), 6", "output": {"entities": {"named_data": [{"text": "World Vector Shoreline"}, {"text": "90m Shuttle Radar Topography Mission (SRTM)"}, {"text": "Global Lakes and Wetlands Database (GLWD-3)"}], "descriptive_data": [{"text": "Exclusive Economic Zone data from VLIZ (2011)"}], "vague_data": []}}}
{"input": "**The World Bank** Uganda Development Response to Displacement Impacts Project Phase II (P510476) PROJECT APPRAISAL DOCUMENT savings and timely repayments, contributing to the growth of the revolving fund. Savings of up to US$1.20 per month per beneficiary are expected to be mobilized throughout the project's six-year lifespan, bringing the PCM to US$10 million. The same sub-component is also verified as Private Capital Enabling. It will strengthen Producer Organizations (POs) and establish Cluster Value Chain Facilities. It is expected to increase access to formal finance for project-supported institutions, including POs, Common Interest Groups (CIGs), and Village Revolving Funds (VRFs). This is captured under a non-monetary results indicator (Project-supported institutions that access formal finance (number)), which measures the capacity of group-based enterprises to engage with formal financial institutions. 11. **Uganda remains eligible to access financing from the IDA WHR** . The World Bank, following consultations with the United Nations High Commissioner for Refugees (UNHCR), has determined that Uganda’s refugee protection framework remains adequate for the purposes of the WHR. The Refugees Act Cap 312 and the 2010 Refugee Regulations provide a strong legal and regulatory framework for refugee rights. However, UNHCR protection assessments have raised concerns that will need to be addressed", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "exposure of wetlands to a 1 m SLR. Low elevation wetlands are within the Low Elevation Coastal Zone [17] . For the area calculation, grids representing cell areas in square kilometers at different resolutions were created, using the length of a degree of latitude and longitude at the cell center. [18] According to the GLWD-3 and the DTM, 76 countries and territories in five World Bank regions have coastal wetlands which are currently at 1 m from sea level. In the DIVA database, wetlands are not located within the most extreme responses: WMP1 or WMP5. If wetlands can migrate (WMP category 2), then they may survive in their current location to the extent that natural migration or wetland accretion keeps pace with sea-level rise (Titus, 1988). Wetlands in WMP category 3 cannot migrate, and the human resources 17 Coastal zone with elevation derived from SRTM which is 10 or less meters above sea level. 18 Latitude and longitude were specified in decimal degrees. The horizontal datum used is the World Geodetic System 1984 (WGS 1984). 9", "output": {"entities": {"named_data": [{"text": "GLWD-3"}, {"text": "DIVA database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "(2024). _Rwanda Finscope 2024_ . 38 https://genderdata.worldbank.org/en/home 39 Republic of Rwanda (2024) _Labour Force Survey Q3 2024_ : file:///C:/Users/wb236615/Downloads/LFS%202024~Q3.pdf 40 In Rwanda, men on average carry out 12.8 hours of productive work and 11.6 hours of household work, for a total of 24.4 hours a week. Women, in contrast, carry out an average of 14.9 hours of productive work and 29.6 hours of household work per week, for a total of 44.5 hours a week. USAID/VOICE. Gender Analysis, 2015. Page 19", "output": {"entities": {"named_data": [{"text": "Labour Force Survey Q3 2024"}], "descriptive_data": [], "vague_data": []}}}
{"input": "former refugees in Zambia.** **[10]** The majority of refugees and asylum seekers originate from the Democratic Republic of Congo; other significant refugee populations are from Burundi, Somalia, Angola, and Rwanda. Zambia continues to receive new arrivals of refugees and asylum seekers—approximately 600–800 refugees arrive each month from the South Kivu, Haut-Katanga, and Tanganyika provinces in the Democratic Republic of Congo. Women and children make up 58 percent of refugees, while 3 percent are elderly and persons living with disabilities. 8. **Former refugees are people who escaped civil war in Angola and Rwanda in the 1994 genocide against the Tutsi** **who have lived in Zambia for several decades** . Their refugee status has ceased, making them effectively stateless and facing multiple barriers to accessing livelihood opportunities and services. The requirement to have national identification or residence documents has been an impediment for many former refugees. Many former Rwandan refugees fear returning to their home country while application fees for passports are unaffordable for many. The GRZ has offered to integrate former Angolan refugees who arrived between 1966 and 1986. However, most of those who arrived after 1986 do not have any form of identification. The risk of statelessness extends to children", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Integrated Community Resilience Project (P506969) PROJECT APPRAISAL DOCUMENT **I.** **STRATEGIC CONTEXT** **A. Project Strategic Context** 1. **Djibouti, a small country of 23,200 square kilometers with a population of approximately 1 million,** **faces** **significant poverty challenges, particularly in rural areas, where 27.2 percent of the population resides** . Strategically located at the southern entrance to the Red Sea, it acts as a bridge between Africa and the Middle East and hosts multiple foreign military bases supporting global anti-piracy. However, recent geopolitical tensions have reduced commercial ship traffic, leading to increased food prices and reduced availability of essential goods, disproportionately affecting the most vulnerable. These challenges are compounded by limited economic diversification, scarce arable land and low annual rainfall, which result in heavy reliance on imports for basic needs like water and food [1] . As a result, the economy remains highly vulnerable to external shocks, including market downturns. Additionally, climate change exacerbates existing pressures, with rising temperatures and erratic rainfall further straining local resources and food security. 2. **These economic and climate constraints contribute to persistently high levels of inequality and social** **vulnerability** . Using the World Bank poverty line for Low Middle-Income Countries (LMIC) of US$3.65 a", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "World Bank poverty line for Low Middle-Income Countries"}], "vague_data": []}}}
{"input": "not reached. In addition, 77% of the funding requirement MA interventions is not met. - There is also a **lack of human resources dedicated to coordination at national and regional** **level, prevention, and assistance to victims** . The MA Sub-Cluster has not been functional since the withdrawal of UNMAS in early November 2022, despite joint coordination efforts between CNCCAI and MA actors including Mines Advisory Group (MAG) and Humanity and Inclusion (HI) 8 Dashboard des réalisations de protection, cluster Protection, Avril 2023", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "risk will primarily involve moderate-to-** **intermediate scale for the construction and/or rehabilitation of socio-economic infrastructure, a limited number of** **consultants for technical assistance, and some goods.** MASS and ADDS have prepared a dedicated Project Procurement Strategy for Development (PPSD) and a procurement plan detailing procurement-related activities. Both agencies have prior experience with World Bank financing handling procurement, though at varying scale. However, there have been recurrent delays in procurement processing and reporting for both agencies, leading to the assessment of procurement risk at this stage as substantial. To mitigate this risk, the procurement officers of each agency will receive close follow-up and support from the World Bank to ensure appropriate procurement planning and implementation. Page 24", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "of Infrastructure, etc.). The PSC will sign off on the Annual Work Plan and Budget (AWPB) and ensure consistency with national standards and policies across the different sectors, including the upcoming GoR Refugee Graduation Strategy. Complementing the PSC will be a Project Technical Committee, which comprises the same agencies as the PSC, but with technical level staff. The PTC will meet prior to PSC meetings to review progress reports and AWPBs in detail. **Figure 1: Implementation Arrangements** Page 14", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Economics of Disasters and Climate Change Exposure to flooding was again evaluated using flood extent (we also evaluate flood depth, for full results, see online supplementary materials). We examine the flood extent both for all urban areas (the whole HCMC province) and for those areas defined as potential slums (from the PUMA data set) to examine how exposure to floods is different in slum areas. Again we use a number of events, from the case of regular flooding (10-year event) to more extreme flooding events (1000-year event). Moreover, we examine how this exposure changes due to climate change (proxied by sea level rise changes), by running the analysis with flood hazard maps taking into account a 30 cm sea level rise. In each district and across the whole city, we examine the percentage of area within each of the two categories (all urban areas, and potential slum areas) that is exposed to floods and the percentage which is not exposed to floods. We then compare these values across the two categories. Results National-Level Analysis for Poverty and Exposure to Floods Flood Exposure (with and without Climate Change) For the entire country of Vietnam, at the district level, we estimate the", "output": {"entities": {"named_data": [{"text": "PUMA data set"}], "descriptive_data": [{"text": "flood hazard maps"}], "vague_data": []}}}
{"input": "Refugees (UNHCR), has determined that Uganda’s refugee protection framework remains adequate for the purposes of the WHR. The Refugees Act Cap 312 and the 2010 Refugee Regulations provide a strong legal and regulatory framework for refugee rights. However, UNHCR protection assessments have raised concerns that will need to be addressed through humanitarian and development financing, including poor water and sanitation conditions, social service deficits, cuts to food rations, and a reduction in activities promoting self-reliance. **II.** **PROJECT DESCRIPTION** **A. Project Development Objective** 12. To improve access to basic social and economic services, expand economic opportunities and enhance environmental management for host communities and refugees in the target areas. **B. Theory of Change and PDO Indicators** 13. The Project Development Objective (PDO) indicators are: - Displaced people and people in host communities provided with improved access to services (number, of which refugees, host community members, and women (percentage)) (corporate scorecard indicator); - Households benefiting from activities and actions that expand and enable economic activity (number, of which refugees, host community members, and women (percentage)); and - People benefitting from enhanced resilience of terrestrial and aquatic systems (number, of which refugees, host community members, women, and youth (number)) (corporate scorecard indicator). **Theory", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "of these analyses present estimates of the economic values, which may be associated to these lost wetland areas around the world. The valuation studies by Tol (2007) and Anthoff et al. (2010) are also based on wetland losses derived from the Global Vulnerability Analysis (Hoozemans et al. 1993). Wetland value is assumed to be logistic in per capita income, with a correction for wetland scarcity, and a cap in these studies and the rate of pure time preference is assumed to be 1%. For a 1m SLR by 2100, Tol (2007) estimated annual costs of wetland loss as a percentage of GDP, per country and Anthoff et al (2010) assessed the net present value of global coastal wetland damage costs for the period 2005-2100 with dikes to protect against SLR can be as high as USD 160 billion. [ 25] Due to uneven coverage of the wetland stock and different assumptions of coastal protection, comparison of the prior research with our estimates proved to be difficult. ##### **Conclusion** Coastal wetlands will decline with rising sea level. In this paper, we have quantified the vulnerable freshwater marsh, swamp forest, GLWD Coastal Wetlands, and brackish/saline wetlands taking into account the exposure of", "output": {"entities": {"named_data": [{"text": "Global Vulnerability Analysis"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Full results are presented in Table 3. But these national results on exposure are not evenly be distributed across the country. The spatial analysis also allows us to examine which districts have the highest absolute and the highest relative exposure. We present results for the 25-year flood, for a historical and a high 6 Results presented are similar to a previous study analyzing the exposure to a 100-year return period flood without climate change impacts, which finds 40 million people to be exposed to that event (Jongman et al. 2014). While we had planned to compare our simulated results with national statistics, these statistics were unavailable at the time of analysis. However, we consulted our findings with individuals familiar with the Vietnam context who ended to agree that the numbers were in the range of plausible estimates.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In order to improve the situation, ideally information on (i) high spatial resolution of the coastal zone elevation, (ii) high spatial resolution of wetlands, (iii) clear delineation of current wetlands and (iv) location specific information on the wetland migratory potential are necessary. High spatial resolution of the coastal zone elevation will refine the estimates of exposed area to SLR. High spatial resolution wetlands information would allow a more accurate correspondence between the exposed area of SLR and wetland area. Precise delineation of wetlands is generally difficult from remotely sensed data and land cover data. Remotely sensed data measure the vegetation, but may not account for the soil type and the wetland plants may not be easily distinguished by remote sensing. Land cover products are often produced from composite imagery over a time period, so the frequency of the data or the smoothing of multiple observations may make the wetland delineation difficult. In addition, location specific information on the Wetland Migratory Potential would add accuracy to the areas where wetlands can migrate (e.g. excluding human altered landscapes such as urban areas). ###### **III.3 Economic losses** As indicated earlier, wetlands provide a flow of goods and services, which contribute to the welfare", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "land cover data"}, {"text": "remotely sensed data"}]}}}
{"input": "(5) Total annual regionally adjusted household expenditure (local currency, regionally deflated). (6) Total food expenditure (nondeflated). (7) Total housing expenditure (nondeflated). (8) Total health and education expenditure (nondeflated). (9) Total household energy expenditure (gas and electricity) (nondeflated). *** p<0.01, **p<0.05, *p<0.1. All regressions control for year and district fixed effects, urban dummy, age, and years of education. **7. Robustness for district-level estimations** **7.2 Using production levels** We continue by exploring the effects of mining intensity as proxied by district-level production volumes. The estimation will be similar to equation (2), but we replace the indicator variable for being an active mining district with annual gold production in the district: Y��� - β�gold_production�� - ∝�� g� �λX�� �ε��� �4� The measure of gold production is in 10 tons of gold produced, and gold_production�� is either _gold_year_district_, which equals the total production of all mines in a district in the different survey years, or _gold_period_district_, which equals total production for the years before the survey. For the 1993 survey, the period is 1990–93, for 1998 it is 1994–98, and so on. Using production levels instead of an indicator of having any production in the district has the advantage of capturing the intensity of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "by the recipient (such as limited/restricted competitive bidding, request for quotations/shopping, direct contracting), will be consistent with the requirements set out in paragraphs 5.3 and 5.4 d. as appropriate. 13. **Publication (advertising).** The recipient is required to prepare and submit to the World Bank a General Procurement Notice. The World Bank will arrange for its publication in the United Nations Development Business online (UNDB online) and on the World Bank’s external website. Specific Procurement Notices for all procurement under international competitive procedures and requests for expressions of interest for all consulting services, estimated equivalent to US$300,000 and above, will be published in UNDB online and on the World Bank’s external website and at least one newspaper of national circulation in the recipient’s country or in the official gazette or on a widely used website or electronic portal with free national and international access. 14. **Procurement implementation arrangements.** The project does not foresee complex procurement activities. The hands-on experience gained under Government funded project will pave the way for improvements in organizing and performing the procurement functions more professionally to achieve the PDO. MoHAIS will delegate financial and Page 41", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "wetlands and GLWD Coastal Wetlands of SA amount to 900 and 840 square kilometers respectively. GLWD coastal wetlands Brackish / saline wetlands Square kilometers Square kilometers 10000 1969 SubSaharan Africa 938 Latin America & the Caribbean 8000 6000 4000 2000 0 1278 SubSaharan Africa Square kilometers 12000 10000 8000 6000 4000 0 East Asia & the Pacific 691 Latin America & the Caribbean East Asia & the Pacific Freshwater marsh 10085 2217 4 7159 Middle East & North Africa 862 SubSaharan Africa 847 South Asia 12402 East Asia & the Pacific 2619 Middle East & North Africa 8000 6000 4000 2000 0 903 South Asia South Asia Middle East & North Africa 2908 Latin America & the Caribbean 2000 0 **Figure 1. Lost wetlands by types of wetlands and regions, for a 1m SLR** Freshwater marsh GLWD coastal wetlands Brackish / saline wetlands East Asia & the Pacific South Asia Middle East & North Africa Latin America & the Caribbean South Asia Middle East & North Africa Latin America & the Caribbean East Asia & the Pacific South Asia Middle East & North Africa Latin America & the Caribbean **Figure 2. Distribution of lost wetlands by types of wetlands across", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "in Africa. The probability of adoption of irrigation increases in regions with lower temperatures (for example Egypt and South Africa), while it decreases in warmer regions. Irrigation in cooler regions is more profitable because it requires less water and the crops are more productive. Similarly, in regions of higher precipitation or available flow, the probability of adopting irrigation decreases. Irrigation is less profitable in wetter locations because the fixed cost of irrigation remains the same but the net increment to production declines. In the probit model, we controlled for water flow by including the log transformation of a long run average (30 years) of estimated mean flow. The coefficient on this variable is positive and significant. In the selection model, we also controlled for soils. The soil variables reflect the proportion of a district with a particular soil type. The inclusion of certain soils specific to a particular region or district results in the model not being full rank (thereby making the interpretation of the statistical significance of the coefficients unreliable). As a result, we included only those soils that are jointly significant for both irrigated and dryland farms. We then turned to estimating the second stage model of net", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "agricultural extension officers from MoA. (b) **Co-investments in subprojects.** While all eligible farmers and cooperatives will receive TA, only a subset will receive investment from the project for assets or working capital. Eligible farmers will be incentivized to apply for financing through well-organized cooperatives, common interest groups or producer groups. Eligibility criteria might include (i) businesses already operating with well-maintained financial records, (ii) climate-smart business plan, (iii) potential demand for products or services, (iv) financial viability and technical feasibility of business plan, (v) willingness to take up climate adaptation and mitigation measures, and (vi) preference for women and youth. Precise selection criteria will be developed by the service provider in consultation with local officials from the MoA, with proposals screened by a committee of local sector experts. Up to 70 percent of business proposals will be funded through the project. The co-investee farmers or cooperatives will receive additional technical support on the operation and maintenance of purchased assets. A grants’ manual will be developed. 36 World Bank. 2023. _Zambia Gender Assessment_ . 37 Finscope Survey 2020 and in-person consultations at Meheba settlement 2022/23. Page 19", "output": {"entities": {"named_data": [{"text": "Finscope Survey 2020"}], "descriptive_data": [], "vague_data": []}}}
{"input": "spent migrating. Finally, reforms contributed to higher agricultural yields and profits through three channels, namely (i) greater rental market activity that transferred land to more productive producers; (ii) substitution of purchased inputs for labor; and (iii) a shift out of grains towards vegetables, corn, and oilseeds, all of which offer higher levels of profitability. All of these findings are consistent with the notion that, without reforms, tenure insecurity and transaction cost in factor markets undermined investment and functioning of land and labor markets, preventing high value peri-urban land from being used most effectively and reducing job creation, especially for the less affluent and educated. As China considers how to build on what has been achieved, pilot results point to important substantive lessons in terms of key elements of reform implementation and elements of what has been done in Chengdu reform are thus likely to form an integral part of any future reform package. While we can only estimate impacts of the entire reform package rather than individual components, careful design of future reforms, with an emphasis on evaluation right from the start, could help to further enhance lessons 18 Reform-induced increases in supply of (young) own labor noted above are", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) according to the National Household Survey data for age cohorts from the National Institute for Statistics and the Census, while a little over 40 percent of individuals aged 55-59 in 2023 had completed at least lower secondary education (9 years of education), this number more than doubles to 85 percent of 20-24 year olds. The 2020 Human Capital Index shows that a child born in Costa Rica can expect to be 63 percent as productive with the current education and health services as he or she could be if he or she enjoyed complete education and full health, which is slightly higher than the LAC average of 60 percent. [9] Costa Rica aspires to go beyond being among the best in the LAC region, to be on the global vanguard of the digital age, with education outcomes on par with the OECD, a highly skilled workforce, and a transformative digitalization and management agenda. **Foundational Learning** 5. **National assessments show weakness in foundational learning, and learning outcomes are strongly correlated** **to socioeconomic conditions, which points to the need for foundational learning with deeper attention to the education** **outcomes of students from", "output": {"entities": {"named_data": [{"text": "2020 Human Capital Index"}], "descriptive_data": [{"text": "National Household Survey data for age cohorts"}], "vague_data": []}}}
{"input": "and often complex. [5] The rapid loss of the global coastal wetland stock in the 20 [th] century was primarily caused by direct land reclamation. While significant losses due to human actions are likely to continue in the future, it is projected that stresses on wetland areas may be further aggravated in the 21 [st] century due to climate change. Wetlands face a number of hazards including rise in sea-level, increased atmospheric 4 A precise and widely agreed upon definition of wetland is not available. RAMSAR convention, a UNESCO-based intergovernmental treaty on wetlands adopted in 1971, defines wetlands as (Article 1.1): areas of marsh, fen, peatland or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish or salt, including areas of marine water with the depth of which at low tide does not exceed six meters, and highlights (in Article 2.1) that wetlands may incorporate riparian and coastal zones adjacent to the wetlands, and islands or bodies of marine water deeper than six meters at low tide lying within the islands. 5 These causes include sea-level rise, waves, erosion, subsidence, storms and biotic effects. Human actions include drainage for agriculture & forestry,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "#### **Impact of Property Rights Reform to Support China’s Rural-Urban** **Integration:** **Household-Level Evidence from the Chengdu National Experiment [¶]** Klaus Deininger [†], Songqing Jin [‡], Shouying Liu [♯], Fang Xia [♦] †World Bank, Washington DC ‡Michigan State University, East Lansing MI ♯Development Research Center of the State Council, Beijing ♦Central University of Finance and Economics, Beijing **JEL Codes O1, O43, R14, R3** **Keywords: Urban development, land use change, China, financial development** - Email: kdeininger@worldbank.org; jins@anr.msu.edu; liusy@drc.gov.cn; xia.fang.fx@gmail.com. We thank NBS, in particular Pingping Wang, Wei Wu, Yilin Feng, and Jianliang Di, as well as the Chengdu Statistical office, especially Taixiang Zhao, Xiaoying Gu, Yuan Lin, Yufang Chen, Qiuyan Chen, and Shiming Ren for access to data and support, Ting Shao for communication with NBS and the Chengdu Statistical office, and Yihao Li for research assistance. Funding support from the Knowledge for Change Program is gratefully acknowledged.", "output": {"entities": {"named_data": [{"text": "Chengdu National Experiment"}], "descriptive_data": [], "vague_data": []}}}
{"input": "(1.614) Effect of payout at average payout 3.46 1.68 1.75 4.17 3.55 0.63 Observations 1534 1534 1534 459 459 459 R-squared 0.061 0.118 0.047 0.084 0.285 0.069 _Notes_ : Observations are aggregated at the village level. The dependent variable is the number of insurance purchasers in a village. Panel A includes the sample of villages in 2005 and 2006 in which insurance coverage was offered in the village the following year. Panel B is restricted to villages in which at least on person purchased insurance the following year. The effect at average payout is the overall increase in purchasers estimated at the average payout level. In Panel A, the average ratio of payout to premium is 2.68; in Panel B it is 3.25. All regressions contain state fixed effects. Errors are clustered at the weather station level. ***p _<_ 0.01, **p _<_ 0.05, *p _<_ 0.1. _Source_ : Authors’ analysis based on data from BASIX. In panel B, I restrict the analysis to villages that had at least one buyer the year after insurance outcomes, creating a sample analogous to the “Marketing Restricted Sample” in table 3. The logic behind this is, if a village had zero buyers, it is", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "BASIX"}], "vague_data": []}}}
{"input": "**The World Bank** Socio-economic Inclusion of Refugees & Host Communities in Rwanda Project Phase II (P509677) health facilities and market-linked skills training. [7] The 2024 Rwanda FinScope survey also showed relatively low takeup of finance for investments or credit for productive purposes by Rwandese and refugees, limiting business and income-generating opportunities. [8] 7. **High poverty rates and minimal economic activity in the hosting districts constrain self-reliance prospects** **for refugees and host communities alike.** The national non-monetary poverty rate in Rwanda of 30 percent is exceeded in all five districts that host refugee camps. Gisagara, where the Mugombwa camp is located, ranked as the poorest district in the country in the 2022 Census at 45 percent. [9] By comparison, the City of Kigali has the lowest percentage of poor people (9.5 percent). Core elements of the non-monetary poverty index include health, education and living standards, highlighting the dual need to: (a) invest in economic opportunity and access to services in the hosting districts; and (b) at the same time, facilitate refugee mobility out of the camps and rural areas into urban centers, where more opportunities are available and self-reliance is more achievable. 8. **Building on the ongoing Phase I of Jya", "output": {"entities": {"named_data": [{"text": "2024 Rwanda FinScope survey"}, {"text": "2022 Census"}], "descriptive_data": [], "vague_data": []}}}
{"input": "for expecting mothers and newborns. Component 2.1 will enhance women’s access to healthcare through improved infrastructure, including all-weather roads, clean energy, and water, as well as investments in maternity wards. These improvements will support reproductive health, prenatal care, and the treatment of issues related to FGM/C. Additionally, the project will foster women’s economic empowerment by supporting livelihoods for women-only Affinity Support Groups (GEAs) and female-led businesses. 16. **Climate change exacerbates the vulnerabilities of already underserved and rural communities in Djibouti** . The country’s harsh climate is characterized by high temperatures and extreme water scarcity. Djibouti has no perennial rivers, 12 [USAID (2024), Djibouti Assistance Overview](https://www.usaid.gov/sites/default/files/2024-08/USAID-BHA_Djibouti_Assistance_Overview-August_2024.pdf) 13 WFP (2024), [WFP Djibouti Country Brief November 2024](https://docs.wfp.org/api/documents/WFP-0000163674/download/?_ga=2.195641900.1223889895.1738425185-377343974.1738425185) 14 Malaeb, B., Duplantier, A., Maarraoui, G., Fluet, E. (2023). Towards a More Equitable Development: Constraints and Opportunities of Women in Djibouti. The World Bank, Washington 15 Country Profiles for Early Childhood Development, 2023. 16 According to Malaeb B. et al. (2023), women-owned businesses have higher rates of using informal methods of financing (53 percent compared to 33 percent); women-owned enterprises are usually micro-sized (80 percent of women businesses are sole-proprietorships), informal (42 percent of women businesses are informal), and young (42 percent of women businesses", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "countries: Number of people exposed to significant flood risk (and as share of total_ _regional population)_ Considering the absolute population exposure figures above biases attention towards large and populous regions. Notably, Uttar Pradesh, Maharashtra, and Bihar are the three most populous sub-national regions in the world. Instead, considering relative population exposure, i.e. the share of the overall population that is exposed to flood risks, can help identify regions in which flood risks are prevalent across large parts of the population. Figures 10 and 11 present relative flood exposure estimates, which demonstrate that in various regions the vast majority of the population is facing significant flood risks. The sub-national region with the highest relative exposure to flood inundation risk is the Pool region in the Republic of Congo. The region, home to Pool Malebo, has a population of approximately 360,000 people, 91% of whom are exposed to significant flood risk. In all of the top 10 subnational regions in terms of relative population exposure, over two-thirds of the population are estimated to face significant flood risks. Strikingly, regions with high flood exposure can be found in all regions, and in low- and high-income 15", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "the lowest quintile of the PISA index were below level 2. Foundational learning (literacy and numeracy) in early grades paves the way for future learning, and differences in educational attainment become magnified through youth and adult life in the acquisition of human capital. Without any claims regarding causation, it is useful to look at labor earnings, which are more closely related to human capital than earnings from other assets. OECD figures show that 32 percent of 25–64-year-olds in Costa Rica with low levels of educational attainment (below upper-secondary education) earned less than half of the median earnings for the country and were thus at risk of poverty, if not already poor. [10] **Employability** 6. **In addition to foundational learning, Costa Rica’s education system requires a renewed emphasis on** **competencies for employability, including cognitive, technical and digital skills, socioemotional competencies, and** **English language skills.** Costa Rica’s economy diversified from agricultural commodity exports in the 2000s to an economy centered on high-tech manufacturing and services. Costa Rica contributes to at least 5 major high-tech global value chains: electronics, medical devices, automotive, aeronautic/aerospace, and film/broadcasting devices. However, the education system has not been highly effective in keeping up to the changes by providing", "output": {"entities": {"named_data": [{"text": "the PISA index"}], "descriptive_data": [{"text": "OECD figures"}], "vague_data": []}}}
{"input": "construction land (18.7% and 22.6% of villages with a mean of some 6 disputes). Even where disputes emerged, most cases were resolved by local institutions: in villages with conflict, a total of 1.2 cases required intervention by institutions above the village. After certification, contracts with a length exceeding 30 years were issued for all construction land and more than 95% of all other land use types. Permanent land use contracts were given in close to 72% of cases overall, from 85% of residential and construction land to 80% of collective land, and some 50% and 48% of arable and forest land. Survey data point toward a total cash cost for the program of about Y 8.6 per mu of which close to half (38%) was contributed by the village and the remainder from outside. Villagers contributed close to 2,000 man-days of labor (about 3 days per household) and, with somewhat more than 10 person-months of labor by outsiders, contributions from above the village remained limited. **4. Econometric results** The reform is estimated to have led to a significant increase of 7.7 percent in per capita consumption that was most pronounced for less educated and less wealthy households, and an increment", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "Survey data"}], "vague_data": []}}}
{"input": "between Africa and Asia through Israel‘s southern border with Egypt. The asylum seekers originate mainly from Sudan and Eritrea, as well as other Sub-Saharan countries. At the time of writing, it is estimated that around 26,000 asylum seekers have entered Israel and a few hundred more continue to cross the border every month (Nathan 2010). _Sources: UNHCR Statistical Yearbooks. No data available for 2003. UNHCR has not yet published_ _data for 2010._ The Sinai desert serves as a geographical barrier between the countries and only short, 'sensitive' strips of the 260 kilometres are fenced. The asylum seekers often pay large sums to Bedouin smugglers (operating from both sides) who traffic them through the desert. In a border characterised by an active trade of drugs, tobacco, weapons and 2 As I demonstrate below the ̳refugee terminology‘ is contentious. In the interest of coherence I predominantly use the term ―asylum seekers‖, a term which does not tells us much about motivation but refers to the claim, which ought to stand evaluation. Thus, in this work, a person is considered an asylum seeker, until proven otherwise. 2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "non-exposed areas are those grid cells where the flood level is zero. This is a measure of extent rather than depth, and has been used in previous studies to examine exposure to floods (Jongman et al. 2014; Winsemius et al. 2015; Ceola et al. 2014). Furthermore, while we lose information by using extent rather than depth (we have depths in our flood data), we decided to use extent since our flood data assumes no protection. Protection is more likely to impact the depth, rather than the extent, of the flood results. [4] 4 There is also a good reason for examining extent over depth, in terms of the hazard modeling; flood depths within a large scale flood model are very uncertain, and there is much more certainty about extents.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "flood data"}]}}}
{"input": "the east of Israel, Jordan hosts nearly 500,000 refugees, and to the South, Egypt (from which the majority of asylum seekers cross to Israel) hosts a population of more than 100,000 (UNHCR 2009; USCRI 2009). It is also known that Egypt has a vast population of unregistered foreign nationals who are not accounted for in refugee statistics. Estimates of their number vary considerably (Harrell-Bond and Zohry 2003; Nassar 2008). While such numerical and comparative analysis suggests that Israel‘s asylum seeker population is relatively small, this approach does not illuminate the social and political issues which give Israel‘s asylum seekers particular political and cultural weight. Surrounded by Arab and Muslim countries with weaker economies, Israel‘s prosperity and democratic structure act as significant pull factors for migrants. The country‘s decision to follow UNHCR guidelines and not to deport Eritreans and Sudanese while tolerating their unauthorised work must also function as an incentive. It is also important to consider the circumstances that prompt Sudanese and Eritreans, the two dominant groups of asylum seekers, to make Israel their first or second country of asylum (Afeef 2009, 9). While their circumstances significantly differ, Eritreans and Sudanese share a desire to seek better protection and to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "refugee statistics"}]}}}
{"input": "and coincidence of flood risk and population, this approach does not allow a robust estimation of exposure headcounts. Jongman et al. (2012) provide the first global flood exposure analysis that utilizes spatial hazard and population data, albeit at relatively coarse resolution by current standards (10 x 10 kilometers for population data, and 1 x 1 kilometers for flood data). The authors estimate that in 2010, 805 million people worldwide were exposed to fluvial flooding with a 1-in-100 year return period; 271 million people to coastal flooding with the same return period. By accounting for overlap between coastal and fluvial flood risk zones, they further estimate that the global flood exposed population was 992 million in 2010, and project this number to reach 1.3 billion by 2050. In this study, we show that this projection has already been exceeded in 2020, with 1.47 billion living in high-risk flood zones. Several factors can explain this increase in estimated exposure headcount: On the 1 Disclaimer: The boundaries, colors, denominations, and other information shown on the maps in this study do not imply any judgment on the part of The World Bank concerning the legal status of any territory or the endorsement or acceptance", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "flood data"}, {"text": "population data"}], "vague_data": []}}}
{"input": "host in Africa, and among the five largest worldwide.** There are over 1.8 million refugees and asylum seekers in the country at present, most of whom originate from South Sudan (54 percent) and the Democratic Republic of the Congo (32 percent). Uganda continues to experience significant inflows, with over 170,000 refugees having arrived during 2024. The refugees are formally settled in 12 of Uganda’s 146 districts, plus Kampala. 4. **Uganda is globally recognized for its refugee policy framework, which is closely aligned with the priorities of** **the GCR.** Uganda’s refugee policies deliver the shared international vision under the 2018 GCR, that allows refugees to 1 As of April 30, 2025, the exact number of refugees and asylum seekers in Uganda is 1,890,334. Source: Office of the Prime Minister and the United Nations High Commissioner for Refugees (UNHCR). 2 Zhou, Yang-Yang, Grossman, Guy, and Ge, Shuning, 2023. \"Inclusive refugee-hosting can improve local development and prevent public backlash,\" World Development, Elsevier, vol. 166(C). 3 Phase I of DRDIP in Uganda was rated Satisfactory throughout implementation and exceeded all Project Development Objective indicator targets. Page 1", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "rural-urban integration reforms undertaken in Chengdu prefecture followed a more integrated approach that could hold broader lessons. We describe the nature of the reforms and our analytical approach to evaluating their impact. **2.1 The challenges of rural-urban land conversion in China** In the 2000-2010 period, the size of urban areas in China expanded enormously: use of satellite imagery to define ‘urban’ consistently across countries reveals that, with an average annual area expansion of 9.8% for Hangzhou, 8.1% for Shanghai, 6.1% for Chongqing, 5.9% for Chengdu, 4.5% for the Pearl River Delta and 4.0%, for Beijing, most Chinese cities expanded at a rate well in excess of the East Asian average of 2.8% (World Bank 2014). [1] At the same time, and despite numerous measures to the contrary, rural-urban income inequality widened. While clear causality is difficult to establish, most experts agree that high rates of land conversion make a key contribution to this and, in addition, give rise to factor market distortions and often inefficient and unsustainable land use. This can largely be attributed to structural factors, most importantly the fact that, as rural land is owned by village collectives and not tradable, conversion of land from agricultural to non-agricultural", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "696 Stein Resolved Observational Data Integration Towards Evaluation of Water Resources. [5] This data set has daily readings of rainfall for the period 1961–2004, at a precision of .25. [6] The data are extrapolated based on historical rainfall readings from weather stations primarily provided by the Indian Meterological Department. For each block, the data contain the amount of rainfall in millimeters and the number of stations within the grid that contributed to the data. These data are used to evaluate how the insurance policies would have paid out historically, which can be used as a proxy for past rainfall shocks. [7] The three individual years of BASIX customer data were converted into a panel by manually matching individual customers using available identifying data. Errors in matching customers from year to year create the possibility of introducing nonclassical measurement error into the analysis. In section I discuss the possible consequences of such errors and how they affect interpretation of the estimates. **II.** **Results: The Effect of Payouts on Take-Up** In this section I address the central question: is receiving an insurance payout correlated with repurchasing insurance the following year? To do this, I examine BASIX’s customers in 2005 and 2006, and", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "historical rainfall readings from weather stations"}, {"text": "BASIX customer data"}], "vague_data": []}}}
{"input": "squared. In this specification, the dummy on receiving 5 [APHRODITE’s water resources project; http://www.chikyu.ac.jp/precip.](http://www.chikyu.ac.jp/precip) 6 25° latitude equals about 27.5 kilometers. .25° longitude varies by latitude; over the range of latitudes in this survey it equals roughly 26 kilometers. 7 It is not clear if ICICI-LOMBARD used APHRODITE or another source of historical rainfall data in order to price their policies because this information is proprietary. The APHRODITE data set is based on historical data provided primarily by the Indian Meteorological Department (IMD), but similar gridded data sets provided by IMD contain vast amounts of missing data over both time and space. It is very likely that the ICICI-LOMBARD products were priced using IMD data, but it is likely the ICICI-LOMBARD used different techniques to account for missing data. 8 It makes sense to assume that the error _εt,i_ is correlated for the same person across time as well as across people in a given year. Ideally, one would like to include individual fixed effects to account for individual heterogeneity. However, in order to exploit this variation one would need to look at customers who purchased insurance in both 2005 and 2006, and received payouts in only one of those", "output": {"entities": {"named_data": [{"text": "APHRODITE data set"}], "descriptive_data": [{"text": "similar gridded data sets"}], "vague_data": [{"text": "historical data"}, {"text": "historical rainfall data"}]}}}
{"input": "facilitate the full participation, retention, and educational advancement of students with disabilities, as well as facilitation for their transition to the labor market. 13. **Indigenous students face additional educational challenges related to the low availability of educational** **materials in indigenous languages.** There are an estimated 16,000 indigenous students from eight communities (NgäbeBugle, Cabécar, Bribri, Malecu, Chorotega, Huetar, Térraba, and Boruca) located in 24 indigenous territories recognized by the State. Education matters are managed by local indigenous education councils ( _Consejos Locales de Educación_ _Indígena_ ) under the aegis of MEP’s national system of indigenous education. Despite the existence of a decree from 2013 that aims to preserve indigenous languages and promote early grade learning in mother tongues, additional efforts are needed to train teachers and develop learning materials in indigenous languages. [21] Education and administrative boards continue to face a lack of training and supervision, hindering their ability to effectively fulfill their responsibilities. 19 UNHCR, Strategy 2024, Situation Analysis. 20 Data from MEP’s Saber, as of September 26, 2023. 21 Sistema Costarricence de Información Jurídica, Decreto Ejecutivo 37801, Reforma del Subsistema de Educación Indígena, [https://www.pgrweb.go.cr/Scij/Busqueda/Normativa/Normas/nrm_texto_completo.aspx?param1=NRM&nValor1=1&nValor2=75249&strTipM=FN](https://www.pgrweb.go.cr/Scij/Busqueda/Normativa/Normas/nrm_texto_completo.aspx?param1=NRM&nValor1=1&nValor2=75249&strTipM=FN) Page 5", "output": {"entities": {"named_data": [{"text": "MEP’s Saber"}], "descriptive_data": [], "vague_data": []}}}
{"input": "CRITICAL FUNDING NEEDS IN MENA / 10 OCTOBER 2024 **Basic Needs** UNHCR’s cash-based assistance targets only the most vulnerable; those who live hand to mouth in truly precarious and desperate situations. Multi-purpose cash assistance assists families to put food on the table, pay for medicines, and keep children in school. Emergency cash assistance is disbursed rapidly for urgent cases, such as for those at risk of eviction from their homes or in need of immediate and life-saving medical care. Cash for Protection works with refugees within a case management framework to address specific and often more complicated protection issues holistically. Around 46,000 IDPs and 3,100 refugee households are affected by the current funding shortfall. **Protection** Holding an identity document is one of life’s basics. Without an ID card, one cannot access basic services, freedom of movement is reduced, and risk of detention and arrest increased. Finding work is also made more difficult. According to UNHCR’s protection monitoring, over 54% of families have at least one child without a birth certificate, and 71% have family members without national identity cards. Displaced populations are often unable to access or have lost civil documentation and face challenges getting replacements for reasons connected to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "2.8 Value of crop output during the second season of 2004 347.5 366.9 164.0 419.3 Area covered under crops during the first season of 2005 2.7 3.0 1.6 2.9 Value of crop output during the first season of 2005 190.2 194.2 140.9 212.2 Value of crop output per acre [a] 101.5 96.7 95.3 110.8 Number of observations (households) 5530 2726 1076 1728 _Source:_ Own computation from 2005/06 UNHS III _Notes:_ [a ] Plot area weighted average of the value of crop output per acre of the two agriculture seasons. 17", "output": {"entities": {"named_data": [{"text": "2005/06 UNHS III"}], "descriptive_data": [], "vague_data": []}}}
{"input": "PIU. If the authorization is obtained, there may be an additional risk that the MEP fails to obtain access to SIGAF. To mitigate these risks, efforts will be made to include in the same draft law seeking loan approval by the Legislative Assembly the creation of a PIU with access to SIGAF. In addition, once the PIU is created, the MEP will recruit staff with adequate qualifications and experience on terms of reference acceptable to the Bank as reflected in the POM. Training in FM and disbursement procedures will be provided to FM staff before starting implementation, and a Project operational manual satisfactory to the Bank will be prepared and will include a FM section detailing FM processes and procedures to ensure adequate internal controls, contract management and monitoring mechanisms over project funds, timely payments and issuance of financial report: Lastly, the Bank will undertake regular missions to support the implementation of the project. For Procurement. The procurement residual risk of delays in implementation is Substantial as MEP has limited experience implementing World Bank-financed projects, and no experience under the current Procurement Framework. These risks will be mitigated by training staff on Procurement Regulations, as well as through the inclusion", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "This dataset, created by the National Oceanic and Atmospheric Association’s Climate Prediction Center, is based on ground station measurements of precipitation over the period 1948–2001. The average temperatures and precipitation for each country in the sample are shown in Appendices A and B. Note that there is a wide range of climates across the 11 countries in the sample. It is not possible to use every month of climate in a Ricardian regression because of the high correlation between one month and the next. Consequently we must cluster the monthly data into seasons. However, it is not self-evident how to cluster monthly temperatures into a limited set of seasonal measurements. We explored several ways of defining three-month average seasons, starting with November, December, and January for winter. Comparing the results, we found that defining winter in the northern hemisphere as the average of November, December, and January provided the most robust results for Africa. This assumption in turn implies that the next three months would be spring, the three months after that would be summer, and August, September and October would be fall (in the north). These seasonal definitions were chosen because they provided the best fit with the data", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "ground station measurements of precipitation"}], "vague_data": []}}}
{"input": "experiences of their friends and neighbors. Evidence in the developed world shows that purchases of flood and earthquake insurance in the United States are greatly influenced by recent experiences with disasters and insurance payouts, that peoples’ insurance decisions are influenced by their friends and neighbors’ experiences with insurance (Kunreuther, Sanderson, and Vetschera 1985; Gallagher 2014). Reacting to Daniel Stein is a senior economist at IDinsight; his email address is [Daniel.stein@idinsight.org.](mailto:Daniel.stein@idinsight.org) This work would not have been possible without the assistance of the insurance staff at BASIX, especially Sridhar Reddy, for help in obtaining and understanding their customer database. Thanks to Tim Besley, Greg Fischer, Gani Aldashev, and Xavier Giné for giving helpful advice and commenting on earlier drafts. Thanks to participants at the Munich Re 6th Annual Microinsurance Conference, the Midwestern International Economic Development Conference, seminars at the London School of Economics, University of Namur, and KU Leuven for helpful comments. All remaining errors are my own. A supplemental appendix to this article [is available at https://academic.oup.com/wber.](https://academic.oup.com/wber) 1 CIA World Factbook: India; Indiastat.com. © The Author 2016. Published by Oxford University Press on behalf of the International Bank for Reconstruction and Development / THE WORLD BANK. All [rights reserved. For", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "customer database"}]}}}
{"input": "and sharing of technical and institutional analyses to help the project designs be closely aligned and synergistic; (ii) the administrative and legislative processes for project approval by the Government are expected to take place at the same time as the IDB-financed project; and (iii) project implementation will be carried out in close coordination with the IDBfinanced project. An example of complementarity is on the pedagogical reform, with the proposed Project focused on foundational learning, while the IDB financed project would deepen the impact with support to a wider curricular reform. The efforts of both projects in supporting MEP’s digitalization agenda are included as an operational core of an ongoing regional effort between the two Banks under the Memorandum of Understanding on strategic areas including reducing the digital access gap. 16. **Costa Rica recently received a positive IMF review of the overall Government program, which bodes well for** **MEP, especially as MEP reforms are geared towards sustainability** . [22] An important consideration of the reform program is that the planned interventions do not require a level of investment that would put inordinate fiscal pressure regarding the MEP budget. Expenditures such as the investments planned for the digitalization agenda of the MEP", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "School](https://www.worldbank.org/en/news/feature/2024/01/11/djibouti-giving-refugee-children-a-chance-to-go-to-school) 9 The Ministry of Health and UNHCR signed a cooperation agreement in 2018 for the inclusion of refugees in the national health system 10 Government of Djibouti (2024), Stratégie Livelihoods et Inclusion Economique Djibouti 2024 – 2028 11 UNHCR, African Development Bank Group, IGAD, EAC (2024), Regional Report Draft: Regional Program on Enhancing the Investment Climate for the Economic Empowerment of Refugee, Returnee and Host/Return Community Women in the East and Horn of Africa and Great Lakes Region. Page 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Some coastal zones in our study area invest significant resources in damage prevention via polder construction and other measures, while others offer compensation once cyclone-related damage has occurred. Incorporation of controls from our cyclone panel database may permit more accurate estimation of the timing and magnitude of responses to these differences. To conclude, we believe that the coastal cyclone experiences of Bangladesh, West Bengal and Odisha also offer potentially-valuable lessons for the global community. Our overall findings for the Indian Ocean are consistent with the view that ocean warming from climate change has increased the frequency and average power of regional cyclone storms. Since 1960, a composite index of cyclone frequency and power has increased by about 50%. Since our focal study area is one of the world’s most cyclone-prone, its experience can provide important clues for understanding the potential future of other cyclone-affected areas. In this context, studies that 22", "output": {"entities": {"named_data": [{"text": "cyclone panel database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "of natural shocks, and historical data only offer limited guidance on the future. So, when taking long-term investment and planning decisions, selecting options that offer robust performance under a variety of scenarios is crucial (Hallegatte et al. 2019). This study considers a 1-in-100 year return flood intensity to reflect a relatively rare and intense disaster. However, the concept of return periods is easily misunderstood and the probability underestimated. A 1in-100 year flood has, on average, a 1% probability of occurrence in any given year. But this translates to or 10% probability in a decade, or 50% in a lifetime (68 years). These are significant probabilities that lie well within reasonable planning horizons of governments. For comparison, the Dutch flood protection system protects against events up to 1-in-10,000 years. In addition, it should be noted that these probabilities apply independently to a given river basin or microclimate. For the purpose of this study, we consider hundreds of thousands of such locations. This means that, globally, hundreds of 1-in-100 year flood events happen every year. **3.2.** **Population density** This study estimates the location of people using the Global Human Settlement Layer (GHSL), produced by the EC JRC. It offers global coverage and", "output": {"entities": {"named_data": [{"text": "Global Human Settlement Layer"}], "descriptive_data": [], "vague_data": [{"text": "historical data"}]}}}
{"input": "components. Progress on all project components will be through biannual progress reports submitted by the PMU to the World Bank and disclosed publicly. 53. **Progress on the implementation of Components 2 and 3 will be overseen by the district-level PMU.** Progress will be assessed on infrastructure and agribusiness activities and provide quarterly reports to the MoHAIS. 54. **Citizen engagement and social accountability will be promoted throughout the project cycle.** The project has prepared a Stakeholder Engagement Plan (SEP) which was disclosed in country and on the World Bank website on August 1, 2024, which provides guidance on ensuring effective project communication and consultation at different stages of implementation. It further sets out indicators that will be monitored in accessing the level of beneficiary engagement, feedback, and grievances. The policy stakeholder group will facilitate the exchange of information between policy makers and the public. Citizen engagement will be measured through beneficiary assessments, which will include (a) participatory focus groups and (b) semi-structured interviews with refugees and former refugees, host community members, farmers, cooperatives, and agribusinesses. Citizen engagement outcomes will be assessed through the indicator “Stakeholder consultations convened, and priority measures identified”. These beneficiary assessments will help assess the relevance and impact", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Loayza, N., A. Mier y Teran, and J. Rigolini. 2013. “Poverty, inequality, and the local natural resource curse.” Discussion Paper Series, Forschungsinstitut zur Zujunft der Arbeit, 7226, Bonn. Maldonado, S. (2017). The non-monotonic political effects of resource booms. Mamo, N., Bhattacharyya, S., & Moradi, A. (2019). Intensive and extensive margins of mining and development: evidence from Sub-Saharan Africa. _Journal of Development_ _Economics_, _139_, 28-49. Michaels, G. 2011. “The Long Term Consequences of Resource-Based Specialisation.” _The_ _Economic Journal_ 121: 31–57. MineAtlas. 2013. https://mining-atlas.com/ Rhee, S., Nyanza, E. C., Condon, M., Fisher, J., Maduka, T., & Benshaul-Tolonen, A. (2018). Understanding environmental, health and economic activity interactions following transition of ownership in gold mining areas in Tanzania: A case of private to public. _Land use policy_, _79_, 650-658. Standing, A., and G. Hilson. 2013. “Distributing mining wealth to communities in Ghana: Addressing problems of elite capture and political corruption.” _U4_ issue 2013 (5). van der Ploeg, F. 2011. “Natural Resources: Curse or Blessing?” _Journal of Economic_ _Literature_ 49 (2): 366–420. von der Goltz, J., & Barnwal, P. (2019). Mines: The local wealth and health effects of mineral mining in developing countries. _Journal of Development Economics_, _139_, 1-16. Wilson, N. 2012. “Economic Booms and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "This reliance on international trade – especially for essential imports such as water and food - leaves Djibouti vulnerable to climate-related shocks affecting both its own territory and its neighboring trading partners. 6. **As of January 15, 2025, Djibouti hosts 32,643 registered refugees** **[2]** **and asylum-seekers, constituting** **approximately three percent of the population, primarily from Somalia, Ethiopia, and Yemen** [3] **.** Eighty-five percent of refugees live in settlements (2,529 in Obock; 8,019 in Holl Holl; and 16,980 in Ali Addeh), while 15 percent reside in urban areas (5,115 in Djibouti-Ville). A majority of refugees are between the ages of 18-59, and the gender composition is 52 percent male and 48 percent female. The government’s proactive approach, aligned with the Global Compact on Refugees, includes efforts to integrate refugees into national systems while promoting social and economic inclusion, reinforced by the adoption of a National Refugee Law (NRL) in 2017 to strengthen institutional and legislative frameworks and ensure refugee access to services. Djibouti’s relative peace and economic growth in the region have made it a key destination for refugees and migrants, who seek sanctuary from conflict and climate-induced disasters. Additionally, Djibouti serves as a key transit corridor for migrants from the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**World** 0 2 4 6 8 Billions **Figure 2** _**. Global population headcounts exposed to different levels of flood risk**_ By regionally disaggregating global exposure headcounts, it becomes apparent that flood risks are particularly prevalent in certain regions. At 595.3 million people, the East Asia and Pacific (EAP) region has the highest number of people exposed to significant flood risk – corresponding to about 25% of EAP’s total population. In all other regions, flood exposed people account for a smaller share of the overall population. In the South Asia region (SAR), 370 million people are exposed to significant flood risk – i.e. about 19.5 percent of the SAR population. In Sub-Saharan Africa (SSA), Europe and Central Asia (ECA), Middle East and North Africa (MENA), Latin America and the Caribbean (LAC), and the United States and Canada (USA & CAN), between 16.3 to 8 percent of the respective regional populations are exposed to high flood risk. Figure 4 provides a full breakdown of regional exposure estimates in absolute and relative terms. In several cases, regional exposure numbers are driven by single countries – like is the case for China in EAP, India in SAR, or Egypt in MENA. Section 5.2. presents", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "Global population headcounts"}], "vague_data": []}}}
{"input": "wheat and other grains increased and those of oil crops decreased in Chengdu while the opposite was true for households in neighboring counties. Also, key interventions in place during the period of concern are a new rural pension scheme (Lei _et al._ 2013), cooperative medical scheme (Wagstaff _et al._ 2009), and agricultural subsidies (Huang _et al._ 2011; Meng 2012). While these are funded centrally, disbursements may vary by prefecture and we include information on the amounts received in such schemes, in addition for a wide range of household-level observables, in our regressions. **3.2 Nature and cost of the certification process** To quantify costs of the reform, we use the overlap between the counties in our sample and a village survey administered in May 2014 on either side of comparable stretches of the administrative border of Chengdu prefecture(Deininger _et al._ 2015). Characteristics of the certification process for different types of land are described in table 2. The average village has an area of about 7,500 mu (5 km [2] ) of which some 51% were 13 To test for presence of pre-reform trends for variable _Yit_ in household _i_ in year _t_, we use the pre-reform sample to estimate ��� �������", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "village survey administered in May 2014"}], "vague_data": [{"text": "village survey"}]}}}
{"input": "**Poverty and flood exposure.** By combining flood exposure estimates with survey-based sub-national data on poverty, we further estimate flood exposure among the world’s poor. Our estimates show that 132 million people living in extreme poverty (living on less than $1.90 per day) are directly exposed to flood risk; of these, 72.5 million (or 55 percent) are in Sub-Saharan Africa (figure 16). Approximately two out of ten people exposed to flood risk globally are living in extreme poverty. When poverty is defined using less extreme (i.e. higher) thresholds, the number of flood-exposed poor people increases significantly. Around 343 million are estimated to live in high-risk flood zones while living on less than $3.20 a day. The number increases to 587 million when considering incomes below $5.50 a day. Increasing the poverty threshold from $1.90 to $5.50 doubles the number of poor people exposed to floods in Sub-Saharan Africa from 73 million to 147 million. However, in South Asia the number of the poor and flood-exposed increases seven-fold from 41 million to 289 million; in East Asia the increase is nine-fold from 9 million to 80 million. but increases the poor people exposed in SAR by a factor of 6.55 to 286.8", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "survey-based sub-national data on poverty"}], "vague_data": []}}}
{"input": "by the World Bank, in collaboration with WHO (Pandey, et al., 2004; Wang, et al., 2003). For natural resource degradation, we base our indicator on recent research that identifies the vulnerability of people on fragile lands (i.e., land that is steeply-sloped, arid, or covered by natural forest) as a major determinant of rural poverty and natural resource degradation in developing countries (World Bank, 2003). Our indicator, the total rural population living on fragile lands, has been constructed from a GIS (Geographic Information System) - based spatial overlay of demographic, topographical, climatic and natural resource information. We have developed our biodiversity threat indicator from a variety of sources. For terrestrial biodiversity, we use a GIS-based spatial overlay of human population with critical areas identified by Conservation International (CI), the World Wildlife Fund (WWF), and Birdlife International (BI). We also include freshwater lake areas, to capture the role of inland aquatic ecosystems. The World Bank’s Environment Strategy focuses on both the threat to biodiversity from human encroachment, and the value of biodiversity resources for human populations. Our indicator for this two-way relationship in each country is its total human population in critical biodiversity areas. For marine biodiversity, we draw on estimates of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "up potential differential effects across urban compared to rural localities. None of the treatment effects are statistically significantly different between rural and urban areas. [16] In panel C, we have constructed a new treatment variable _#active*mines_ that counts the number of actively producing mines within 20 km. Women are sampled within 20 km of one mine (593 women), within 20 km of two mines (137 women), and within 20 km of three mines (64 women). The 16 Few of the other interaction coefficients are also statistically significant. The interaction between _urban*mine_ is significant, and women in urban localities with a future mine are 12 percentage points less likely to be working in agriculture. 28", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) 15. As per paragraph 5.9 of the Procurement Regulations, the World Bank’s Systematic Tracking and Exchanges in Procurement (STEP) system will be used to prepare, clear, and update Procurement Plans and conduct all procurement transactions for the Project. Page 35", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "see Office of the Prime Minister and UNHCR (2024) _Uganda Urban Response Strategy 2024-2029_ . 7 The definition used is canopy height >5m. Global Forest Watch 8 Compounded by the fact that refugee settlement population density is typically ten times the national average: World Agroforestry Center, 2024. 9 Gianvenuti, A., Bedijo, N. G., Jalal, R., Hitimana, L., Walter, S., Linhares-Juvenal, T., and Xia, Z. (2022). Woodfuel Consumption in Refugee Hosting Areas and Its Impact on the Surrounding Forests—The Case of Uganda. _Forests_, _13_ (10), 1676. Page 2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Access to housing:** Protection monitoring findings and focus group discussions have highlighted that accommodation was the most urgently reported need (39% of respondents in first quarter of 2024 compared to 27% in the last quarter of 2023), followed by employment. Protection monitoring shows a positive trend in the percentage of respondents residing in rented accommodation with an increase from 46% in the last quarter of 2023 to 59% in the first quarter of 2024. In parallel to this, the percentage of residents in collective accommodation facilities decreased from 12% to 6% during the same period. It is likely that many refugees residing in collective accommodation facilities have already begun to relocate to rented housing as a result of the changes in the provision of cost-free accommodation. This applies also to vulnerable persons, who previously continued to benefit from cost-free accommodation beyond the 150 days. Findings from Protection Monitoring for this quarter confirm that 38% of those having to leave their accommodation was on account of the accommodation closing, compared to only 22% in the last quarter of 2023. ## 39% Consider accommodation an urgent need facilities across seven regions [1] highlighted the challenges in accessing sustainable and affordable housing, including", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "to their home country while application fees for passports are unaffordable for many. The GRZ has offered to integrate former Angolan refugees who arrived between 1966 and 1986. However, most of those who arrived after 1986 do not have any form of identification. The risk of statelessness extends to children born to refugees, because Zambian laws do not automatically grant citizenship to children born to foreign parents on Zambian territory. 9. **Most refugees and former refugees in Zambia live in designated refugee settlements** . Approximately 75 percent of refugees are in one of the three remote refugee settlements of Mantapala (8720 individuals), Meheba (41,762 individuals), and Mayukwayukwa (26,049 individuals), with 25 percent in Lusaka, Ndola, and other urban centers. Mayukwayukwa and Meheba are four to five decades old, with dilapidated and inadequate infrastructure. Around 16,000 8 National Adaptation Plan for Zambia, 2023. 9 The plan is the fourth of its series of five-year National Development Plans intended to achieve the National Vision 2030, which is aimed at transforming Zambia into ‘a prosperous middle-income nation by 2030’. 10 Zambia National Statistical Report, Ministry of Home Affairs and Internal Security, May 2024. Page 9", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "and so on), and nearby households. A key social infrastructure priority is schools, which are massively overcrowded and lack classroom capacity; teacher accommodation; and appropriate water, sanitation, and hygiene (WASH). Energy for school infrastructure will allow uninterrupted learning, while new classroom designs will allow greater cooling and ventilation and the adoption of simple water harvesting will permit more handwashing. Through this component, the GRZ—specifically Kalumbila Town Council—will be provided with TA to improve capacity in climate-resilient design and construction standards for infrastructure. The project aims to pilot new climate-resilient classrooms designs that are cost-effective and sustainable. The project will also invest in sensitizing local communities on how better to adapt to climate risks, including appropriate water usage, farming techniques etc. 32. **Meheba falls within the Kalumbila District, one of the eleven districts of the North-Western Province in Zambia.** The district has become a new destination for domestic and foreign investment in Zambia, driven largely by the rapid growth in mining activities, which has seen the population of the district more than double in 10 years—from around 85,000 at the time of the 2010 census to 180,000 in the 2022 census. [23] The population of Meheba, which is predominantly youthful (75.9", "output": {"entities": {"named_data": [{"text": "the 2010 census"}, {"text": "the 2022 census"}], "descriptive_data": [], "vague_data": []}}}
{"input": "varied but a total of 9597 surveys were administered. After data cleaning, including removal of farms that did not grow crops, and surveys with field errors and missing information, the final number of useable surveys was 8463. We conducted the analysis at the plot level of each farm as the dataset was sufficiently detailed to extract and utilize information about whether or not a particular plot (from a set of three) was irrigated or not. Each farm provided plot specific data on whether or not irrigation was used, crop production (including crop type, amount harvested, quantity sold, quantity consumed and amount of sales receipt) and crop costs (fertilizer, pesticide and seed data). Using this data, prices per crop and yields per hectare of farmland and cropland were estimated, as well as plot specific crop revenues and farm level gross and net revenues. Net revenue estimates are at the farm level because the input data, including labor (both hired and household) and machinery, were available only at that unit of measurement. It was not possible to allocate most inputs to specific plots as much of it was applied to several plots at a time. The dataset we used contains 1750 irrigated", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "in table 1. **Table 1.** Insurance Policy Summary Statistics **Year** **2005** **2006** **2007** Number of weather stations 34 42 28 Average premium for three phases (Rs) 290 295 287 Expected payout (Rs, using rainfall 1961–2004) 119 73 80 Ratio of premium to expected payout 2.67 2.47 2.12 Mean percentage of years policy would have 22.9 15.6 13.9 paid out 1961–2004 _Notes_ : This table lists basic features of the insurance policies studied in this paper. Each policy offers three phases of coverage with different premiums, but customers are not required to purchase all three. However, as purchasing all three phases was the most common behavior, the average premium for purchasing all phases of coverage is listed. The expected payout is estimated using the APHRODITE dataset, for the period 1961–2004. As pricing strategies for ICICI-LOMBARD are proprietary, these estimates may not correspond to their internal estimates of expected payouts. However, the APHRODITE data set likely draws from the same historical data used to price the insurance policies. The ration of premium to expected payout is the average premium (averaged across all weather stations) divided by the average expected payout. _Source_ : Authors’ analysis based on data from BASIX and APHRODITE.", "output": {"entities": {"named_data": [{"text": "APHRODITE data set"}, {"text": "APHRODITE dataset"}], "descriptive_data": [{"text": "data from BASIX and APHRODITE"}], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) can contribute meaningfully to environmental conservation and sustainable development while meeting the challenges posed by climate change. **MEP Management Structure and Efficiency** 10. **Reforming the organizational structure and management processes of MEP offers an opportunity to increase** **its efficiency, decision-making, and accountability to improve student learning and education trajectories in Costa Rica.** With 2,763 officials at the central level and 1,451 at the regional level, distributed in 4,810 schools, the educational system has the necessary infrastructure to implement significant changes. [16] A reform of MEP to increase effectiveness and alignment with educational objectives would include: (i) review and rationalization of the central organizational structure to eliminate redundancies and clarify roles and responsibilities, especially in units focused on educational quality; (ii) restructuring of MEP regional units to better respond to local needs and organizations, ensuring that these offices focus on providing direct and effective support to frontline schools; and (iii) Improving decision-making with a data-driven approach, improving information systems and planning, which requires more accurate cost estimation and resultsoriented strategic planning. These measures would allow the MEP to optimize its management and fulfil its mandate to ensure that resources are used", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "vulnerable freshwater marshes and China represents 79.1% of all vulnerable GLWD Coastal Wetlands within EAP. Within MENA, 92.7% of all regional vulnerable saline wetlands are in Libya and Egypt. On the whole, our results suggest a significant asymmetry in the burden of SLR on wetlands: a small number of developing countries is expected to bear the additional burnt of sea level rise, while many other coastal countries will experience little change. It should be noted that numerous studies on impacts of climate change have indicated that small island nations are particularly susceptible to the impacts of SLR (for example, see Anthoff et al 2010; Nicholls et al 2010; Anthoff et al 2006; Church et al 2006; Nicholls et al 1999). However, limitations of the resolution of the global spatial datasets make quantification of the vulnerability of wetlands of small island nations particularly difficult. [20] Even though the SRTM elevation data are at approximately 90m spatial resolution, the global wetlands data are compiled from a range of sources resulting in generalized areas. Also, the correspondence 20 Tol 2007 drew on the Global Vulnerability Analysis and other country studies for quantification of wetland loss from 1 m SLR for a global analysis", "output": {"entities": {"named_data": [{"text": "SRTM elevation data"}, {"text": "Global Vulnerability Analysis"}], "descriptive_data": [], "vague_data": [{"text": "global spatial datasets"}, {"text": "global wetlands data"}]}}}
{"input": "The World Bank Economic Review 701 villages that did not experience a rainfall shock. A shock is defined using each location’s insurance policies in 2005: If insurance would have paid out in 2004 based on the structure of the 2005 weather policy, this is deemed a rainfall shock. As the quality of the rainfall data is related to the amount of nearby weather stations, I weight the observations based on the number of nearby rainfall stations. [11] Also, I create a hypothetical payout ratio, similar to the “Ratio of Payout to Premium” variable presented in table 3. This is the ratio of the amount that the 2005 policy would have paid out in 2004 divided by the premium of the policy. The results of this regression are presented in table 5. [12] **Table 5.** Direct Effects of Rainfall on Purchasing **Dependent variable is number of buyers in 2005** **(1)** **(2)** **(3)** **(4)** Would have been payout in 2004 −3.843*** −4.592*** −5.045** −3.788* (0.987) (1.039) (2.173) (1.898) Ratio of hypothetical 2004 payout to 2005 Premium 4.365 −0.755 (4.610) (5.543) Payout ratio squared −1.991 −0.279 (1.814) (2.064) Constant 8.001*** 0.651 7.985*** 1.015 (0.714) (6.341) (0.713) (6.494) Weather station constants NO YES NO", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "rainfall data"}], "vague_data": []}}}
{"input": "more progressive approach to refugee inclusion.** There is a general recognition in Government that a shift to self-reliance and a move away from humanitarian support is required. Zambia’s Eighth National Development Plan (8NDP) has a vision for a more decentralized approach to economic and social development, which will support the greater inclusion of approximately 101,837 [15] refugees, asylum seekers, and former refugees that currently reside in the country. 14. **In August 2023, the GRZ endorsed a new National Refugee Policy, approved by the Cabinet in November 2023.** The Office of the Commissioner for Refugees, in close cooperation with the MoHAIS and the United Nations High Commissioner for Refugees (UNHCR), developed the new policy to address existing legal gaps and enhance coordination within government. Its implementation is expected to ease reservations to the 1951 Convention and harmonize the 2017 Refugee Act with other national legislation (for example, the Immigration and Deportation Act of 2010) that will enhance opportunities for protection and solutions for self-reliance. [16] To assist policy delivery, the Government has established an interagency National Steering Committee chaired by the Office of the Vice President. In March 2023, the MoHAIS launched a plan for the Modernization of Refugee and Host", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "climate variables but found the linear model to be more reliable. (Log pseudolikelihood = -2340.59 and r-squared 0.51 versus -2187.4434 and 0.54, respectively, for the quadratic probit model.) The Chow test for determining the null hypothesis that the estimated parameters are jointly the same is rejected (chi [2] (30) = 3967.66; Prob > chi [2] =0.0000). The coefficients (which are highly significant) suggest that the probability of adoption of irrigation increases with higher temperatures and precipitation in each season except in spring. The reported standard errors in the paper are based on the Huber-White estimator of variance which are robust against many types of misspecification of the model (Heltberg & Tarp 2002). The annual marginal effects, which are more informative of the decision to irrigate or not, reflected in the probability response functions of choosing irrigation given delta temperature increments (holding all other variables constant), reflect the current irrigation landscape in Africa. The probability of adoption of irrigation increases in regions with lower temperatures (for example Egypt and South Africa), while it decreases in warmer regions. Irrigation in cooler regions is more profitable because it requires less water and the crops are more productive. Similarly, in regions of higher precipitation", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "information within the infrastructure module on repairs and upgrades and the integration of energyefficient and climate-smart features, such as improved drainage, natural ventilation, and use of climate-resilient materials in educational establishments; and (ii) strengthen the digitalization of MEP and the development of digital platforms and content delivery to enable remote instruction when extreme weather events make it unsafe for students to go to school for in-person learning. [28] The integration of digital platforms will be accompanied by the development of business continuity plans to ensure network connectivity and minimize downtime during extreme weather events. With these considerations, the Project is considered to have reduced risks to acceptable levels and to be aligned on adaptation. 27 These will consider the best available technology or match or surpass country benchmarks in energy efficiency performance. [28 In the past, extreme weather events have disrupted school continuity. For instance, in 2017, Hurricane Nate damaged 72 schools that remained](https://www.nacion.com/el-pais/educacion/tormenta-nate-dana-72-escuelas-y-colegios-en-todo-el-pais/42ZNMUM3BFA5BIWXJI3INJOBHA/story/?utm_source=rss&utm_medium=rss&utm_content=2017-10-06&utm_campaign=rss-nacional) [closed for several days. More recently, in 2022, 234 schools lost access to electricity and water following storm Julia. The MSP contract will include](https://mep.go.cr/noticias/mep-reporta-234-centros-educativos-afectados-paso-huracan-julia) contingency measures so that remote instruction can continue in the event of outages. Page 17", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "panel B shows the effects of increased production in the survey year. There is no evidence of spillovers in the sense that there is a similar effect in neighboring districts. In fact, most coefficients point in the opposite direction for mining and neighboring districts indicating, if anything, a shift in employment from neighboring districts to the producing ones. **8 Conclusions** Ghana has a long history of gold production and has recently been experiencing its third gold rush, during which annual gold production skyrocketed. It was the first gold rush the country has experienced as an independent nation, and it brings hope of improving the lives of its citizens. Natural resource extraction is often argued to have detrimental effects on countries, however, and the so-called natural resource curse may imply that resource wealth is harmful to social development and inclusive growth. We use rich geocoded data with information on households and mining production over time to evaluate the gold boom at the local and district levels in difference-in-differences analyses. Men benefit from direct job creation within the mining sector, and women seem to benefit from indirectly generated jobs in the service sector (statistically significant within 10 km from a mine). Women", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "rich geocoded data"}]}}}
{"input": "candles, flashlights, and generators for lighting and cell phone charging. Enhanced transport and energy will also stimulate retail business and production. The upgrading and expansion of school infrastructure will improve learning outcomes, enhance teacher retention and new recruitment, and afford greater dignity to boarding pupils, especially girls, as many are currently sharing beds due to the lack of capacity. The provision of modern WASH facilities will support greater school attendance—especially for girls whose attendance is often curtailed due to lack of access to hygiene services [26] —and improve the health of students who are at increased risk of waterborne diseases such as cholera in the rainy season given the current overreliance on pit latrines. (a) **Transport infrastructure: Meheba settlement main access road and Mwafwe bridge (US$3 million).** The overall state of rural roads within the Meheba settlement remains one of the main bottlenecks to the development of that settlement into an economically viable area. Results from various studies such as the 23 Zambia 2022 Census of Population and Housing, Central Statistical Office Zambia, 2023. 24 One Meheba Local Area Plan, Planning Survey and Issues Report, GRZ, 2023. 25 One Meheba Local Area Plan, Planning Survey and Issues Report, GRZ, 2023.", "output": {"entities": {"named_data": [{"text": "23 Zambia 2022 Census of Population and Housing"}], "descriptive_data": [], "vague_data": []}}}
{"input": "expand essential services, job creation and entrepreneurship to stimulate local economies, and the development of key sectors like agriculture, renewable energy, and small-scale industries. Addressing climate change, the vision emphasizes efficient water management and renewable energy to enhance resilience. Aligned with this vision, **the National Strategy for Non-** **Contributory Social Protection (NSPS, 2023-2027) integrates adaptive social protection systems, basic services,** 2 The WBG Scorecard FY24-FY30 Methodology Note defines a ‘ **refugee’** is a person who, ‘owing to a well-founded fear of being persecuted for reasons of race, religion, nationality, membership in a particular social group, or political opinion, is outside the country of his or her nationality, and is unable or, owing to such fear, is unwilling to avail themselves of the protection of that country’, referencing the 1951 Convention Relating to the Status of Refugees. For the purposes of this PAD, the term ‘refugee’ will include both refugees and asylum-seekers. 3 UNHCR (2025), Djibouti: Refuge and Asylum-Seekers Locations, as of 15 Jan 2025; UNHCR (2024), Djibouti: Refuge and Asylum-Seekers Locations, as of 31 Dec 2025 Page 2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "relationships between household wealth (excluding the value of owned land) and their willingness to pay in order to obtain full ownership rights on occupied parcels. The marginal elasticity of the reported amount that occupants’ are willing to pay with respect to wealth, though inelastic with 0.36, is positive and statistically different from zero. But wealth elasticity on the probability of willingness to pay is very negligible (0.03), implying that poorer tenants will possibly be over-bid even if they are equally willing to buy full ownership rights on occupied parcels. **5. Conclusion and policy implications** Although a large literature explores the effectiveness of titling interventions, and the impacts of tenure security on investment and productivity of land use, the African literature has not led to a consensus on whether insecurity should be of concern to policy makers or on how to most effectively address it. Our findings contribute to the methodological and the policy debate. Methodologically, the ability to use within household fixed effect estimates allows us to demonstrate that tenure insecurity has statistically very significant effects on investment and thus the productivity of land use. The fact that both our sample and the point estimates obtained are several times larger", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "after the 2005 floods, it was slow to arrive and the amount delivered was inadequate to support losses suffered (Patankar 2015). Given that poor people have consumption closer to subsistence, a substantial loss from floods in the absence of support can have high non-monetary costs in the form of irreversible impacts on children and distress sales of assets (de Janvry et al. 2006; World Bank and Australian AID 2014). In summary, livelihood shocks triggered by floods could keep people from escaping poverty and even push them into deeper poverty (Karim and Noy 2014). Despite this poverty-vulnerability relationship, previous quantitative studies on flood exposure in Vietnam have focused on the generation of losses rather than exposure across socioeconomic levels (Chinh et al. 2017; Apel et al. 2016; MONRE 2009). Nevertheless, insights from qualitative focus groups across the country (in An Giang, Kien Giang, Kon Tum, Hoa Binh, and Bac Nih) find that many poor households feel more vulnerable to floods due to their increased exposure (a result of living in flood prone areas, like along river banks or outside of protective dikes, and often having substandard quality of housing) are less likely to have sufficient assets to buffer the effects of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "executing agency, which describes how procurement in this Project will support the PDOs and deliver value for money under a risk-based approach. The PPSD will provide adequate supporting market analysis for the selection methods detailed in the Procurement Plan. Mandatory 29 MEP implemented the Equity and Efficiency of Education Project (P057857, 7284-CR). However, the project closed in 2013. 30 The PEFA 2022 concluded that overall Costa Rica PFM system is well aligned with good international practices, being budget reliability and transparency of public finances the foremost strengths. Page 18", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "because the input data, including labor (both hired and household) and machinery, were available only at that unit of measurement. It was not possible to allocate most inputs to specific plots as much of it was applied to several plots at a time. The dataset we used contains 1750 irrigated plots and 9183 dryland plots. The distribution of surveys – irrigated and dryland plots by country – is shown in Table 1. In this study, we relied on monthly temperature data collected from US Department of Defense satellites (Basist et al. 2001). This set of polar orbiting satellites obtain measurements at a given location on earth at 6am and 6pm every day. The satellites are equipped with sensors that measure surface temperature by detecting microwaves that pass through clouds (Weng & Grody 1998). The monthly precipitation data comes from the Africa Rainfall and Temperature Evaluation System (ARTES) (World Bank 2003). This dataset, created by the National Oceanic and Atmospheric Association’s Climate Prediction Center, is based on ground station measurements of precipitation over the period 1948–2001. The average temperatures and precipitation for each country in the sample are shown in Appendices A and B. Note that there is a wide range", "output": {"entities": {"named_data": [{"text": "Africa Rainfall and Temperature Evaluation System"}], "descriptive_data": [{"text": "ground station measurements of precipitation"}], "vague_data": [{"text": "monthly temperature data"}]}}}
{"input": "Nam Assessment Report on Climate Change IPCC (2007) Summary for Policymakers.^ In Climate Change 2007: Mitigation. Contribution of Working Group III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, B. Metz, O.R. Davidson, P.R. Bosch, R. Dave, L.A. Meyer (eds). Cambridge University Press, Cambridge, UK and New [York, USA. http://www.ipcc.ch/pdf/assessment-report/ar4/syr/ar4_syr_spm.pdf](http://www.ipcc.ch/pdf/assessment-report/ar4/syr/ar4_syr_spm.pdf) IPCC (2014) Climate Change 2014: Impacts, Adaptation, and Vulnerability. Part B: Regional Aspects. Contribution of Working Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Barros, V.R., C.B. Field, D.J. Dokken, M.D. Mastrandrea, K.J. Mach, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White (eds.)]. Cambridge, United Kingdom and New York, NY, USA: Cambridge University Press de Janvry, A., F. Finan, E. Sadoulet, and R. Vakis. 2006. BCan conditional cash transfer programs serve as safety nets in keeping children at school and from working when exposed to shocks?^ J Dev Econ 79: 349–373 Jongman B, Hochrainer-Stigler S, Feyen L, Aerts JCJH, Mechler R, Botzen WJW, Bouwer LM, Pflug G, Rojas R, Ward PJ (2014) Increasing stress on disaster-risk finance due to large floods. Nat Clim Chang 4(4):264–", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "shock of the same intensity occurs again. Using historical data and based on the statistical frequency of a shock of a certain intensity, it describes the probability of such an event. Figure 1 illustrates the extent of floods with two return periods: one with a 25-year return period (or a 1in-25-year flood) and one with a 100-year return period (or a 1-in-100-year flood). The 1-in-25-year flood has a 1/25 or 0.04 annual probability of occurring. In other words, each year there is a 4 percent chance of such an event occurring, regardless of when the last such event took place. The probabilistic nature of return periods means that there is a 63.9 percent probability that a flood of at least this intensity will occur once within a 25-year period. But this also leaves the possibility for this event to not occur at all, or to occur several times. In comparison, a 1-in-100-year flood is a more extreme event with a lower probability but higher intensity — that is, it affects a wider area and has a greater depth. As time passes, more climatic data become available, which will update the empirical probabilities associated with certain natural shocks. As the impacts", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "historical data"}, {"text": "climatic data"}], "vague_data": []}}}
{"input": "optimal allocation model, with a brief review of the methodology developed in Buys, et al. (2003). Assuming continuity with the past scale and thematic composition of lending, Section 8 uses the model to estimate lending and AAA opportunities by country and environmental theme for the period 2004-2009. [2] Section 9 interprets our findings using two country cases, and Section 10 provides a summary and conclusions. **2. Environmental Indicators** Building on prior work by Buys, et al. (2003), we construct country indicators for six environmental problems: greenhouse gas emissions; health damage from air and water pollution; the threat of natural resource degradation on fragile lands; threats to biodiversity; problems related to water resources; and problems with environmental policies and institutions. All of our indices reflect recent research on the cross-country incidence of environmental problems. For global greenhouse gas emissions, our indicator is total metric tons of carbon equivalent in 2000 from fuel combustion (CO2), land-use change (CO2) and other sources (methane (CH4), nitrous oxide (N20), hydrofluorocarbons (HFC’s), perfluorocarbons (PFCs), and sulfur hexafluoride (SF6)). We draw our emissions estimates from the World Resources Institute’s Climate Analysis and Indicators database. [3] Our estimate of pollution damage is total DALY (disability-adjusted life year) losses", "output": {"entities": {"named_data": [{"text": "World Resources Institute’s Climate Analysis and Indicators database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "NUSAF IV will focus on the poorest individuals, while DRDIP II will target ‘active individuals’ identified through national wealth ranking data; (b) DRDIP II will concentrate on regions with a high refugee population, freeing up NUSAF IV to operate in other areas; (c) data sharing will be facilitated through interoperability between the DRDIP II management information system (MIS) and related projects; (d) the Geo-Enabling initiative for Monitoring and Supervision (GEMS) at the portfolio level will provide mapping of different projects, offering timely information on subproject locations; and (e) bi-annual joint reviews and joint missions of the PIUs and World Bank will be explored for strategic stocktaking and alignment. DRDIP II will also coordinate with activities of the International Finance Corporation (IFC), ensuring at the very least not to crowd out private investment. 45. **As part of the portfolio level coordination, a common taxonomy across operations will be developed through** **project implementation manuals, building a shared understanding of graduation pathways at individual and group** **levels** . Livelihoods grants from NUSAF IV and economic opportunity grants from DRDIP II will form the foundational support to refugees and host communities, priming households to become economically active and participate in value chains. The DRDIP", "output": {"entities": {"named_data": [{"text": "DRDIP II management information system (MIS)"}], "descriptive_data": [], "vague_data": [{"text": "national wealth ranking data"}]}}}
{"input": "the planned procurement, the absence of a comprehensive project expenditure framework, and weak technical and procurement capacity at both the ministry and PMU levels. 16. The mitigation measures are as follows: a) A comprehensive expenditure framework including a Procurement Plan for the overall project for the first 18 months of implementation has been developed and will be updated periodically as necessary; b) Qualified staff will be assigned as focal persons to monitor, support, and report on procurement activities; c) Evaluation committee members will consist of a maximum of five members with three members from the concerned PMU/department and two members from the concerned ministry; d) Financial and administrative authority at the PMU/Department of Procurement level will be efficiently delegated to conduct procurement and manage contracts in compliance with the World Bank’s Procurement Regulations; e) Implementing agencies will start advance procurement to award a few critical contracts following Board approval; f) The Systematic Tracking of Exchanges in Procurement (STEP) system will be used for all procurement activities; and g) The World Bank will carry out regular reviews of project-related procurement activities. 17. **Procurement oversight and monitoring arrangements.** The World Bank exercises its procurement oversight through a risk-based approach comprising prior and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "possible, refugees and host communities will be provided with access to climate information, and to inform livelihood choices balanced against market demands. _Subcomponent 1.2. Issuing of ID cards to refugees and former refugees nationally (US$6 million)_ 27. **The GRZ plans to issue new biometric National Registration Cards (NRCs) to all citizens.** The process is led by the Department of National Registration, Passports and Citizenship under the MoHAIS through the Integrated National Registration Information System (INRIS) project. The overall objective of the project is to improve civil registration and identity management processes through digitization and automation. In line with the new Refugee Policy, the scheme will be extended to all refugees and former refugees, enabling them for the first time to be part of the national civil registry. Despite the historically high uptake of NRCs by Zambian citizens, women and girls still face several access challenges, attributed to time and mobility constraints due to domestic work and childcare commitments. 28. **The current system of documentation leaves persons of concern** **[20]** **vulnerable.** The GRZ, with the support of the UNHCR, has been registering persons of concern and issuing them with documents such as asylum seeker certificates, registration certificates, refugee identity cards, birth", "output": {"entities": {"named_data": [{"text": "Integrated National Registration Information System"}], "descriptive_data": [], "vague_data": [{"text": "national civil registry"}]}}}
{"input": "Africa has increased substantially over the past 18 months, with more than 700,000 people approaching UNHCR in **Egypt** since April 2023 and nearly 69,000 new arrivals to **Libya** . UNHCR is working with governments and humanitarian partners to sustain an emergency response to help those fleeing the horrors of war; however, the regional response to the Sudan situation continues to be severely underfunded. After more than 13 years, the **Syria Situation** remains one of the largest displacement crises in the world. Close to 6 million Syrian refugees are hosted in the neighbouring countries. Maintaining assistance to Syrian refugees in host countries in the region remains of paramount importance, particularly given the already heightened vulnerabilities among refugees in host countries and added pressure on host governments. A lack of adequate resources has exacerbated tensions between refugees and host communities, decreased opportunities for livelihoods and strained already overstretched national systems. Years of devastating conflict in **Yemen** have left 18.2 million people dependent on humanitarian assistance. In **Iraq**, UNHCR also urgently needs resources to continue supporting the authorities in ensuring access to civil documentation and inclusion in the national social safety net for some 1 million internally displaced Iraqis. UNHCR is responding to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Policy Research Working Paper 6277 #### **Abstract** Scientific evidence indicates that global warming could well lead to a sea-level rise of 1 meter or more in the 21 [st] century. This paper seeks to quantify how a 1-meter sea-level rise that would affect coastal wetlands in 76 developing countries and territories, taking into account how much of wetlands would be submerged and how likely the wetlands would move inland as the coastline recedes. It is estimated that approximately 64 percent of the freshwater marsh, 66 percent of Global Lakes and Wetlands Database coastal wetlands, and 61 percent of brackish/saline wetlands are at risk. A large percentage of this loss would be shouldered by two regions: East Asia and the Pacific, and the Middle East and North Africa. At the country level, the results are extremely skewed with a small number of countries being severely affected. In East Asia, China and Vietnam would bear the brunt of these losses. In the Middle East and North Africa, Libya and Egypt would see the most losses. A rough estimate of the economic value of the goods and services produced by wetlands at risk is approximately $630 million per year in 2000 U.S. dollars.", "output": {"entities": {"named_data": [{"text": "Global Lakes and Wetlands Database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "are also aggregated to administrative units, including for each country and subnational unit. These estimates are also aggregated to yield regional and global estimates. **4.** **Compute the number of poor people exposed to flood risk:** While poverty estimates are not available at the pixel level, the World Bank’s GMD database provides them at the subnational level for most countries. These poverty shares are multiplied with the population headcount that is estimated to be exposed to flooding, in order to obtain an estimate of the number of poor people in each administrative unit exposed to flood risk. Similarly, exposure headcount estimates are multiplied with subnational GDP per capita figures to obtain estimates of flood exposed GDP in monetary terms. **4.2.** **Stepwise computational process** The following steps are repeated for each subnational region where data are available. **Merge coastal, pluvial, fluvial flood hazard maps** - Crop fluvial and pluvial flood rasters to subnational boundary - Crop then virtually warp the coastal flood raster, using a nearest neighbors resampling method, to perfectly match the resolution and extent of the fluvial and pluvial rasters - Merge fluvial, pluvial, and coastal rasters using a maximum value method 8", "output": {"entities": {"named_data": [{"text": "World Bank’s GMD database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "**The World Bank** Costa Rica Results in Education (CORE) (P181174) provision of hardware (notebook computers and tablets) and connectivity for primary and secondary schools; in addition to computers, the Project will provide other equipment such as smart boards, projectors, headphones, robotics and related physical computation kits, routers to enhance internal connectivity); [26] and (iii) support to the development and implementation of a hybrid learning policy, its operational plan, and a communication strategy. This last activity would include the development of a national learning platform for virtual learning; implementation of a monitoring mechanism, such as the World Bank’s Education and Technology Readiness Index (ETRI); and development of digital resources such as e-books, multimedia contents, simulation exercises, and educational applications, as part of a unified learning management and competency certification system. As with foundational learning, implementation of the PNFT as part of the curriculum (it is not optative) will ensure that equal opportunity will be provided for girls and boys for all modules, and that girls will not lag behind boys in digital competencies, including coding and robotics. Computer Science teachers would be specially trained to make sure that coding and robotics activities are gender inclusive (for example in the choice of", "output": {"entities": {"named_data": [{"text": "World Bank’s Education and Technology Readiness Index (ETRI)"}], "descriptive_data": [], "vague_data": []}}}
{"input": "**Figure 3: Coastal cyclone landfalls in Bangladesh, West Bengal and Odisha:** **Median locations by period, 178 cyclonic storms, 1877-2016** **Sources: BMD, IMD, IBTrACS** **Figure 4: Coastal cyclone landfalls in Bangladesh, West Bengal and Odisha:** **Distribution of locations by period, 178 cyclonic storms, 1877-2016** **Sources: BMD, IMD, IBTrACS** 11", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "from coefficients on dummies for longer-term possession (5-12 and > 12 years, respectively) as discussed earlier. Relevant regression results and tests for relationships between coefficients, presented in table 5, lead us to conclude that granting legal protection to _bona fide_ occupants attenuates investment disincentives in a way that goes beyond the mere passage of time. In the case of tree investment and soil conservation measures _γ_ _[2]_ _L_ [ is ] insignificant and _γ_ _[1]_ _L_ [significant, suggesting that what we find is a legal rather than just a time-effect. Still, ] while it is not surprising to find that tests consistently reject the hypothesis of _γ_ _[2]_ _L_ [ =] _[ γ]_ _T_ [ at the 1% level, ] pointing towards significant under-investment on parcels that were occupied for longer than 5 years, the same equivalent hypothesis (i.e. _γ_ _[1]_ _L_ [ =] _[ γ]_ _T_ [) is also rejected at 5% throughout. This implies that, compared to ] parcels they own, households invest significantly less in parcels to which by law they have been granted permanent and heritable occupancy rights. The magnitude of such under-investment remains large; according to the point estimates, _bona fide_ occupancy on customary land", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "with six lags of the dependent variable. The Arellano-Bond regression contains one lag of the dependent variable, with this lag instrumented by five previous lags. Observation are years 1967–2004 for the fixed-effects regression, and years 1962-2004 for the Arellano-Bond regression. All regressions contain weather station fixed effects. Robust standard errors are in parentheses. ***p _<_ 0.01, **p _<_ 0.05, *p _<_ 0.1. _Source_ : Authors’ analysis based on data from BASIX and APHRODITE. This evidence casts doubt on the hypothesis that positive autocorrelation of weather events is driving increased insurance purchasing. It appears that total rainfall is actually negatively autocorrelated, whereas shocks (which are proxied by the insurance contract giving a payout) do not appear to be correlated at all. Even if there is no positive autocorrelation of rainfall, there may be other aspects about experiencing a shock that result in people having a higher propensity to purchase insurance. In order to look at the results of weather separately from the effects of insurance, I analyze how previous weather events affected insurance purchase decisions in the first year that insurance was offered to BASIX customers, which was 2005. To accomplish this, I first aggregate the purchasing data to the village", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "data from BASIX and APHRODITE"}, {"text": "BASIX and APHRODITE"}], "vague_data": []}}}
{"input": "**The World Bank** Integrated Community Resilience Project (P506969) PROJECT APPRAISAL DOCUMENT **productive inclusion and social behavior change communication (SBCC) to reduce poverty, enhance resilience to climate** **risks and support economic empowerment targeting the poor and vulnerable through financial inclusion** . Refugees and asylum-seekers, included in the 2024 census, are now part of the NSPS, and refugees were incorporated into the National Programme of Family Solidarity (PNSF) in 2023. Together, these strategies aim to build a sustainable, inclusive and shockresilient socio-economic landscape, conducive to long-term growth across the country. 8. **Over the last five years, Djibouti has made significant strides in social protection, but faces challenges in** **ensuring a comprehensive, effective and efficient social protection system that is adaptive and sustainable.** While the government has successfully piloted a targeted cash transfer program and laid the foundations for delivery mechanisms using the social registry, the NSPS highlights challenges of fragmentation (as of 2019, nine safety net programs covered different groups), inadequacy, and unpredictability. Djibouti’s social protection system is currently inadequate to shield poor and vulnerable people from adverse lifecycle impacts or encourage desirable investment in human capital and provides limited coverage. In 2012, social safety net coverage was 9.5 percent, well below", "output": {"entities": {"named_data": [{"text": "2024 census"}], "descriptive_data": [], "vague_data": [{"text": "the social registry"}]}}}
{"input": "J. Cochrane and W. Kisamba-Mugerwa. 1994. \"Tenure Security, Credit Use, and Farm Investment in the Rujumbura Pilot Land Registration Scheme, Uganda.\" In Bruce, J. W. and S. E. Migot-Adholla, eds., _Searching for Land Tenure Security in Africa_ . Dubuque, IA: Kendall/Hunt Publishers. Rugadya, M., E. Obaiko, and H. Kamusiime. 2004. \"Gender and the Land Reform Process in Uganda: Assessing Gains and Losses for Women in Uganda.\" Land Research Series No. 2. Kampala: Associates for Development. Shaban, R. A. 1987. \"Testing between Competing Models of Sharecropping.\" _Journal of Political Economy_ _95_ (5): 893-920. West, H. W. 1972. _Land policy in Buganda_ . Cambridge: Cambridge University Press. World Bank. 2003. \"Nicaragua Land Policy and Administration: Towards a More Secure Property Rights Regime.\" Report 26683NI. Washington, DC: World Bank. 26", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**pandemic, regional drought, inflation crisis and continuing global economic turbulence.** According to data from\n\nthe Kenya COVID-19 Rapid Response Phone Survey (RRPS), the Shona community experienced significant job\n\nlosses during the pandemic, particularly between July and September 2020, when unemployment increased\n\ndramatically. [[9]] This period of economic disruption caused by the pandemic led to fluctuating employment rates, as\n\nseen in the figure below.\n\n_Figure 3: Labor force participation as a percentage of working age population, between 2019 and 2024_\n\n_Source: 2019 Shona socioeconomic survey,_ [[8]] _Kenya COVID-19 Rapid Response Phone Surveys (RRPS),_ _[[9]]_ _and the authors’ calculation_\n\n_of 2024 survey data._\n\n**While employment has started to improve, it has not yet returned to pre-pandemic levels, especially for women.**\n\nThe employment rate for women decreased from 72 percent in 2019 to 61 percent in 2024, which can largely be\n\nattributed to the job losses incurred during the pandemic and slower recovery in female-dominated sectors that\n\nwere further setback by the food price crisis and global economic headwinds. Meanwhile, male employment\n\nincreased slightly from 74 percent to 76 percent during the same period, reflecting a quicker rebound in male\ndominated occupations.", "output": {"entities": {"named_data": [{"text": "Kenya COVID-19 Rapid Response Phone Survey (RRPS)"}, {"text": "2019 Shona socioeconomic survey"}], "descriptive_data": [{"text": "2024 survey data"}], "vague_data": []}}}
{"input": "24 25 Economic research on dispersal policies and labour market inclusion focuses on the strength of local labour markets and size of local ethnic networks. While some scholars find only the strength of local labour markets to be significant and not co-national networks (Foged, Hasager, and Peri, 2022), or inconsistent results for conational networks (Müller, Pannatier, and Viarengo, 2022), others find effects only for co-national networks (Damm, 2014).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\n# **Supporting \r Durable \r Solutions** **in \r South-­‐East \r Myanmar**\n\n## **A \r framework \r for \r UNHCR \r engagement**\n\n**1.** **INTRODUCTION**\n\nMyanmar \r is \r currently \r undergoing \r a \r process \r of \r significant \r and \r rapid \r change, \r which \r has\nalready \r generated \r a \r series \r of \r political, \r social \r and \r economic \r reforms \r affecting \r all \r aspects\nof \r life \r in \r the \r country. \r The \r reforms \r launched \r by \r the \r president \r Thein \r Sein \r and \r largely\nsupported \r by \r the \r opposition \r leader \r Aung \r San \r Suu \r Kyi \r have \r received \r strong \r and \r positive\nencouragements \r from \r abroad \r with \r the \r most \r immediate \r outcome \r reflected \r in \r increased\nforeign \r aid \r and \r the \r temporary \r suspension \r of \r a \r number \r of \r economic \r sanctions. \r Key \r legal\namendments \r have \r been \r adopted \r to \r ease \r restrictions \r on \r foreign \r investments, \r national\nmedia \r and \r political \r parties \r while, \r in \r addition, \r hundreds \r of \r political \r prisoners \r have \r been\nreleased \r from \r detention.\n\nIn \r late \r 2011, \r President \r Thein \r Sein’s \r Government \r pledged \r to \r make \r the \r ethnic \r issue \r a\nnational \r priority, \r offering \r dialogue \r with \r all \r armed \r groups \r and \r dropping \r preconditions\nfor \r talks. \r By \r early \r 2012, \r cease-­‐fires \r were \r agreed \r between \r the \r Government \r and \r a \r number\nof \r non-­‐state \r armed \r opposition \r groups, \r including \r the \r Democratic \r Karen \r Buddhist \r Army\n(DKBA), \r the \r Karen \r National \r Union \r (KNU), \r and \r the \r Karenni \r National \r Progressive \r Party\n(KNPP).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Regarding types of support received, most participants reported utilizing formal services with psychotherapy/counselling services being the most common (44%). Smaller numbers participated in creative psychosocial activities (19%), group or individual structured interventions designed to improve well-being (17%), psychiatry/medication management (8%), school-based services (4% overall; for children under 18, 13%), support gained from messaging materials (2%), and training for caregivers in how to support children in distress (1%). These formal services, provided by professionals or by trained specialists and nonspecialists, aim to address both clinical and subclinical mental health needs through structured, evidence-informed approaches.\n\nInformal support also played a significant role, with 33% of participants receiving support from family and friends, 12% accessing spiritual support, and 3% receiving support from their employer (e.g., flexible Regionally, 56% of participants reported receiving only formal services, 25% reported receiving only informal support, and 14% of participants reported receiving both formal and informal forms of support.\nForms of support varied across countries, with uptake of formal services ranging from 29% of participants in Hungary to 64% of participants in Poland. In some settings with lower use of formal services, participants appeared somewhat more likely to seek out or use informal supports.\n\n**21**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Investigating the district-level effects on children’s health and birth outcomes in table 7, we\n\nnote a higher number of prenatal visits and an increase in attendance of a midwife in panel A.\n\nThese results are highly statistically significant and the effects are economically significant. A\n\nmine opening increases the number of prenatal visits by 0.76 and increases the probability that\n\nthe birth was preceded by a prenatal visit supervised by a midwife by 12.5 percentage points.\n\nIn column 6 of panel A, we see that mine openings in a district reduce child mortality. The\n\nprobability of an infant dying before 12 months of age is reduced by 8.5 percentage points.\n\nGiven the importance of child mortality for human welfare, we strongly encourage future\n\nresearch to investigate the mechanisms behind these striking results. Since the share of prenatal\n\nvisits supervised by a midwife also increases with mine openings, the results potentially speak\n\nto the importance of midwives for reducing infant mortality.\n\n**Table 7 Effects of mine opening at the district level on birth outcomes and child health**\n\n(1) (2) (3) (4) (5) (6)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "- Provide \r assistance \r to \r mine \r victims \r and \r support \r Mine \r Risk \r Education \r (MRE)\nwhile \r following \r up \r and \r advocate \r for \r the \r implementation \r of \r humanitarian \r mine\naction \r including \r survey, \r mapping, \r marking \r and \r clearance \r of \r contaminated \r areas,\nespecially \r in \r areas \r of \r potential \r and \r current \r return. \r Develop \r key \r advocacy\nmessages \r and \r co-­‐ordination \r mechanisms \r to \r ensure \r that \r displaced \r communities\nare \r aware \r of \r any \r landmine \r contamination \r in \r places \r of \r origin \r and \r transit.\n\n- Advocate \r for \r the \r recognition \r of \r education \r certificates \r received \r in \r country \r of\nasylum \r and \r the \r development \r of \r bi-­‐lingual \r educational \r programmes.\n\n- Conducting \r awareness-­‐raising \r on \r SGBV \r prevention \r and \r response, \r assisting \r SGBV\nvictims \r through \r established \r referral \r mechanisms \r for \r treatment \r and \r psycho-­‐\nsocial \r support, \r and \r supporting \r community-­‐based \r protection \r solutions.\n\n- Establish \r community \r based \r mechanisms \r for \r identifying \r EVIs \r and \r provide\ntailored \r assistance.\n\n13", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "that is produced by labour alone. This can be estimated by assuming that it is equal to the labour compensation share of GDP (GDP can be divided into compensation of labour and capital), which in 2022 and 2023 stood in Poland at 48% according to the European Commission’s AMECO database.\nAccounting for that, gives a lower estimate of 0.7-1.0% GDP. Such calculations are very abstract, and do not account for other phenomena developing simultaneously in the economy, like the various effects of the war and energy shock. For this reason, we turn next to formal general equilibrium modelling, where equations of the model state explicitly every assumption about the workings of the economy and allow for a credible estimation of counter-factual scenarios.", "output": {"entities": {"named_data": [{"text": "European Commission’s AMECO database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "refugees, we have adjusted all the results proportionally to a 1.4-2.2% employment growth. First, Gradzewicz, Jabłon owski, Sasiela, and Żółkiewski (2021) use the NBP CGE model to estimate the economic impact of pre-2022 Ukrainian migrants over the 2015-2018 period, treating their inflow as a positive unskilled labour shock. If the Ukrainian refugee inflow had the same characteristics, it would yield a 0.5-0.8% higher GDP – the lower bound of our estimate. Second, Strzelecki, Growiec, and Wyszyński (2022) perform a growth accounting exercise to gauge the economic impact of the pre-2022 Ukrainian migrants over the 2014-2018 period, accounting for hours and worker characteristics to arrive at a productivityadjusted labour supply. If Ukrainian refugees had the same characteristics, they © UNHCR / Anna Liminowicz As such **4 scenarios** were calculated with options corresponding to different mixes of low and high estimation for employment and productivity while keeping stable impact on consumption: high or low employment level, similar (baseline) or lower (conservative) productivity. In the conservative productivity scenario, we assumed approximately 10% lower refugee productivity estimated based on incomes reported in MSNA Poland 2023 and data from Statistics Poland.\n\n**Table 2.** Cumulative changes in main indicators in 2023", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "data from Statistics Poland"}], "vague_data": []}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\nmake \r efforts \r towards \r an \r internal \r peace \r process \r with \r armed \r groups \r in \r the \r border \r areas,\nparallel \r debates \r emerged \r about \r the \r opportunity \r to \r return \r for \r over \r a \r hundred \r thousand\nrefugees \r from \r the \r “temporary \r shelters” [2] in \r Thailand.\n\nWhile \r the \r present \r and \r immediately \r expected \r environment \r in \r Myanmar \r does \r not \r meet \r all\nthe \r conditions \r or \r safeguards \r for \r an \r organized \r return, \r the \r changing \r environment \r makes\nit \r prudent \r that \r measures \r are \r initiated \r to \r prepare \r for \r any \r possible \r voluntary \r repatriation\nof \r refugees \r as \r well \r as \r the \r return, \r local \r integration \r or \r voluntary \r resettlement \r to \r another\npart \r of \r the \r country \r of \r IDPs \r in \r Myanmar. \r Any \r preparations, \r however, \r should \r be \r initiated\nwith \r due \r caution \r so \r as \r not \r to \r send \r the \r wrong \r “message” \r to \r the \r Government, \r non-­‐state\narmed \r groups, \r IDPs, \r refugees \r or \r partners \r that \r return \r is \r being \r encouraged \r or \r promoted\nat \r this \r stage.\n\nThis \r Discussion \r Paper \r seeks \r to \r articulate \r a \r broad \r framework \r which \r should \r guide\nUNHCR’s \r engagement \r in \r the \r South-­‐East \r in \r 2013-­‐2015, \r and \r in \r particular, \r to \r define \r the\nparameters \r of \r UNHCR’s \r role \r in \r supporting:\n\ni. durable \r solutions \r for \r IDPs; \r and\nii. the \r sustainable \r reintegration \r of \r returning \r refugees.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "treatment. District level is an additional interesting level of analysis, since it captures effects\n\nthrough the fiscal channel, and has previously been employed in, for example, Loyaza, Mier y\n\nTeran, and Rigolini (2013) to measure income inequality across mining districts in Peru. With\n\nGhana’s tax-sharing rules, district tax income and royalties increase with expansion in gold\n\nextraction (for more information, see section 2). In the district-level analysis, we first use mine\n\nopenings as the independent variable, and then we use a richer specification with production\n\nlevels. Given the spatial location of mines near district borders, we additionally analyze spatial\n\nspillovers from mining districts to neighboring districts.\n\n**4.2.1 Difference-in-differences at the district level**\n\nThe first approach is similar to the local-level approach, only an individual is defined as being\n\ntreated by a mine opening if she or he lives in a district with at least one active mine. In total,\n\nour mines are located in 11 mining districts (see figure 3). For districts with several mines, we\n\ndefine the whole district as active whenever at least one mine is active. Later, we will also\n\nconsider district total annual production (tons of gold extracted), and thereby the effect of the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "wages and reduced over-education for migrants working in licensed jobs, while producing worse labour market outcomes for those who did not gain licensure.\nAccording to Peterson et al. (2014), over the 1973–2010 period, U.S. states with more stringent occupational licensing for migrant physicians received fewer new migrant physicians and struggled more with staffing shortages in healthcare. Aleksynska and Tritah (2013) quoted data that migrants in France were denied legal access to approximately 30% of jobs in the country.\n\nUkrainian refugees Polish citizens Source: Deloitte own elaboration based on mid-2024 SEIS UNHCR survey (Ukrainian refugees’ educational attainment), 2023 Eurostat Labour Force Survey Eurostat (Polish citizens educational attainment), and mid-2024 ZUS administrative data (occupational groups).\n\n**Chart 21. Share of regulated professions by citizenship and legal status, Q2 2024**\n\n**The educational premium seems**\n\n**to be lower for Ukrainian refugees**\n\n**compared to the general workforce**", "output": {"entities": {"named_data": [{"text": "mid-2024 SEIS UNHCR survey"}, {"text": "2023 Eurostat Labour Force Survey"}], "descriptive_data": [{"text": "mid-2024 ZUS administrative data"}], "vague_data": []}}}
{"input": "and control groups being on similar trajectories before mine opening. This assumption is\n\ndiscussed below when we investigate the balance of treatment and control areas. In particular,\n\nwe test for differences in outcomes in areas where mining has not started and compare this to\n\nareas farther away.\n\nWhile we cannot show the exogeneity of the opening year to local socioeconomic variables,\n\nthis assumption has been made in previous literature (e.g. Aragon and Rud, 2015; Benshaul\n\nTolonen, 2018, 2019; Kotsadam and Tolonen, 2016, von der Goltz and Barnwal, 2019). In\n\naddition, Benshaul-Tolonen (2018, 2019) who explore gold mining, in particular, point to (i)\n\nthe rapid increase in large-scale gold mining that occurred during the recent mineral price\n\nsupercycle, (ii) the dominance of large multinational firms who are not relying on local labor\n\nmarket conditions, (iii) and their lower reliance on local infrastructure compared with bulkier\n\nmetals and minerals, as gold mining firms may fly out their resources. Despite this, the\n\nassumption of exogenous opening year or exact location remain untested.\n\nIn a second method, we use a spatial lag model. Such a model allows for nonlinear effects with", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n**The only reliable timeseries of the**\n\n**number of Ukrainians in Poland over**\n\n**the past decade is social insurance**\n\n**data on insured Ukrainian nationals,**\n\n**though it accounts only for workers.**\nThe focus on workers rather than on the entire group does not change much in the data from before February 2022, as the previous influx consisted mainly of Ukrainians seeking employment in Poland. However, the actual number of employed Ukrainian nationals must have been higher. First, certain types of legal work often undertaken by temporary employees do not require Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Chart 4. Age and gender structure of Ukrainian refugees**\n\n**Most of the refugees from Ukraine**\n\n**currently living in Poland are women**\n\n**and children, though over half of**\n\n**the total population is of working**", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "data on insured Ukrainian nationals"}], "vague_data": []}}}
{"input": "On 25 April 2023, in the midst of significant arrivals from Sudan, the Transition President promulgated\n[Decree No. 0648/PT/PM/MATDBG/2023 implementing the asylum Law (Decret d’application de la loi d’asile](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf)\n[n°0648/PT/PM/MATDBG/2023 portant modalités d’application de la loi du 31 décembre 2020). This 2023](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf)\nDecree establishes the measures to operationalize the provisions of the 2020 asylum Law. Henceforth, the\ncombined set of legal instruments, comprising the 2020 asylum Law and the 2023 Decree, is referred to as\nthe asylum legislation.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "UNHCR (2023). Poland: Multi-Sector Needs Assessment — Results Overview (MSNA 2023), October, https://data.unhcr.org/fr/documents/details/104427 UNHCR (2025a). Poland: Socio-Economic Insights Survey in Poland - Results Analysis (SEIS 2024). UNHCR, October, https://data.unhcr.org/en/documents/ details/115045 UNHCR (2025b). High employment rates, but low wages: a poverty assessment of Ukrainian refugees in neighboring countries, Regional Refugee Response for the Ukraine Situation, Regional Bureau for Europe, UNHCR.\n\nUNHCR (2025c). Ukraine Multi-year Strategy 2025 – 2027, UNHCR, November.\n\nUrban M. (2022). Refugees will lift economy's potential, but challenges remain, Research Briefing | Poland. Oxford Economics, https://www.oxfordeconomics.\ncom/resource/refugees-in-poland-will-lift-economys-potential-but-challengesremain/\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland 47", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "but has negative labour market effects due to increased competition for jobs among workers. However, little of these theoretical negative labour market effects can be seen in empirical data. This is because immigrant workers encourage further specialisation among native workers and firms, which increases productivity and offsets the negative effects. The same effects can be expected in the case of refugees entering the Polish labour market – besides increasing labour supply and competing with Polish workers, they provide new skills, ideas, and allow Polish workers to specialize in higher value-added tasks. These effects were included in the estimates of the impact of Ukrainian refugees on Polish GDP by Monitor Deloitte (2022) and Oxford Economics (2022), but these estimates were based on literature rather than Polish empirical data. In Deloitte’s 2024 study, these effects were omitted due to a lack of empirical data with which to calibrate them specifically. This study uses available data, albeit limited, to create a conservative scenario that includes positive impacts on productivity.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "Polish empirical data"}]}}}
{"input": "As of September 2024, Indonesia is host to 11,735 refugees and asylum-seekers (6,548 families)\nresiding primarily in urban areas throughout the Indonesian archipelago. Almost half of all refugees\nand asylum seekers are from Afghanistan, followed by Myanmar, Somalia, and 49 other countries.\nUNHCR has a country office in Jakarta and field presence in Aceh, Medan, Makassar, Pekanbaru, and\nTanjung Pinang.\n\nWhile Indonesia is not signatory to the 1951 Refugee Convention, there are provisions for refugee\nprotection embedded within domestic law (including the 1945 Constitution, the 1999 Human Rights\nLaw, and the 2016 Presidential Regulation on the Handling of Refugees) and Indonesia generally\nrespects the right to seek asylum and the principle of non-refoulement. UNHCR continues to work to\nadvance opportunities for refugee inclusion and participation in Indonesia, including by seeking to\nimprove access to self-reliance and to national education, health, civil registration, and social systems.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Displaced \r people \r and \r their \r host \r communities \r in \r South-­‐East \r Myanmar \r currently \r face \r a\nnumber \r of \r protection-­‐related \r risks \r and \r problems \r such \r as \r the \r lack \r of \r civil \r documentation\n(including \r birth \r registration, \r family \r lists \r and \r identity \r documentation \r in \r remote \r areas),\nlandmines, \r access \r to \r land \r and \r livelihoods, \r forced \r labour, \r forced \r recruitment, \r forced\ncontribution \r or \r taxation, \r trafficking, \r gender-­‐based \r violence \r and, \r in \r some \r cases,\nrestrictions \r of \r movement. \r The \r protection \r concerns \r are \r often \r exacerbated \r for \r IDPs \r and,\npotentially, \r refugees \r upon \r return.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "A \r profiling \r exercise \r covering \r both \r the \r registered \r and \r unregistered \r refugee \r population\nresiding \r in \r the \r temporary \r shelters \r in \r Thailand, \r will \r be \r carried \r out \r by \r the \r Mae \r Fah \r Luang\nFoundation \r on \r behalf \r of \r UNHCR \r in \r 2013-­‐2014. \r The \r exercise \r will \r permit \r updating \r of \r data\non \r areas \r of \r origin \r (Regions/States, \r districts \r and \r townships, \r and \r village \r tracts/villages)\nand \r will \r assess \r the \r intentions \r of \r refugees, \r whether \r that \r would \r be \r for \r eventual \r voluntary\nreturn, \r resettlement \r to \r a \r third \r country \r or \r other \r durable \r solution \r possibilities. \r For \r those\nrefugees \r that \r intend \r to \r return, \r information \r about \r their \r desired \r or \r intended \r destination\nwill \r be \r captured \r in \r the \r survey \r (this \r may \r include \r places \r of \r origin \r or \r prior \r habitual\nresidence, \r or \r other \r locations \r in \r Myanmar). \r The \r major \r focus \r of \r the \r survey \r is \r about \r future\n\n5", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "[Furthermore, Article 65 of the 2023 Decree specifies that refugees or asylum-seekers with a (provisional)](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf)\nresidence permit have the right to reside and move within the Chadian territory, like Chadian nationals. This\nlegislation aligns with previous practices, and there has been no change in the duration and legality of stay\nfor refugees and asylum-seekers in Chad. In practice, renewals of asylum-seekers’ certificates and refugee\nidentity cards by the authorities continue without difficulty. Over 80 per cent of consulted asylum-seekers in\n2021 reported no difficulties with the renewal of their asylum-seeker certificates.\n\nArticle 36 of the 2020 Asylum Law guarantees protection against refoulement. The 2023 Decree also\ndetails specific provisions to ensure effective respect to the non-refoulement principles including Articles\n51, 52 and 53. The Law also outlines legal provisions for cessation clauses, cancellation and revocation of\nrefugee status, adhering to international refugee law standards. Over the past three years, there has been\nno documented case of refoulement involving a refugee or asylum-seeker, nor has there been any reported\ncase of the unlawful termination of refugee status. Despite over half of arriving asylum-seekers lacking\nidentity or civil registry documentation, there have been no issues reported regarding their admission to\nthe territory.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "A significant number of refugees are concentrated in the urban areas of Poland. For one, cities generally record lower unemployment rates and higher work productivity, though the costs of living remain higher than in rural areas.\nAccording to the active population in the PESEL database, over 30% of all PESEL UKR holders had them issued in the country’s 12 biggest cities. At the same time, the results for the MSNA Poland 2023 survey suggest that these 12 biggest cities are inhabited by over 35% of refugees.\n\nRefugees record higher levels of employment inclusion in European countries that have relatively better labour market situations. In countries with lower unemployment, refugees fare better in the labour market. Since women make up the majority of refugees of working age, the situation of women on the labour market is especially important. As such, female unemployment rates explain 36% of the variation in refugees from Ukraine employment rates in studies from 11 EU Member States [22]\n\n**Chart 10.** Female unemployment and refugees from Ukraine employment in Europe\n\n70%\n\n**Chart 11.** Education attainment of Poles and Ukrainians\n\n**Eurostat** Poland LFS 2022\n\n**UNHCR**\n\n**(2023)**\n\n**NBP**\n\n**(2022)**\n\n**Ukrstat**\n\n11% 56% 48% 46% 30% Refugees from Ukraine VII-VIII 2023\n\n---\n[22] After excluding Germany and Switzerland as outliers. 23 Due to possible differences in methodologies data from this surveys should not be directly compared", "output": {"entities": {"named_data": [{"text": "PESEL database"}, {"text": "MSNA Poland 2023 survey"}, {"text": "Poland LFS 2022"}, {"text": "Eurostat"}], "descriptive_data": [], "vague_data": []}}}
{"input": "**Total of Incidents** **[5]**\n\n### Protection risks\n\n##### Protection Risk I\n\n**Discrimination and stigmatization.** Racism and xenophobia are mentioned by refugees and other\npeople in need of international protection as serious obstacles to their local integration into the\nBrazilian society. Adults report that discrimination hinders their access to dignified housing and\nthe formal labor market, [6] while children refer to being bullied in school because of their origin. [7] In\nRoraima state, the primary entry point for Venezuelans into Brazil, 44% of refugees and migrants\nreported experiencing discrimination due to their nationality. This was most prevalent in the\nworkplace (37%), during job searches (30%), and while attempting to access healthcare (24%),\neducation (21%) and also while looking for housing (20%). [8 ]", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**populations in responding to and**\n\n**shaping the assistance following a**\n\n**disaster in the Venezuelan context.**\n\nThe cluster’s participation in this space\n\nguarantees that affected populations are\n\nplaced at the heart of the emergency\n\nresponse. Additionally, the different\n\nneeds and capacities of all these groups\n\nwill shape the response plan and how\n\ncluster partners and affected populations\n\ninteract through all the phases of the\n\nHumanitarian Programme Cycle (HPC),\n\nguiding the necessary workplans.\n\nDuring the meeting of October, the new\n\nframework of AAP was presented, and it\n\nwas revised jointly by its members. This\n\nframework was created with the support\n\nand accompaniment of the Humanitarian\n\nCountry Team and the Resident and\n\nHumanitarian Coordinator. The WG\n\ncoordinator shared the minimum\n\ncommitments of the framework with\n\nthe members and opened the floor for\n\ndiscussions. The PC suggested some\n\n**coordinated the \"La Carnada\" play**\n\n**in Petare in collaboration with the**\n\n**Taller Experimental de Teatro/ Center**\n\n**for Artistic Creation (TET), IOM, and**\n\n**UNHCR on September 23rd and 24th.**\n\nThis The TET is a theatral group based\n\nin Caracas, Venezuela that was founded\n\non December 11, 1972, by Eduardo Gil\n\nunder the heart of the Central University\n\nof Venezuela (UCV) with the purpose", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "An inflow of migrants can constitute more than just an increase in the labour supply. Typically, in theoretical models an increase in the number of workers lowers the amount of capital per worker thus lowering productivity until firms invest to return the capital-worker ratio to normal, returning productivity to the previous level (Borjas, 2019). However, immigrants bring new skills to the workforce, extending the scope of specialisation and thus likely making workers more productive.\nPanel econometric studies from the past decade found, that immigration improves not just GDP or GDP per person (Ortega and Peri, 2014), but has also a causal positive impact for labour productivity (Jaumotte et al., 2016), GDP per capita growth rate (Aleksynska and Tritah, 2015), and total factor productivity (Peri, 2012).\n\n13 E.g. vice-president of Polish Development Found Bartosz Marczuk estimated it at around 16 billion PLN, but this estimation also included spending of NGOs which was combined with spendings of local governments [Polska pomoc dla Ukrainy 2022 - ile kosztowała? - Infor.pl.](https://www.infor.pl/prawo/nowosci-prawne/5635962,Polska-pomoc-dla-Ukrainy-2022-ile-kosztowala.html) 14 For example, found by Beerli and Peri (2017), Tabellini (2020), Cattaneo et al. (2015), Foged and Peri (2016), D’Amuri and Peri (2014), Ortega and Verdugo (2014), Peri and Sparber (2009).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Data sources: UNHCR PRIMES.  For more information or to contribute, please contact UNHCR RBSA DIMA (rsarbdima@unhcr.org)\n\nThe boundaries and names shown and the designations used on this map do not imply official endorsement or acceptance by the United Nations", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "7. The MSNA, which ran in 7 countries: Bulgaria, Czech Republic, Hungary, Republic of Moldova, Poland, Romania, and Slovakia 8. Equivalized as per [Eurostat methodology. Essentially income per person, but with household members beyond the first one](https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Glossary:Equivalised_income) assigned weights less than 1.\n9. With the poverty line defined as 50% of the median national equivalized income 10. This figure differs from the one reported in the [previous year’s publication due to changes to methodology, which includes a](https://data.unhcr.org/en/documents/download/108068) different treatment of households that report zero income\n\n**4**", "output": {"entities": {"named_data": [{"text": "the MSNA"}], "descriptive_data": [], "vague_data": []}}}
{"input": "In Chapter 3, we estimate the economic impact of refugees from Ukraine in Poland in general equilibrium Deloitte D.Climate model. This is the gold standard of economic modelling on the macro-level, which comprehensively accounts for the supply side of the economy including labour supply and productivity, and the demand side including consumption as well as taxation. Unfortunately, such macroeconomic models cannot account for how exactly refugees and other migrants enable native workers to specialise in better paid professions (occupational upgrading), or how firms allow for new skills by adapting different production technologies. As such, our estimates should be treated as a conservative lower bound of the effect.\n\nFurthermore, in Chapter 4, we move beyond theoretical modelling, to examine empirical studies on how immigrants and refugees impact not just output, but labour productivity as well. This effect comes not from traditional supply-demand analysis, but from increased specialisation.\nImmigrants enable occupational upgrading of residents, supply new skills to firms, enter household works services that allow highly productive native women to increase labour supply, and exhibit high rates of entrepreneurship.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Among the 23% of individuals reported to have mental health or psychosocial problems affecting daily functioning (such as the ability to get out of bed, care for oneself or others, or carry out daily activities such as cooking, going to school), 46% (47% of women and girls; 42% of men and boys) reported trying to access support. This means that more than half (54%) of individuals experiencing such problems did not try to access support, which may be due to multiple factors, including stigma, mental health awareness, or other access barriers.\n\n**20**\n\n(N=4,053) Of those individuals who reported trying to access support, almost all (96% overall; 97% of women, 94% of men) reported successfully accessing and receiving some sort of support. This high rate of access is partly explained by the inclusion of both formal services, such as psychotherapy, psychiatric care, or structured group interventions, and informal support, such as help from family, friends, employers, or spiritual leaders. By encompassing a broad spectrum of support mechanisms, the findings capture the diverse ways individuals seek and receive assistance, highlighting the importance of informal networks in complementing formal MHPSS services.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "rush. During this period, annual gold production has increased by 700 percent, as shown in\n\nFigure 1. It is the expansion that has happened during this recent gold rush that is used in this\n\nanalysis to understand the socioeconomic effects of mining. The high international gold price\n\nwas a driving factor in the expansion of small-scale mining, such as the 2,700% increase in gold\n\nmining territory around the Offin River between 2008 and 2012 (Hausermann et al., 2018).\n\nBetween 2006 and 2012, two large-scale mines opened in Ghana, but no mine closed down\n\n(Table 1) possibly due to the high gold price increasing profitability and extending life length.\n\nThe expansion across artisanal small-, medium-, and large-scale mining contributed to an\n\nincrease in total production that rose from 541,147 oz in 1990 to 3,119,823 oz in 2009 according\n\nofficial Ghana statistics (Bloch and Owusu, 2012). This production increase led to an increased\n\nsector contribution to GDP from 4,83% (1990) to 5,78% (2009), alongside export value of\n\nUS$304m in 1990, US$702m in 2000, and US$2246 m in 2008, reaching 43% of national\n\nexports in 2008. Mining related foreign direct investment (FDI) also rose from US$165m to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "official Ghana statistics"}]}}}
{"input": "Securing \r durable \r solutions \r for \r displaced \r populations \r should \r be \r an \r integral \r component\nof \r the \r peace \r process, \r and \r the \r engagement \r of \r UNHCR \r and \r other \r actors \r in \r support \r to\ndurable \r solutions \r should \r be \r located \r within \r a \r broader \r peace-­‐building \r framework. \r In\naddition \r to \r advocating \r for \r the \r participation \r of \r IDPs \r and \r refugees \r in \r the \r peace\nnegotiations, \r activities \r in \r support \r of \r durable \r solutions \r should \r be \r grounded \r in \r sound\nconflict \r analysis. \r The \r provision \r of \r assistance \r should \r be \r conflict-­‐sensitive, \r minimizing\nunintended \r negative \r impact \r while \r maximising \r its \r peace-­‐building \r impact, \r and \r use \r “Do \r No\nHarm” \r approaches \r to \r contribute \r at \r building \r trust \r and \r supporting \r the \r peace-­‐building\nprocess. \r Co-­‐existence \r projects \r and \r other \r activities \r should \r be \r prioritised \r in \r support \r of\nreintegration. \r Activities \r such \r as \r peace \r education \r and \r conflict \r resolution \r training \r may \r be\nundertaken \r even \r prior \r to \r an \r organised \r voluntary \r return.\n\nRefugees \r and \r IDPs \r will \r frequently \r opt \r to \r spread \r risk \r and \r to \r cushion \r the \r impact \r of \r return\nby \r having \r some \r family \r members \r remaining \r outside \r the \r country, \r or \r move \r elsewhere\nwithin \r the \r country \r to \r pursue \r migration \r strategies. \r This \r should \r be \r facilitated \r and \r not\nviewed \r as \r a \r failure \r of \r the \r reintegration \r process.\n\n**6.** **NATIONAL \r OWNERSHIP \r AND \r CO-­‐ORDINATION**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Among adolescent girls aged 15- 17 who faced access barriers (N=13), the lack of knowledge took the lead ahead of the waiting times and financial barriers. Moreover, compared to women, adolescent girls reported lower levels of trust in local healthcare providers. For all young women aged 18-24 who reported barriers (N=30), the most significant were long waiting times and inability to make an appointment.\n\nAmong pregnant and breastfeeding women (N=441), 5% reported facing barriers in accessing SRH services. For those experiencing barriers, half lacked knowledge about where to access SRH services and one in five did not trust local healthcare providers, in addition to facing language barriers.\n\nWomen with a disability reported more barriers with 11% across the region (N=29) compared to those without disability (5%).\n\nAn in-depth assessment is needed to better understand sexual and reproductive health (SRH) needs, the role of SRH access barriers in decisions to visit Ukraine, and how these barriers vary among women of different age groups, pregnant and breastfeeding women, and women with disabilities.\n\n**Support services for survivors of gender-based**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "### **Verification Exercise**\n\nUNHCR is undertaking a country-wide verification exercise in 2024. The project enables UNHCR staff\nto systematically connect with and update registration data for every refugee and asylum seeker in\nIndonesia.  UNHCR protection/registration teams are updating family composition and recording\ninformation on specific needs and vulnerabilities, skills, work experience, education levels, and family\nconnections outside Indonesia. The information collected will provide a clean and accurate set of data\nthat will enable UNHCR to better develop and target programming for the refugee population and will\nassist in identifying individuals who may qualify for solutions outside Indonesia.\n\n©UNHCR/Amanda Jufrian\n\nUNHCR / 1 November 2024 10", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Sona Tahery, a young Afghan woman, found safety in Brazil after fleeing severe restrictions on women’s rights and access to work_\n_in her home country. After spending a year as a refugee in Iran, she arrived with her sister and brother-in-law, seeking a new_\n_beginning. Now, at Todos Irmãos Shelter in Guarulhos, she is rebuilding her life with dignity and hope._ © _UNHCR// Diego Baravelli_\n\n##### Protection Risk III\n\n**Gender equality and access to rights for refugee women and girls.** Refugee women and girls face\nsignificant barriers to the realization of their rights due to gender roles and power disbalances.\nRegardless of their nationality, women and girls face higher unemployment rates, less access to\neducation opportunities, greater exposure to gender-based violence and additional caregiving\nresponsibilities. [26] Members of the LGTBQIA+ community face discrimination and stigmatization\ndue to their sexual orientation and gender identity, and experience barriers in their access to\ndignified livelihoods with some of them, especially transgender women, resorting to survival sex\nas one of the few viable means to earn a living in the country. [27]", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "only statistically significant for boys at an effect size of 6.6 percentage points.\n\n**Table 5 OLS estimates of birth outcomes, infant survival, and child health in the DHS individual-**\n\n**level analysis**\n\nPANEL A                 size at birth            infant mortality (<12months)         antenatal visits\nsmall average large all boys girls # visits at least 1\nactive*mine 0.022 0.053 -0.075* -0.041* -0.066** -0.020 -0.151 -0.007\n(0.028) (0.041) (0.041) (0.022) (0.030) (0.035) (0.331) (0.028)\nmine -0.010 0.071** -0.061** 0.004 0.008 0.001 0.153 0.000\n(0.019) (0.028) (0.030) (0.015) (0.020) (0.024) (0.241) (0.019)\nactive -0.010 0.054** -0.044 0.002 0.014 -0.012 0.012 0.002\n(0.016) (0.026) (0.027) (0.014) (0.022) (0.018) (0.209) (0.012)\n\nObservations 6,771 6,771 6,771 5,356 2,718 2,638 5,704 5,704\nR-squared 0.031 0.054 0.059 0.135 0.160 0.152 0.186 0.062\nMean of dep var. 0.136 0.359 0.505 0.073 0.08 0.066 5.79 0.941\n\nPANEL B in the last 2 weeks, had: anthropometrics (WHO) in sd has\nfever     cough    diarrhea ht/a       wt/a      wt/ht health card\n\nactive*mine -0.035 -0.061* 0.042 -3.532 -5.208 -0.641 0.014\n(0.037) (0.033) (0.027) (11.472) (9.283) (8.948) (0.027)\n\nmine -0.002 -0.006 -0.038 -0.828 3.481 3.853 -0.006\n(0.031) (0.028) (0.024) (10.385) (8.574) (7.468) (0.022)\n\nactive 0.023 -0.003 -0.033** -1.904 5.265 9.433* 0.009\n(0.020) (0.020) (0.016) (5.942) (5.304) (5.183) (0.012)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Macroeconomic modelling generally finds that immigration increases output, while cross-country econometric estimates find also positive impacts on labour productivity. The first approach builds a theoretical model of the economy calibrated to the particular circumstances, which allows us to simulate counterfactuals and observe all changes in the economy.\nThe second approach relies on empirical data, usually over many years and countries, trying to isolate the effect of immigration, but gives no information on the channels through which these effects operate. In the present case it would not be practical to follow anything else than the first approach. Unfortunately, it relies on the canonical labour market model.\nAs Peri (2014) elaborates, that model assumes that immigration is simply a shift in the labour supply for a given labour demand and given labour supply of native workers. It further assumes that immigrants are essentially identical to natives in that they enter the same 38", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "empirical data"}], "vague_data": []}}}
{"input": "It \r builds \r upon \r a \r separate \r discussion \r paper \r dated \r 1 \r October \r 2012, \r which \r sets \r out \r a\nframework \r for \r voluntary \r repatriation \r for \r Myanmar \r refugees \r from \r Thailand. \r The \r papers\nshould \r form \r the \r basis \r of \r a \r more \r detailed \r operational \r strategy \r for \r 2013-­‐2015, \r and \r should\nalso \r serve \r as \r the \r first \r step \r towards \r a \r consultative \r multi-­‐stakeholder \r process, \r engaging\nGovernment, \r civil \r society, \r UN \r and \r NGO \r partners, \r donors \r and \r refugees \r and \r IDPs\nthemselves, \r to \r elaborate \r a \r shared \r vision \r and \r strategy \r for \r support \r to \r durable \r solutions \r in\nthe \r South-­‐East. \r The \r document \r outlines \r UNHCR’s \r general \r principles \r and \r standards \r as\nwell \r as \r context-­‐specific \r objectives \r and \r activities.\n\n**2.** **CONTEXT**\n\n**2.1. \r Political \r environment**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\nfrom \r the \r temporary \r shelters \r in \r Thailand \r to \r their \r place \r of \r origin, \r the \r majority \r of \r whom\nare \r single \r males \r who \r stated \r that \r they \r had \r returned \r to \r assess \r the \r security \r situation \r and\nstart \r re-­‐establishing \r their \r livelihood \r before \r the \r return \r of \r other \r family \r members. \r The\ndimensions \r of \r this \r spontaneous \r return \r movement \r have \r been, \r so \r far, \r negligible.\n\nWhile \r the \r dimensions \r of \r IDP \r return \r movements \r remain \r extremely \r difficult \r to \r assess,\nsome \r 37,000 \r IDPs \r are \r estimated \r by \r the \r The \r Border \r Consortium \r (TBC) \r to \r have \r returned\nhome \r or \r resettled \r in \r surrounding \r areas \r between \r August \r 2011 \r and \r July \r 2012 [3] .\n\nIf \r the \r current \r trend \r of \r political \r and \r socio-­‐economic \r reforms \r continues \r and \r as \r larger\npolitical \r events \r draw \r closer, \r such \r as \r the \r ASEAN/AEC \r agenda \r with \r Myanmar \r as \r Chair \r in\n2014, \r a \r national \r census \r in \r 2014, \r and \r national \r elections \r in \r 2015, \r then \r the \r momentum \r to\ntranslate \r cease-­‐fire \r negotiations \r into \r peace \r agreements \r may \r increase. \r This \r may \r lead \r to\nan \r increase \r in \r the \r number \r of \r spontaneous \r returns \r and \r the \r possibility \r of \r sudden\ndemands \r upon \r UNHCR \r to \r facilitate \r the \r voluntary \r repatriation \r of \r refugees.\n\n**2.2. \r Protection \r environment**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Regionally, 6% of men aged 18–34 report a disability, compared to 2% of women in this age group. A similar trend is observed for the 35–59 age group, with 8% of men and 4% of women reporting a disability respectively. The higher prevalence among men is likely related to the fact that men without a disability are less likely to leave Ukraine.\n\n0-4 5-17 18-34 35-59 60+ years old (N=19,622) These findings suggest that health services should be tailored to address these gender and agerelated dynamics, as should the dissemination of information about available services.\n\n**9**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Chart 19. Tertiary education and corresponding** **Chart 20. Ukrainian refugees median net wages by**\n\n**occupational groups shares** **educational attainment**\n\n4,300 4,275\n\n**Addressing occupational downgrading**\n\n**could bring macroeconomic benefits.**\nTo demonstrate the potential impact, a simulation was conducted in which the underrepresentation of refugees in higher-paying occupations was reduced by half. It was not assumed that there would be no differences between refugees and Polish citizens, as some barriers (such as Analysis of the impact of refugees from Ukraine on the economy of Poland country-specific knowledge and business networks) are more difficult to address than others (such as language skills and occupational licensing). However, if the gap was narrowed by half, the average wage of refugees would increase by approximately 10%. Assuming that the productivity increase is equivalent to the wage increase, this would result in PLN 3.5 billion of added 40% Tertiary education share 25-64 age group surveys Managers, professionals, and technicians ZUS-insured employment share", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE\n\n**Regular employment** **[11]** **- key for refugee household**\n\n**prosperity**\nThe income composition of refugee households above and below the poverty line is very different.\nRegular employment represents 74% of total income in the wealthier group compared to just 35% for lower earners. In part, this is explained by higher labor force participation [12] (68% vs 49%), which is tied to differences in household composition. The age dependency ratio [13], for example, stands at 52% in the higher earning group versus 77% for households with a lower income. Additionally, however, members of households above the poverty line are significantly more successful in finding work - their unemployment rate is twice as low at 10%, and half as many are working part time (14% vs 31%).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "To show the robustness of these results, we have tried three alternative strategies for each of\n\nthe outcomes. In row 2, we drop the sample that lives 20 to 40 km away, since they might be\n\naffected by the mine; in row 3, we drop the sample that was surveyed two years prior to mine\n\nopening; in row 4, we add closest mine fixed effects; and in row 5 we cluster on the closest\n\nmine. The coefficients do not change much, even if some magnitudes become bigger and the\n\nestimates more significant. However, as in the results using DHS data, these estimates are not\n\nprecisely measured – few are statistically significant because the standard errors appear large.\n\nWomen are 7.4 to 10.4 percentage points more likely to work in service or sales if they live\n\nclose to a mine (depending on the estimations in panel A columns 4, only one statistically\n\nsignificant estimate). Women close to mines are 2.5 to 2.6 percentage points more likely to\n\nwork in mining (only one statistically significant estimate).\n\nMen, on the other hand, (results shown in panel B of table 12), are significantly more likely to", "output": {"entities": {"named_data": [{"text": "DHS data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "to work, but only in a designated health care center, and for no longer than five years without the possibility of extension.\nIn February 2022, Ukrainian psychologists were allowed to provide services to other Ukrainian citizens, but only for 18 months.\nWhile such changes are likely to be extended, they do not motivate Ukrainian refugees – unsure, if they will be allowed to continue practice in the long term – to acquire the necessary skills, for instance to improve language fluency or invest in professional courses. Instead, the refugees may prefer to seek opportunities in other countries or change their line of work to one that will be more accessible, but less valuable for the Polish economy.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# Non-technical summary\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland Swift legal action facilitated labour market integration of refugees. After the beginning of the full-scale war on 26th February 2022, the European Union activated the Temporary Protection Directive on 4th March 2022, and the Polish parliament passed a special act to facilitate refugee integration on 12th March 2022. Ukrainian refugees in Poland were granted instant access to the job market, health care, and education. The authorities granted people escaping Ukraine legal residency for a period of eighteen months and enabled them to access digital services and basic administrative systems like PESEL.\nThus, the policies that have previously hampered job market integration of refugees in other contexts, such as temporary labour market bans (Fasani, Frattini, & Minale, 2021) and forced dispersals (Fasani, Frattini, & Minale, 2022), have been avoided.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_On World Refugee Day, refugees and local families in Porto Alegre's Sarandi neighborhood shared a meal and received support._\n_The event, organized by UNHCR partners, acknowledged the solidarity shown during recent floods and celebrated the rebuilding_\n_of lives by refugees from Venezuela, Haiti, Colombia, and Afghanistan, among others._ © _UNHCR/Ricardo Ara._\n\n### Challenges & Opportunities\n\nSince 2018, Brazil has supported refugees and migrants from Venezuela through a comprehensive\nhumanitarian federal initiative known as “Operacao Acolhida” . The Operation primarily focuses\non the northern State of Roraima, the main entry point for Venezuelans into Brazil, where\nreception, documentation, shelter, and other forms of humanitarian assistance are provided.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "and girls. Maternal and reproductive health services remain underdeveloped in some areas, struggling\nto be fully effective due to a lack of material and financial support.\n\n**5.2** **Social inclusion**\n\nThe most significant differences or restrictions in terms of socio-economic development affecting refugees\nwith particular characteristics are:\n\n**a.** **Access to biometric identity cards and unique identifier number:** The continued lack of access to\n\nlegally recognized identity cards for refugees issued by the competent authority in Chad, ANATS, and\nnational identification numbers, challenges their inclusion into national system and limits their socioeconomic integration in the country.\n\n**b.** **Access to civil registry civil status documents:** The low percentage of registered births, due to\n\nsignificant deficiencies in the Civil Registration and Vital Statistics (CRVS) system in Chad, especially in\nrural areas, exposes refugees born in Chad to the risk of statelessness.\n\nR E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **R E P U B L I C O F C H A D** 13", "output": {"entities": {"named_data": [{"text": "Civil Registration and Vital Statistics (CRVS)"}], "descriptive_data": [], "vague_data": []}}}
{"input": "of human trafficking in different states of\n\nVenezuela through a service mapping\n\nexercise that was implemented.\n\n**IX. Protection Mainstreaming**\n\n**Training**\n\n**The PC in collaboration with the**\n\nof Performing Arts, over 140 people\n\nattended the play, including community\n\nmembers, representatives from NGOs\n\nand INGOs, and agency representatives.\n\nDrawing on testimonies and real\n\ndata, and with the technical support\n\nof UNHCR, IOM, and the Venezuela\n\nProtection Cluster, the authors of the\n\nplay have crafted an original and avant\ngarde dramaturgy that highlights the\n\nissue of TiP and its associated risks. Two\n\nadditional performances are scheduled\n\nfor the last week of November (in\n\nPetare) and another in December in\n\nChichiriviche de La Costa, La Guaira,\n\nin commemoration of the 16 days of\n\nactivism for the International Day for the\n\nEradication of Violence against Women.\n\n**VI. Annual TiP Bulletin 2022-2023**\n\n**After one year of the creation of the**\n\n**6**\n\n**WGTiP, an annual bulletin was pub-**\n\n**lished in October.** This document\n\nconsolidates information from the quar\nterly bulletins of 2022 and 2023 and\n\nprovides a context analysis of TiP in\n\nVenezuela, raising awareness on new\n\ninformation and dynamics and highlights\n\ncounter-trafficking efforts of members\n\nwith a specific focus on activities for the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "agri- service profess- manual not earns works\nculture sales ional labor working cash all year\nPANEL A: Women\n\nactive*mine -0.025 0.024 -0.017* 0.012 0.006 0.054** -0.013\n(0.039) (0.031) (0.009) (0.021) (0.023) (0.026) (0.033)\nmine -0.025 0.056* -0.001 -0.012 -0.018 -0.069*** -0.012\n(0.031) (0.029) (0.008) (0.018) (0.020) (0.022) (0.024)\nactive 0.014 -0.000 -0.006 0.009 -0.016 -0.037** -0.007\n(0.015) (0.016) (0.006) (0.011) (0.012) (0.015) (0.016)\n\nObservations 12,176 12,176 12,176 12,176 12,176 9,262 7,085\nR-squared 0.350 0.103 0.124 0.024 0.234 0.095 0.042\nMean of dep var. 0.237 0.358 0.045 0.117 0.739 0.891 0.877\n\nPANEL B: Men\n\nactive*mine 0.050 0.020 0.027 -0.069* 0.006 -0.013 -0.015\n(0.051) (0.020) (0.026) (0.036) (0.023) (0.028) (0.051)\nmine -0.060 0.002 0.000 0.041 -0.018 -0.009 0.066*\n(0.042) (0.016) (0.020) (0.030) (0.020) (0.028) (0.039)\nactive 0.000 0.002 -0.001 -0.029 -0.016 -0.107*** -0.025\n(0.021) (0.014) (0.015) (0.020) (0.012) (0.039) (0.028)\n\nObservations 7,157 7,157 7,157 7,157 7,157 4,374 2,794\nR-squared 0.290 0.415 0.084 0.183 0.076 0.107 0.104\nMean of dep var. 0.328 0.111 0.137 0.214 0.209 0.928 0.841", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The overlap between certain mental health problems, such as difficulties with memory, concentration, or self-care, and the criteria used to assess disability further demonstrates the complex interplay between these factors. The data also suggests that structural and systemic differences between countries may influence outcomes, as reflected in the varying rates reported. These findings highlight the critical need for inclusive MHPSS strategies that address the unique needs of individuals with disabilities and provide targeted interventions to reduce barriers and ensure equitable access to support. Additionally, further analysis of country-specific contexts could help uncover underlying factors driving these disparities.\n\n**% OF INDIVIDUALS WHO REPORTED EXPERIENCING**\n\n**A MENTAL HEALTH OR PSYCHOSOCIAL PROBLEM BY**\n\n**DISABILITY STATUS AND COUNTRY**\n\nWith disability Without disability Regional Romania Hungary Poland Bulgaria Estonia Lithuania Slovakia Czechia Latvia Moldova (N=17,934)\n\n**25**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**positive impact on labour productivity.**\nIn the earlier report, the overall positive impact of refugees was reduced based on conservative assumptions, in the absence of available/clear data on the increased competition in the labour market. The model notably considered lower wages and higher unemployment among native workers. However, recent data indicates that these concerns did not materialize.\nInstead, Polish workers have moved on to better paid occupations, and the economy has benefited from a larger pool of talent, enabling deeper specialization and increased productivity growth.\n\n##### Remaining challenges\n\n**Despite significant progress in**\n\n**integrating refugees into the labour**\n\n**market, several challenges persist.**\nRefugees are half as likely to have an employment contract as Polish citizens and few of them achieve high incomes.\nAlthough refugees have been moving on to more desirable professions at a faster rate than other groups in the economy, their jobs continue to be disproportionately skewed towards elementary occupations.\nThese issues are most evident among those with university diplomas, but those with below university education also face obstacles. As of June 2024, there were several interconnected issues:\n\n**•** **There is a disparity between the**\n\n**educational attainment and labour**\n\n**market position of refugees,**\n\n**reflecting their significant over-**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "recent data"}]}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n### **Contents**\n\n###### Executive summary\b 3 Context \b 5 Methodology \b 6 Limitations \b 7 Sample demographics \b 8 Health analysis \b 10 Mental Health and Psychosocial Support (MHPSS)\b 19 Recommendations\b 28\n\n### **Acknowledgements**\n\nWe gratefully acknowledge the contributions of many individuals and organizations who contributed to this report. The regional analysis was facilitated by the Regional SEIS Health and Mental Health Sector Analysis Group, co-coordinated by Ardita Tahirukaj (WHO), Sandra Harlass (UNHCR), Monica Zikusooka (WHO) and Sofia Casas (UNHCR). The data analysis was conducted by Irma Sirutyte (UNHCR). Writing of the report was led by the co-coordinators along with Arianna Pearlstein (UN Women), Iuliana Gutu (UNFPA), Leah James (UNICEF), Liqun Gao (UNHCR), and Luna Mehrain (UNFPA).\n\nThanks to Jad Ghosn and the Regional Bureau for Europe (UNHCR) for their guidance, review and support on the regional SEIS analysis for health and MHPSS.\n\nAcknowledgements include also those who reviewed the report: Agron Gashi (UNICEF), Chiaki Ito (IOM), Erin Autumn Neale (IOM), Greisy Trejo (IFRC), Heide Rieder (IOM), Melita Murkom (WHO), Pieter Ventevogel (UNHCR), Ursula Wagner (IOM).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "would increase GDP by 0.9-1.3% – the mid to higher bound of our estimate.\nThird, Urban (2022) uses an Oxford Economics model to estimate the impact of Ukrainian refugees on the potential GDP by 2030 and 2050, including a positive shock to the total factor productivity growth. This yields GDP higher by 1.5-2.6% by 2030, significantly higher than our long-term estimate – the higher result is likely due to the increase in TFP that we do not include in our modelling. Fourth, Monitor Deloitte (2022) provided an early wide estimate of the economic impact of Ukrainian refugees.\nThis would translate into 0.9-2.4% higher GDP, also due to the possibility of a positive productivity shock. We review the relevant literature on the impacts of immigration on productivity in Chapter 4.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "mean value of the independent variable is 0.085 - that is, on average women are close to 0.085\n\nmines. Conditional on being close to a mine, the main independent variable is 1.33 - that is, a\n\nwoman sampled close to a mine is close to 1.33 mines on average. Panel C of table A3 shows\n\nthe effects on women’s labor market participation. We note that the estimates are similar in\n\ndirection as before, where mines are positively associated with service and sales jobs and with\n\ncash earnings, but negatively associated with agriculture and professional jobs.\n\nPanel D of table A3 shows the results if we drop the part of the sample that lives 20 km to 40\n\nkm away from a mine, and if we drop those that are sampled two years before mine opening.\n\nThe rationale for this is to have a cleaner control group, since those that live just outside our 20\n\nkm cutoff distance may also be “treated” by the mine, and the investment phase of the mine\n\nthat precedes initial production can generate substantial employment. Overall, the effects do\n\nnot change much except making the cash earnings coefficient larger and more significant. The", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Source: Deloitte own elaboration based on mid-2024 SEIS UNHCR survey (Ukrainian refugees’ educational attainment and median net wages), 2023 Eurostat Labour Force Survey Eurostat (Polish citizens educational attainment), and mid-2024 ZUS administrative data (occupational groups).\n\n**Widespread occupational licensing**\n\n**is a serious obstacle to an efficient**\n\n**use of Ukrainian refugees’ human**\n\n**capital.** Poland has the third highest\nnumber of regulated professions among the 28 European Union member states, according to European Commission’s Regulated Professions Database. This can be a problem, as occupational licensing is cited in the literature among the reasons for occupational downgrading of migrants.\nCassidy and Dacass (2021) found that in the United States, immigrants were significantly less likely to have a license than similar\n\n#### **4.2 Access to regulated professions**", "output": {"entities": {"named_data": [{"text": "2023 Eurostat Labour Force Survey"}, {"text": "European Commission’s Regulated Professions Database"}], "descriptive_data": [{"text": "mid-2024 ZUS administrative data"}], "vague_data": []}}}
{"input": "Expanding community-based MHPSS services that integrate formal services and promote the use of informal supports will enhance service delivery.\nPublic awareness campaigns, tailored to both refugees and host communities, should aim to reduce stigma and improve knowledge of available support. Gender-responsive and age-sensitive approaches are necessary, particularly for adult men and adolescent boys, to encourage help-seeking behaviours and ensure that services are tailored to the specific needs of children and adolescents.\nLastly, further research is required to gain a deeper understanding of unmet health needs—including SRH and MHPSS needs—and the barriers to access, to inform more effective, inclusive, and contextsensitive interventions.\n\n**4**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "increase in off-shore oil revenue accruing to municipalities, alongside increased illegal activity\n\nby mayors (Caselli and Michaels, 2010). We estimate district level effects on living standards\n\n(in mining districts, but no spillovers to adjacent districts, in line with Mamo et al, 2019), but\n\ndo not have further information on public spending by sector to put these effects in context to\n\nexpected changes. Political outcomes such as clientelism, corruption and reelection of local\n\n36", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Deloitte’s D.Climate general equilibrium model finds that refugees from Ukraine contributed 0.7-1.1% to GDP cumulatively in 2023. In the long-term this effect will grow to 0.9-1.35% as the economy fully adjusts.\nThe increases in government revenue from direct and indirect taxes due to wages and private consumption of refugees from Ukraine was likewise modelled.\nThese increases amounted to 0.8-1.0% higher general government revenues in 2022, 1.3-1.6% in 2023, and 0.95-1.13% in the long term. This implies that, while there are no precise public data on the government support to refugees from Ukraine, while a government official quoted cost figures of 15-20 billion PLN in 2022 and around 5 billion in 2023 [50] have been already offset by refugees via taxes of 12.3-15.2 billion PLN in 2022 and 18.2-22.5 billion PLN in 2023.\n\nAll the modelling results are conservative lower bound estimates, as econometric studies from other countries have found immigration to have additionally a positive impact on labour productivity that cannot be accounted for using the available data.\nThese effects could stem from the growth in specialisation due to additional workers with different skillsets appearing on the labour market, e.g., occupational upgrading of native workers.\n\n---\n[50] E.g. vice-president of Polish Development Found Bartosz Marczuk estimated it at around 16 billion PLN, but this estimation also included spending of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The regional analysis is grounded in consolidated data from the Socio-Economic Insights Survey (SEIS), conducted across ten countries: Bulgaria, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Republic of Moldova, Romania, and Slovakia. Data for the country-specific SEISs were collected through in-person interviews from May to July 2024.\n\nThe total sample size comprises **8,720 households** and **19,803 household members**, with respondents providing information on behalf of all individuals within their households.\n\n**COUNTRY** **SAMPLE SIZE 2023** **SAMPLE SIZE 2024**\n\nBulgaria 1,054 1,072 Czechia 1,218 1,215 Estonia - 600 Hungary 682 801 Latvia - 600 Lithuania - 638 Moldova 890 622 Poland 5,645 1,290 Romania 1,222 1,008 Slovakia 819 874\n\n**Total** **11,530** **8,720**\n\nEach country adopted a unique sampling approach, dependent on factors such as the availability of sampling frames and information regarding population distribution by geographic area and accommodation type. A combination of different sampling methods was used, typically incorporating multiple stages and blending convenience sampling, cluster random sampling, and simple random sampling (the latter being exclusive to Romania). It is important to highlight that Hungary and Moldova modified its sampling approach, which limits the comparability of its results across years.", "output": {"entities": {"named_data": [{"text": "Socio-Economic Insights Survey (SEIS)"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland Analysis of the impact of refugees from Ukraine on the economy of Poland To account for refugees impact on economy shocks for economy were calibrated according to existing data.\nAs the refugees started coming to Poland by the end of February and in March 2022 it was assumed that their impact on the economy should be seen starting from the second quarter of 2022. As such their primary impact on yearly data was divided as between 2022 and 2023 setting 3⁄4 of it in 2022 and 1⁄4 in 2023. The total number of refugees was set according to the newest data from the PESEL registry (Chart 3. in Chapter 1). Their employment was calibrated to match data presented in Chapter 2. Changes in population and", "output": {"entities": {"named_data": [{"text": "PESEL registry"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Box 1.** Inflow of savings from Ukraine\n\n**Chart 13.** Income structure of Ukrainian refugee households\n\n**5%** **1%**\n\nWork (regular-, temporary-,and self-employment in Poland, remote employment in Ukraine Remittances from friends/relatives Polish government benefits (Family 500+, cash benefits, disability grants) Ukrainian government benefits (pensions, disability grants, parental benefits) Other (humanitarian organizations, other sources)\n\n**Source:** Deloitte elaboration based on the MSNA Poland 2023. The work category includes regular employment, temporary work, self-employment\nand remote work in Ukraine.\n\n31 [Cudzoziemcy w polskim systemie ubezpieczeń społecznych (zus.pl)](https://www.zus.pl/documents/10182/2322024/Cudzoziemcy+w+polskim+systemie+ubezpiecze%C5%84+spo%C5%82ecznych_2022.pdf/) 32 According to NBP (2023), there were few respondents in this situation, and they most likely had secured other sources of income.\n\n28 29", "output": {"entities": {"named_data": [{"text": "MSNA Poland 2023"}], "descriptive_data": [], "vague_data": []}}}
{"input": "The government of Chad continues to ensure the security of refugees and asylum-seekers through the\nHumanitarian Workers and Refugee Detachment (DPHR). Generally, refugees are not more exposed to\n[existing violence and crime. According to protection data collected through Project 21](https://response.reliefweb.int/west-and-central-africa/protection/projet-21) (‘regional protection\nmonitoring’) approximately 15 per cent of refugees and asylum-seekers claim to have been victims of\nphysical assault, but it is noteworthy that these cases occurred in the country of origin at the time of fleeing.\n\nWhile rape and child marriage remain prohibited by Law, other forms of gender-based violence (GBV)\nare insufficiently covered by existing Laws and policies to protect the Chadian and refugee populations.\nThe national policy to respond to GBV, in effect since 2011, applies in refugee camps and refugee hosting\nvillages but faces challenges due to limited resources (human and logistic) to fully implement this policy. The\nreferral mechanism for refugee victims for medical, legal and psychosocial support remains in place but its\neffectiveness depends on the human and financial resources available in the relevant hosting areas.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "protection data collected through Project 21"}], "vague_data": []}}}
{"input": "45 Based on number of economically active people in III quarter of 2023 according to labour market survey.\n46 E.g. vice-president of Polish Development Found Bartosz Marczuk estimated it at around 16 billion PLN, but this estimation also included spending of NGOs which was combined with spendings of local governments Polska pomoc dla Ukrainy 2022 - ile kosztowała? - Infor.pl.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "labour market survey"}]}}}
{"input": "labour supply in Poland were offset by equivalent changes for Eastern Europe region [41] . It was also assumed that refugees should have higher spending needs which means a lower saving rate than natives.\nMoreover, data shows that it is partially financed by savings they have in Ukrainian banks which was calibrated as them having negative saving rate while being offset by lowering investment levels in Eastern Europe [42] . Lastly, their productivity may differ from productivity of natives (Box 2) which also was taken into account.\nIn total there were three major sources of uncertainty: total level of employment, productivity, and impact on consumption.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The \r sustainability \r of \r IDP \r (and \r potentially, \r refugee) \r returns \r is \r also \r still \r hampered \r by\nlimited \r access \r to \r livelihood \r opportunities. \r At \r present, \r access \r to \r livelihood \r resources \r and\ntraining \r opportunities \r are \r scarce. \r Returning \r IDPs \r and \r refugees \r may \r have \r lost \r the\nproductive \r assets \r needed \r to \r restart \r agriculture, \r while \r homes \r have \r been \r destroyed \r by\nthe \r conflict \r or \r have \r fallen \r into \r disrepair.\n\nAdditionally, \r distances \r are \r substantial \r between \r the \r temporary \r shelters \r in \r Thailand \r and\npotential \r return \r areas. \r Many \r of \r the \r places \r of \r origin \r of \r registered \r refugees \r in \r Thailand \r are\nparticularly \r isolated \r and \r have \r received \r little \r investment \r in \r infrastructure. \r Investment \r in\nrepatriation \r infrastructure, \r including \r transit \r centres \r or \r way \r stations, \r will \r be \r required \r in\ncase \r of \r an \r organized \r repatriation \r movement.\n\n**3.** **POPULATION \r OF \r CONCERN \r IN \r SOUTH-­‐EAST \r MYANMAR**\n\n**3.1. \r Refugees \r in \r Thailand**\n\nUNHCR’s \r current \r area \r of \r operations \r in \r South-­‐East \r Myanmar \r covers \r Kayin, \r Kayah, \r and\nMon \r States, \r and \r Taninthayri \r Regions. \r These \r are \r the \r primary \r places \r of \r origin \r of \r the\nestimated \r 128,876 \r Myanmar \r refugees \r residing \r in \r the \r temporary \r shelters \r along \r the\nborder \r in \r Thailand, \r and \r are \r assumed \r to \r be \r the \r primary \r potential \r areas \r of \r return.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Note:_ Panel A shows the location of the gold mines that were active during the study period. Around each circle,\na 20-km radius is marked. These 40-km-wide areas are the baseline treatment areas in the analysis. Panel B shows\nthe 100-km treatment areas and the distribution of the DHS clusters. Road data is an alternative way of defining\ndistance from mines, but time series data on roads is not available.\n\n**3.2 Household data**\n\nWe use microdata from the DHS, obtained from standardized surveys across years and\n\ncountries. We combine the respondents from all four DHS standard surveys in Ghana for which\n\nthere are geographic identifiers. The total data set includes 19,705 women (of which 12,392\n\nlive within 100 km of a mine) aged 15–49 from 137 districts. They were surveyed in 1993,\n\n1998, 2003, and 2008, [6] and live in 1,623 survey clusters. Since the DHS surveys focus on\n\nwomen, the surveys of women will be the main source of data. However, we also use the\n\nsurveys of men, which give us data from the same four survey years, but with a total number of\n\n---\n[6] The first mines were opened in 1990, prior to the first household survey. Ten mines were opened after the first", "output": {"entities": {"named_data": [{"text": "DHS standard surveys"}], "descriptive_data": [{"text": "microdata from the DHS"}], "vague_data": [{"text": "surveys of men"}]}}}
{"input": "emotional well-being, as well as local integration prospects. In this sense, some Afghan women\nhave reported a strict control exerted by male family members, which translates into their\nconfinement in the domestic realm.\n\n##### Protection Risk IV\n\n**Trafficking in persons, forced labor or slavery-like practices.** Although asylum seekers, refugees,\nand other forcibly displaced persons have the same labor rights as nationals in Brazil, they\nencounter several obstacles to their economic integration. The experience of displacement,\ncoupled with high levels of unemployment, informal labor, and poverty, heighten the risk of this\npopulation to fall prey of human traffickers. According to official data, between 2021 and 2023,\n355 refugees and migrants of all nationalities were rescued from forced labor or slavery-like\npractices in Brazil from various economic sectors, primarily in timber trade, cassava cultivation,\nclothing manufacturing, road transportation, and tobacco. [33 ]", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "[The new asylum legislation - specifically Article 31 of the 2020 Law and Article 73 of the 2023 Decree](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf)   provides for the issuance of refugee identity cards by the competent national authority. It outlines that the\nrefugee identity card is valid for five years, renewable and is issued for each refugee of 18 years old and\nabove. Despite this new asylum legislation, UNHCR continues to give substantial support to the Refugee\nGovernment counterpart, CNARR, including by issuing individual refugee cards to adults, family refugee\nattestations and household ration cards. There have been no changes in the documentation process for\nadult refugees and asylum-seekers. Additionally, UNHCR continue to support CNARR to issue asylumseeker certificates valid for six months and their renewal.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "(1) (2) (3) (4) (5) (6)      (7)       (8) (9)\nln ln ln ln household level ln expenditure\nwages wages wages pc total health hh\nall women men exp. exp. food    housing   education energy\n\nactive*mine 0.520** 0.694*** 0.391 -0.178* -0.126 -0.069 0.316** -0.168 0.297**\n(0.226) (0.241) (0.238) (0.093) (0.089) (0.095) (0.139) (0.199) (0.119)\n\nObservations 6,226 2,914 3,312 7,522 7,522 7,396 7,420 6,541 4,752\nR-squared 0.121 0.128 0.118 0.959 0.964 0.963 0.933 0.837 0.950\n\n_controls_\n\nindividual Y Y Y\n\nhh head Y Y Y Y Y Y\nhh size Y Y Y Y Y\ndistrict fe Y Y Y Y Y Y Y Y Y\nyear fe Y Y Y Y Y Y Y Y Y\n\ndeflated N N N Y Y N N N N\nmean (ln) 15.30 15.29 15.31 13.04 14.19 13.42 10.88 10.74 9.52\n\n_Note:_ (1) Annual wages and salaries for individuals in all ages (nondeflated).\n(2) Annual wages and salaries for women in all ages (nondeflated).\n(3) Annual wages and salaries for men in all ages (nondeflated).\n(4) Real per capita annual food and nonfood expenditure (regionally deflated).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\nreintegration \r of \r refugees \r as \r is \r the \r norm \r in \r repatriation \r operations \r across \r the \r world. \r The\nagreement \r would \r govern \r the \r procedures \r for \r entry \r into \r Myanmar \r and \r modalities \r for\nreception, \r registration, \r immediate \r humanitarian \r assistance, \r and \r travel \r to \r places \r of\ndestination. \r Another \r key \r aspect \r will \r be \r access \r and \r monitoring \r of \r returnee \r areas, \r as \r well\nas \r the \r immediately \r needed \r support \r to \r the \r reintegration \r process.\n\nUNHCR’s \r 2008 \r Policy \r on \r Return \r and \r Reintegration \r defines \r reintegration \r as \r the\nreduction \r and \r ultimately \r the \r disappearance \r of \r any \r factors \r that \r differentiate \r returnees\nfrom \r other \r members \r of \r their \r community \r in \r terms \r of \r both \r their \r legal \r and \r socio-­‐economic\nstatus. \r Therefore, \r reintegration \r is \r a \r comprehensive, \r gradual \r and \r dynamic \r effort \r that\ninvolves \r the \r establishment \r of \r conditions \r which \r enable \r returnees \r and \r their \r communities\nto \r exercise \r their \r social, \r economic, \r civil, \r political \r and \r cultural \r rights, \r and \r on \r that \r basis \r to\nenjoy \r peaceful, \r productive \r and \r dignified \r lives.\n\nThe \r definition \r of \r a \r comprehensive, \r multi-­‐year \r strategy \r for \r return \r and \r reintegration\nshould \r therefore \r be \r framed \r by \r and \r support \r development \r plans. \r Strategic \r plans \r should\ncover \r all \r key \r relevant \r sectors: \r legal, \r economic, \r social, \r and \r environmental, \r and \r guide \r the\ndivision \r of \r roles \r and \r responsibilities \r between \r relief, \r development, \r public \r and \r private\nstakeholders.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**ZUS** - Zakład Ubezpieczeń Społecznych, Polish social security administration, also known as Social Insurance Institution.\n\n44 Chart 1. Poland-Ukraine border movement balance and registered/active PESEL data\b 07 Chart 2. Ukrainians registered for social insurance\b 07 Chart 3. Number of Ukrainians registered in Poland for social insurance by sex\b 08 Chart 4. Age and gender structure of Ukrainian refugees\b 09 Chart 5. Ukrainian refugee households’ demographic composition\b 10 Chart 6. Local population shares of Ukrainian refugees\b 11 Chart 7. Income of Ukrainian refugee households by source\b 12 Chart 8. Ukrainian refugee household incomes from Poland and Ukraine in 2023 and 2024\b 12 Chart 9. Ukrainian refugee labour status 15 Chart 10. Ukrainian refugee median net wage 15 Chart 11. Main occupational groups of Ukrainian refugees, pre-war Ukrainians, other foreigners, and Polish citizens registered for social insurance, Q2 2022 and Q2 2024 (civilian, non-agricultural)\b 16 Chart 12. Ukrainian refugee wages relative to Polish citizens in the same employee-cells\b 17 Chart 13. Polish citizens and Ukrainian refugees’ employment rates by age group\b 18 Chart 14. Ukrainian refugee median net wage estimates in Q2 2024\b 19 Chart 15. Ukrainian refugees wages median net wage by age group\b 20 Chart 16. Median net wages of Ukrainian refugees median net wage by sector \b 21 Chart 17. Gross domestic product growth paths with and without Ukrainian refugees\b 23 Chart 18. Over-qualification rates by citizenship\b 27 Chart 19. Tertiary education and corresponding occupational groups shares\b 28 Chart 20. Ukrainian refugees median net wages by educational attainment\b 28 Chart 21. Share of regulated professions by citizenship and legal status, Q2 2024\b 29 Chart 22. Econometric model of determinants of Ukrainian refugees’ net wages\b 32 Chart 23. Average number of months since arrival of a Ukrainian refugee by Polish language fluency\b 33 Chart 24. What Ukrainian refugee groups have weakest Polish language fluency?\b 33 Chart 25. Ukrainian refugees’ employment rate in the 18-64 age group by previous status in Ukraine\b 34 Chart 26. Polish citizens employment rate \b 38 Chart 27. Polish citizens unemployment rate\b 38 Chart 28. Effect of a 1 pp. change in employment share of Ukrainian refugees on\b 39 Chart 29. Effect of a 1 pp. change in employment share of Ukrainian refugees on gross wage change\b 41 Chart 30. Polish citizens occupational distribution change by salary bracket, Q2 2022 and Q2 2024\b 41 Chart 31. Labour market activity rates \b 42 Chart 32. Average weekly hours in main job\b 42", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "registered/active PESEL data"}], "vague_data": []}}}
{"input": "Death Rates, Adolescent Mothers, and\n\nChildren and Adolescents out of school\n\nusing primary data from the MSNA and\n\nsecondary data sources.\n\nCalculations were refined using qualita\ntive information obtained from experts\n\nduring needs assessments validation\n\nworkshops conducted in Miranda, Zulia,\n\nFalcón, Bolívar, Delta Amacuro, Sucre,\n\nAmazonas, Apure, Táchira, Lara, and\n\nthe Capital District. The overall PIN for\n\nthe Protection Cluster is 4,425,466.00,\n\nrepresenting a 5% increase compared\n\nto the calculation for the Humanitarian\n\nResponse Plan (HRP) 2022-2023.\n\nFurther, throughout October, the national\n\nProtection Cluster participated in the\n\nfacilitation of extended OCHA Local\n\nCoordination Fora meetings in the states\n\nof Miranda, Sucre, Bolivar, Delta Ama\ncuro, Apure, Amazonas, Táchira, Zulia,\n\nFalcón, and Lara. The primary objective\n\nof these workshops was to validate data\n\ncollected from the MNSA on the human\nitarian situation of the respective state\n\nand, to gather complementary informa\n\ntion to contribute to the narrative of the\n\nHNO. Finally, it helped to validate the\n\nprioritization of municipalities in collabo\nration with Cluster partners and OCHA.\n\n**II.** **Coordination** **with** **other**\n\n**platforms, subnational Clusters,**\n\n**ICCG, and Partners**\n\n**Coordination with the Response for**\n\n**Venezuela (R4V) continued through-**\n\n**out September and October through**\n\n**bilateral meetings and common work-**", "output": {"entities": {"named_data": [{"text": "primary data from the MSNA"}, {"text": "MSNA"}], "descriptive_data": [], "vague_data": [{"text": "secondary data sources"}]}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\nAlso \r in \r 2012 \r UNHCR \r received \r authorization \r to \r open \r offices \r in \r Hpa-­‐an \r in \r Kayin \r State \r and\nLoikaw \r in \r Kayah \r State, \r although \r this \r is \r still \r to \r be \r formalised. \r Access \r remains \r restricted\nin \r certain \r areas \r and \r is \r dependent \r on \r Government \r authorization \r and \r restrictive \r advance\nclearance \r procedures, \r especially \r for \r international \r staff. \r However, \r there \r have \r been\nincremental \r improvements \r in \r access \r in \r areas \r close \r to \r the \r Thai \r border, \r particularly \r as \r the\ncease-­‐fire \r process \r has \r become \r embedded. \r Nonetheless, \r humanitarian \r access, \r and \r the\ndegree \r to \r which \r UNHCR \r is \r free \r to \r assess \r needs \r and \r to \r effectively \r target \r its \r support \r to \r the\nmost \r vulnerable \r displaced \r and \r host \r communities \r varies \r considerably \r from \r state \r to \r state.\n\n**5.** **LEGAL, \r INSTITUTIONAL \r AND \r POLICY \r FRAMEWORKS, \r AND \r KEY**\n\n**PRINCIPLES**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**time.** In the SEIS UNHCR survey, on\naverage, Ukrainian refugees who said they were fluent in Polish had stayed in Poland for 29 months, while those with an intermediate level – for only 22 months.\nThe results are interesting, especially the fact that the average time required to 32 33 progress from advanced to fluent language levels was longer than from intermediate to advanced, or beginner to intermediate (although not from zero to beginner). It is likely that the highest level of fluency, which may be required in some of the most attractive occupations, is also the hardest to achieve, and such language courses are not as readily available.", "output": {"entities": {"named_data": [{"text": "SEIS UNHCR survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\nlivelihoods, \r household \r and \r family \r security \r issues, \r as \r well \r as \r about \r past, \r present \r and\npossibly \r future \r skill-­‐sets \r that \r will \r help \r the \r refugees \r to \r return \r to \r a \r normal \r life \r outside \r the\ncamp. \r This \r information \r will \r also \r help \r in \r identifying \r both \r the \r major \r return \r areas \r and \r all\nother \r locations \r along \r with \r indications \r of \r the \r possible \r number \r of \r refugees \r intending \r to\nreturn \r to \r those \r areas, \r and \r required \r programmatic \r interventions \r to \r help \r in \r preparing \r the\nconditions \r that \r would \r support \r a \r sustainable \r voluntary \r return \r and \r reintegration.\n\n**3.2. \r Internally \r Displaced \r Persons**\n\nIn \r its \r October \r 2012 \r report, \r TBC \r estimated \r that \r a \r total \r of \r about \r 400,000 \r individuals \r are\nstill \r internally \r displaced \r in \r the \r rural \r areas \r of \r 36 \r townships \r in \r South-­‐East \r Myanmar \r in\nKayin, \r Kayah, \r South \r and \r East \r Shan \r and \r Mon \r States, \r and \r Bago \r and \r Tanintharyi \r Regions.\nOf \r these, \r the \r number \r located \r in \r Kayin, \r Kayah, \r Tanintharyi \r and \r Mon \r combined \r is\nestimated \r at \r 230,400 \r individuals \r (89,150 \r or \r 38.7% \r in \r Kayin; \r 71,650 \r or \r 31.1% \r in\nTanintharyi; \r 35,000 \r or \r 15.1% \r in \r Mon \r and \r 34,600 \r or \r 15% \r in \r Kayah) [ \r 5] .", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "increase in cash earning opportunities is estimated at 7.5 to 7.8 percentage points compared\n\nwith 5.4 in the baseline estimation.\n\n**6.6 Employment and wages using the GLSS**\n\nThe DHS data do not provide detailed information regarding how much an individual earns for\n\nwork, or her wage rate, but the GLSS does collect such data. First, we try to replicate the results\n\nestimated with the DHS data. Panel A of table 11 indicates that agriculture becomes less\n\nimportant in mining communities for women (statistically insignificant), who mainly shift into\n\nservices and sales (statistically insignificant, except for strategy 2). Men are more likely to work\n\nas miners (statistically significant across all strategies).\n\n29", "output": {"entities": {"named_data": [{"text": "the GLSS"}], "descriptive_data": [{"text": "DHS data"}], "vague_data": []}}}
{"input": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE\n\n**SHARE OF YOUNG UKRAINIANS (AGED 15 TO 24) WHO ARE NOT ENGAGED IN EMPLOYMENT, EDUCATION, OR TRAINING**\n\n**(NEET) BY COUNTRY, %** **[1,2,3]**\n\nHost country Refugees, excluding online education Refugees Bulgaria Czechia Hungary Moldova Poland Romania Slovakia Region\n\n1. Data reported by the national statistics service was used as a\nreference for Moldova 2. With the exception of Poland and the Czech Republic, the reliability of data by country is hindered by a relatively low number of observations\n\n[3. Host country data is based on indicators reported by the OECD for](https://data.oecd.org/youthinac/youth-not-in-employment-education-or-training-neet.htm)\n[2022](https://data.oecd.org/youthinac/youth-not-in-employment-education-or-training-neet.htm)\n\n**UKRAINE REFUGEE YOUTH ACTIVITY BY AGE**\n\n**The gender divide: female – led households are**\n\n**more economically vulnerable than their male –**\n\n**led counterparts**\nThe share of households that are composed of female only adults with or without children constitute 65% of the total sample across the region. Compared to households with male only adults, the vast majority of which are without children, they are 51% more likely to find themselves below the poverty line.\n\n**DISTRIBUTION OF HOUSEHOLDS BY GENDER OF**\n\n**ADULTS, %**\n\nNEET 15 16 17 18 19 20 21 22 23 24", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "indicators reported by the OECD"}]}}}
{"input": "# **BRIEF** **BRAZIL**\n\n### Operational Context & Analysis\n\nBrazil has in place a progressive and inclusive protection and solutions framework for refugees\nand other forcibly displaced individuals, ensuring equal access to rights and services alongside its\nnational citizens. With an open-border policy, Brazil guarantees the admission, registration, and\ndocumentation of those in need of international protection. Brazil hosts the largest number of\nVenezuelans recognized as refugees in Latin America and the Caribbean.\n\nAs of July 2024, Brazil has recognized 144.463 refugees and provided alternative protection\npathways to 572.877 persons in need of international protection, the majority of whom are\nVenezuelan (474.217) and Haitian (89.455) nationals. Additionally, there are 75,998 pending\nasylum applications, primarily from individuals originating from Cuba (26.225), Venezuela (15.065)\nand Angola (8.696).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "host country weighted average [17] . Excluding such online schooling increases this indicator to 18%. The highest NEET rate by country was reported in Moldova at 26%, which is similar to the local population, and the lowest in Poland at just 11% (3 percentage points below the national metric).\nRegionally, the Ukraine refugee NEET rate tends to increase with age, as it becomes more affected by unemployment, which is high for the 15 – 24 cohort (at 17%).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "19 The complete rationale for the productivity shock is outlined in the Appendix on modelling strategy, while further detailed results of econometric models are available in the Online Technical Appendix.\n\n20 As outlined in the Appendix on modelling strategy, the total number of refugees was set at 2.6% of the total population, while their share in total employment as growing from 1.5% in 2022 to 2.4% in 2024.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES Just like last year, employment rates demonstrated disparity by age group, gender, education level, the presence of a disability, and being in need of MHPSS. Disability was found to be associated with the largest drop in employment, with this factor halving the probability of working in 2024 when compared to the sample overall. Having MHPSS needs and being female were also associated with a lower employment likelihood, although to significantly smaller degrees.\n\nCompared to the host population, the refugee sample demonstrated higher employment rates at lower age brackets (15-19 and 20-24), which, considering the findings on poverty, can be interpreted as a coping strategy associated with low income. Higher age brackets (55-59 and 60-64) saw the highest gap in the employment rate compared to hosts, supporting the hypothesis that older age individuals have more difficulty integrating into the local labor market.\n\n**REGIONAL EMPLOYMENT RATE BY AGE AND POPULATION**\n\nRefugees (2023) Refugees (2024) Hosts (2023) 82% 79% 80% 52% 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 Source: Survey data, ILO\n\n**REGIONAL REFUGEE EMPLOYMENT RATE BY POPULATION**\n\n**GROUP (2024)**\n\n**EMPLOYMENT RATE BY EDUCATION LEVEL**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "survey data"}]}}}
{"input": "the bottom 40 percent in four groups: far away, before mine or during mine, and close to mine,\n\nbefore mine or during mine. The summary statistics for selected main outcomes are presented\n\nin table 10. As the table shows, the bottom 40 percent in mining communities are more likely\n\nengaging in agriculture than the bottom 40 percent elsewhere. This could illustrate that\n\nagricultural workers are overrepresented among the less well-off in mining communities.\n\nHowever, women in this group still more often work in services than women did before in the\n\nsame communities.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The choice of district – rather than cluster – fixed effect is informed by the understanding that\n\nmeaningful time-invariant factors - such as mining laws, level of development, local political\n\ninstitutions, norms regarding environment, women’s participation in the labor market, etc. - that\n\ninfluence exploitation of the mine happens at the district level. Including district fixed effects,\n\nwe control for various institutional and cultural factors at the district level that are stable over\n\ntime. Including district fixed effects also ensures that we are not only capturing effects from\n\ntransfers or the fiscal system as we compare individuals within the same districts. With this\n\nmethod we capture the geographic spillover effects in the vicinity of the mine. Moreover, cluster\n\nfixed effects are not possible because of clusters are not repeatedly sampled over time.\n\nHowever, since the estimation is at individual level, all standard errors are clustered at the DHS\n\ncluster level.\n\nThe sample is restricted to individuals living within 100 km of a deposit location ( _mine_ ), so\n\nmany parts of Northern Ghana where there are few gold mines are not included in the analysis.\n\nThe sample restriction is created by using the time-stable continuous distance measure that we", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Due \r to \r the \r size \r and \r remoteness \r of \r the \r operational \r area, \r compounded \r by \r access\nlimitation \r and \r sensitivities, \r reliable \r and \r disaggregated \r information \r on \r the \r profile \r and\nneeds \r of \r displaced \r populations \r remains \r scarce. \r UNHCR \r has \r recently \r strengthened \r its\ninformation \r management \r capacities \r with \r a \r view \r to \r working \r towards \r obtaining \r a \r more\nsystematic \r understanding \r of \r the \r locations \r and \r characteristics \r of \r populations \r of \r concern,\nand \r the \r protection \r risks \r affecting \r them. \r Additionally, \r the \r Joint \r IDP \r Profiling \r Service\n(JIPS), \r has \r recently \r completed \r a \r scoping \r mission \r aiming \r at \r assessing \r whether \r it \r is\nfeasible \r and \r desirable \r to \r conduct \r an \r IDP \r profiling \r that \r would \r inform \r the \r design \r of \r an\neffective \r strategy \r for \r support \r to \r IDPs \r durable \r solutions, \r as \r well \r as \r targeting, \r improved\nadvocacy \r and \r fundraising.\n\n**4.** **UNHCR’S \r CURRENT \r OPERATIONS \r IN \r THE \r SOUTH-­‐EAST**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Persons of concern in Southern Africa, Data as of 30 September 2022**\n\nNotes: *'Other' in the location refers to any known location other than camp or settlement sites, covering both urban and rural areas; **self-settled refers to the individuals without available information such as their names and locations, and their locations are categorised to be 'unknown'; those by location in Congo, Democratic Republic of\nthe Congo and Zimbabwe could be different from the numbers operation report due to inconsistency in proGres v4.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "contrast, show the univariate regression coefficients using OLS, highlighting the difference\n\nbetween the population living close (e.g. Column 2) and far away (e.g. Column 1) before\n\nmining.\n\nIn the pre-period, women in communities that are close to mines are less urban, poorer, have\n\nmore children and are less likely migrants. In contrast, women are of similar age, have similar\n\neducation and occupation (but slightly more likely earning cash). Note that these are raw mean\n\nvalues not controlling for any regional and individual differences. Overall, these differences are\n\nin line with previous research finding that large-scale mines tend to open in more rural and less\n\ndeveloped communities (Benshaul-Tolonen, 2018; Kotsadam and Tolonen, 2016).\n\nIn active mining communities, women are still less likely to live in urban areas (although the\n\ngap between mining and non-mining areas may be smaller) than in non-mining communities,\n\nbut more likely to have some education. The difference-in-difference estimation strategy\n\nassumes similar trends over time across the treatment (close to mines) and control group (far\n\naway from mines), in absence of the gold mining expansion. While this assumption cannot be\n\ntested using our dataset, previous analyses have found evidence for parallel pre-trends in infant", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "CROSS BORDER MOVEMENTS KEY FIGURES\n\n200 61 118 21\n\nREGIONAL BUREAU FOR SOUTHERN AFRICA\n\n**PERSONS OF CONCERN INVOLVED IN CROSS BORDER MOVEMENTS IN SOUTHERN AFRICA**\n\nAs of 30 September 2022\n\nMAP OF THE CROSS BORDER MOVEMENTS WHERE THE FLOW INVOLVED 3 POCs AND MORE *\n\n**Inward movements**\n\n**into the region**\n\n**Total cross**\n\n**border**\n\n**movements**\n\n**Intra region**\n\n**movemens**\n\n**Outward**\n\n**movements from the**\n\n**region**\n\nInward\n\n31%\n\nOutward\nmovements\n\n34%\n\nBefore 2019 2019 2020 2021 2022\n\nexclusion.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "table 7). Low weight-for-age is an indicator for acute malnutrition, whereas height-for-age is\n\nan indicator for chronic malnutrition. This could indicate that mining districts are less food\n\nsecure. [12] Table 7 shows that there are no effects on illness in the last two weeks.\n\n**6. Distributional effects, mechanisms and robustness**\n\n**6.1 Decomposing results by migration status**\n\nWe argue that one source of heterogeneity is to consider when exploring socio-economic\n\nimpacts and distributional effects of large-scale mining is migration status. First because mining\n\nmay cause inward migration of individuals that are different from the previous local population.\n\nWhile it has its limitations, disaggregating the effects between nonmigrants and migrants may\n\nshed some light on the effect on the initial population. Second, to understand the distributional\n\neffects of mining we argue that migration status may be an important factor.\n\nIn the analysis, we distinguish between nonmigrants (where the woman respondent report being\n\nborn in the locality) and migrants (born elsewhere). We note several caveats with this analysis,\n\nthe first being that we cannot follow migrant households before the migration decision.\n\nTherefore, we cannot make any causal claims on changes in this group over time. We compare\n\n---\n[12] In table 5 we saw very small insignificant changes in nutritional status.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "3 As of December 2023, according to UNHCR, based on governmental sources [Situation Ukraine Refugee Situation (unhcr.org)](https://data.unhcr.org/en/situations/ukraine) 4 According to the active PESEL UKR database.\n5 According to the active PESEL UKR database in October 2023.\n6 Deloitte calculations based on Multi-Sector Needs Assessment Poland 2023 survey data provided by UNHCR.\n\n06", "output": {"entities": {"named_data": [{"text": "active PESEL UKR database"}], "descriptive_data": [{"text": "Multi-Sector Needs Assessment Poland 2023 survey data"}], "vague_data": []}}}
{"input": "1. A household classified as above or below the poverty line if household members are individually located above or below the poverty line\n\n2. Income shares represent the average for each group 11 Defined in the survey as working for an employer full- or part-time on a regular basis, opposed to temporary work or selfemployment 12 Here defined as the share of individuals aged 15+ who are either employed or unemployed. Unemployed is understood as having searched for work over the past 30 days and willing to start if an opportunity presents itself over the next 2 weeks 13 Ratio of people younger than 15 and older than 64 to the 15-64 cohort 14 The share of individuals aged 15+ that are either employed or unemployed (have looked for work over the past 30 days and are willing to start if an opportunity presents itself over the next 2 weeks)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "However, \r two \r serious \r internal \r conflicts \r still \r remain. \r Following \r two \r waves \r of \r inter-­‐\ncommunal \r violence \r in \r the \r western \r state \r of \r Rakhine \r in \r 2012, \r over \r 150 \r persons \r were\nkilled \r and \r over \r 115,000 \r people \r were \r displaced. \r In \r the \r northern \r states \r of \r Kachin \r and\nShan, \r the \r conflict \r with \r the \r Kachin \r Independence \r Army \r continues; \r fighting \r flared \r up \r in\nJune \r 2011 \r breaking \r a \r cease-­‐fire \r that \r held \r for \r 17 \r years. \r Despite \r repeated \r attempts \r to\nnegotiate \r a \r new \r cease-­‐fire \r agreement, \r no \r peace \r solution \r has \r been \r reached \r between \r the\nparties \r and \r the \r fighting \r has \r so \r far \r resulted \r in \r the \r displacement \r of \r an \r estimated \r of \r about\n85,000 \r persons \r scattered \r in \r more \r than \r 194 \r locations.\n\nAlthough \r the \r cease-­‐fire \r agreements \r have \r not \r led \r yet \r to \r durable \r peace \r accords, \r the\nsituation \r in \r the \r South-­‐East, \r where \r the \r number \r of \r Internally \r Displaced \r People \r (IDPs) \r in\nUNHCR’s \r area \r of \r operation [1] is \r estimated \r to \r be \r about \r 230,400 \r people, \r has \r started \r seeing\nchanging \r dynamics. \r From \r the \r moment \r when \r the \r new \r civilian \r Government \r started \r to\n\n---\n[1] UNHCR’s \r area \r of \r operation \r in \r the \r South-­‐East \r currently \r consists \r of \r Kayin, \r Kayah, \r and \r Mon \r States, \r and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "During the covered period, a National Development Plan spanning 2022-2026 has been prepared, to\nsupplant the National Development Plan document (2019-2021) which has lapsed, but it has not been\nadopted. The updated plan maintains provisions for establishing consensual mechanisms for the peaceful\nresolution of conflicts. This involves reinforcing the legal framework to foster trust between communities and\nsecurity forces, facilitating socio-security dialogue, promoting peaceful coexistence and fostering respect\nfor differences.\n\n2 R E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **R E P U B L I C O F C H A D**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Deloitte D.Climate, [32 33] is a general equilibrium model that uses consumer and producer optimisation to calculate changes in the economy in response to shocks. This enables the impact of shocks to be assessed by considering supply and demand channels as well as connections between different sectors of the economy. It provides information on the total impact of shocks on various aspects of the economy, including the labour market, government revenue, as well as key economic aggregates. It is the most appropriate tool for accounting for the multi-layered impact of Ukrainian refugees. A counterfactual analysis was performed using the latest data on the Polish economy to account for the effects of other shocks in the economy. The model enabled a counterfactual analysis to be conducted by isolating the refugee influx from all other economic shocks, e.g. the other macroeconomic consequences of the war in Ukraine. The results were calculated for 2022, 2023 and 2024 with an additional long-term analysis up to 2030 to assess the economy’s long-term adaptation (assuming no new shocks, including no countershocks [34] ).\n\n32 Economics of climate change | Deloitte Australia\n\n**Chart 32. Average weekly hours in main job**\n\nWomen in 15-64 age group 68.4% 2023-Q2\n\n---\n[34] E.g. refugees keep having lower productivity rather than adapt to level of natives.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "latest data on the Polish economy"}]}}}
{"input": "During the 2022-2023 school year, a total of 105,295 refugee children were enrolled in schools. This number\nincludes 7,520 in pre-primary, 75,205 in primary, 24,999 in secondary, and 571 in higher education and\nvocational training. The gross enrolment rates for refugees were as follows: 71 per cent in primary, 28 per\ncent in secondary, and less than 1 per cent in tertiary education. Refugee enrolment rates at the primary and\ntertiary levels remain below those of national students (71 per cent and 1 per cent compared to 91 percent\nand 3 per cent respectively), while they are higher than those of national students at the secondary level (28\npercent compared to 22 per cent).\n\nChad continues to have a government-led system to support the integration of refugee children coming\nfrom a different education system (Nigerian and Sudanese refugees) but funded by UNHCR. Local education\nauthorities organize placement tests and catch-up classes before integrating refugee children into the most\nappropriate Chadian school year according to their level, age and other criteria. With new arrivals from\nSudan since April 2023, Sudanese refugee children have been integrated into the existing programme with\nongoing recruitment of new teachers in the main refugee hosting areas.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Analysis of the impact of refugees from Ukraine on the economy of Poland**\n\n**Economists have advanced an array of factors that could be causing these macro-level effects. While macro-level**\n\n**regressions show a positive impact of immigration on productivity, they cannot show the exact channels through which**\n\n**these effects come about. It is thus uncertain which are dominant. Among them are:**\n\n# Conclusions\n\n**Analysis of the impact of refugees from Ukraine on the economy of Poland**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "[8] F. N. P. Nimoh, T. P. Beltramo, J. R. Fix, F. K. Appler, U. J. Pape, and L. A. Rios Rivera, ‘Understanding the Socioeconomic Conditions of\nthe Stateless Shona Community in Kenya: Results from the 2019 Socioeconomic Survey’, Dec. 2020. Accessed: Apr. 02, 2024. [Online].\nAvailable: https://documents.worldbank.org/en/publication/documentsreports/documentdetail/356511608745182603/Understanding-the-Socioeconomic-Conditions-of-the-Stateless-Shona-Community-inKenya-Results-from-the-2019-Socioeconomic-Survey\n\n[9] U. J. Pape _et al._, ‘How COVID-19 Continues to Affect Lives of Refugees in Kenya : Rapid Response Phone Survey - Rounds 1 to 5’, World\nBank Group, Washington, D.C., Policy Note 166098, Oct. 2021. Accessed: Oct. 10, 2024. [Online]. Available:\nhttps://documents1.worldbank.org/curated/en/202201637042522937/pdf/How-COVID-19-Continues-to-Affect-Lives-of-Refugeesin-Kenya-Rapid-Response-Phone-Survey-Rounds-1-to-5.pdf\n\n[10] Kenya National Bureau of Statistics and ICF, ‘Kenya Demographic and Health Survey 2022. Key Indicators Report’, KNBS and ICF,\n\nNairobi, Kenya, and Rockville, Maryland, USA, 2023. Accessed: Oct. 10, 2024. [Online]. Available: https://www.knbs.or.ke/wpcontent/uploads/2023/08/Kenya-Demographic-and-Health-Survey-2022-Key-Indicators-Report.pdf", "output": {"entities": {"named_data": [{"text": "2019 Socioeconomic Survey"}, {"text": "Kenya Demographic and Health Survey 2022"}, {"text": "Rapid Response Phone Survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n### **Outcomes of** **Mental Health and** **Psychosocial** **Support**\n\nAmong those who accessed MHPSS, 33% answered “yes” when asked whether they experienced improvement, while 55% reported a “slight” improvement, resulting in a combined positive response rate of 88%.\n\n**% OF INDIVIDUALS WHO RECEIVED MENTAL HEALTH**\n\n**AND PSYCHOSOCIAL SUPPORT SERVICES AND REPORT**\n\n**IMPROVEMENT IN WELL-BEING BY COUNTRY**\n\nYes Slight No/No, worsening across gender, with older adults aged 60+ reporting the highest improvement rates (93% for women and 94% for men).\n\n**% OF INDIVIDUALS WHO RECEIVED MENTAL HEALTH**\n\n**AND PSYCHOSOCIAL SUPPORT SERVICES AND REPORT**\n\n**IMPROVEMENT IN WELL-BEING BY AGE AND GENDER**\n\nFemale Male Regional Bulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia (N=1,662) 33% 35% 46% 41% 26% 41% 38% 29% 30% 28% 48% 55% 54% 48% 51% 67% 44% 44% 62% 57% 56% 49%", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**higher productivity.** In a simplistic\nsupply-demand framework, the influx of Ukrainian refugees should have caused some Polish workers to become unemployed or leave the labour force, or real wages to fall. This has not happened.\nFirst, among Polish citizens employment rates have grown, and unemployment rates have fallen. Second, poviats in which employment share of Ukrainian refugees has grown by 1 pp., saw 0.5 pp. higher employment rates among Polish citizens, and 0.3 pp. lower unemployment rates.\n\nThird, there is no evidence of lowered wages, in fact the limited available data suggests that Ukrainian refugees may have caused higher wage growth in poviats which they have moved to. These are common findings well documented in academic literature, that as immigrants enter the labour market, native workers specialize in complementary, higher value tasks, which we see empirically in Polish workers moving to more attractive occupational groups. This can be seen in the data, as Polish citizens are moving to better paid occupations. It constitutes a positive shock to productivity which is what counterbalances labour market pressures. [17] Source: Deloitte D.Climate estimates. For details see the Online Technical Appendix.\n\n**The main impact of Ukrainian refugees**\n\n**is expanding the economy and putting**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE negative perceptions of Ukrainian refugees in some host communities including perceived overuse of health services and preferential treatment [6] . As the refugees stay longer, sustainable solutions to meeting health needs of refugees and host communities, including sustainable financing, refugee data integration, integration of the refugee health workforce, and enhanced service delivery including mental health services, are critical.\n\nThrough regional multi-agency collaboration, multisector needs assessments have been conducted in refugee-receiving countries since 2022 to collect information on the needs of refugees, including those related to health, nutrition and mental health and psychosocial support. These assessments support partners’ understanding of the level of access to essential services among refugees and outcomes enable governments and partners to identify priorities for the response. In 2024, a social-economic lens was added in assessing the needs of refugees in the SocioEconomic Insights Study (SEIS) conducted in ten countries (Bulgaria, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Republic of Moldova, Romania, and Slovakia).\n\n# Methodology", "output": {"entities": {"named_data": [{"text": "SocioEconomic Insights Study (SEIS)"}], "descriptive_data": [], "vague_data": []}}}
{"input": "_Source: Authors’ calculation of 2024 survey data._\n\n**Livelihood opportunities for the Shona community have improved significantly since gaining citizenship,**\n\n**particularly in terms of financial access and job prospects – as well as protection outcomes, such as reduction in**\n\n**harassment by law enforcement.** According to the survey data, over half of the Shona community reported that\n\ncitizenship has enhanced their access to banking and mobile wallet services, making it easier for them to save,\n\ninvest, and manage their finances. Increased job opportunities were cited by 47 percent of respondents, reflecting\n\nhow the ability to present formal identification has opened new avenues for employment and economic\n\nparticipation. Importantly, 46 percent of the Shona noted a reduction in harassment by law enforcement, which\n\nhad previously hindered their movement and limited their economic activities. This improvement has enabled more\n\nindividuals to seek employment and conduct business without fear of arbitrary detentions or fines.\n\n_Figure 6: Impacts on receiving citizenship on livelihood opportunities_\n\n_Source: Authors’ calculation of 2024 survey data._\n\n**[www.unhcr.org](http://www.unhcr.org/)** 8", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Additionally, 22 private companies pledged to hire 1,200 refugees and to support 15,000 refugees\nwith trainings and job placement by 2027. Currently, Brazil formally employs around 200,000\nrefugees and people in need of international protection. Of these, more than 12 thousand are\nemployed by 55 companies and organizations that are part of the Companies with Refugees\nForum, an initiative started in 2021 by UNHCR and the UN Global Compact – Brazil Chapter. The\n\nUNHCR / October, 2024 9", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n# **Background**\n\nOver three years have elapsed since the start of the full-scale invasion of Ukraine, an event which has led to the largest displacement crisis in Europe since World War II. As of the end of 2024, 6.3 million refugees from\n[Ukraine were recorded across Europe, close to 2 million of whom are located in ten Regional Refugee](https://www.unhcr.org/europe/publications/regional-refugee-response-plan-2025-2026)\n[Response Plan](https://www.unhcr.org/europe/publications/regional-refugee-response-plan-2025-2026) countries: Bulgaria, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Republic of Moldova, Romania, and Slovakia. This report aims to assess the livelihood situation of this population based on the 2024 round of data collected by the Socio-Economic Insights Survey (SEIS), which received responses from 8,723 households containing 19,803 individuals. Figures for 2023 are derived from a similar exercise [7] conducted in 2023.\n\n# **Key findings**\n\n**Refugee poverty rates remain high, albeit improved from 2023**", "output": {"entities": {"named_data": [{"text": "Socio-Economic Insights Survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "pollution from mining and agricultural productivity. The results point toward decreasing\n\nagricultural productivity because of environmental pollution and soil degradation, which could\n\nhave negative welfare effects on households that do not engage in mining activities or in\n\nindirectly stimulated sectors. Lower productivity in agriculture could potentially push\n\nhouseholds to engage in mining-related sectors, in addition to pull factors such as higher wage\n\nearnings in the stimulated sectors.\n\nWe explore the effects of mining activity on employment, earnings, expenditure, and children’s\n\nhealth outcomes in local communities and in districts with gold mining. We combine the DHS\n\nand GLSS with production data for 17 large-scale gold mines in Ghana. We find that a new\n\nlarge-scale gold mine changes economic outcomes, such as access to employment and cash\n\nearnings. In addition, it raises local wages and expenditure on housing and energy.\n\nAn important welfare indicator in developing countries is infant mortality, and we note a large\n\nand significant decrease in mortality rates among young children, at both the local and district\n\nlevels. [1] We hypothesize that increased access to prenatal care is one of the mechanisms behind\n\nthe increased survival rate.\n\n---\n[1] In the 2010 Ghana population census average district size is 112,000", "output": {"entities": {"named_data": [{"text": "GLSS"}, {"text": "2010 Ghana population census"}], "descriptive_data": [{"text": "DHS"}], "vague_data": []}}}
{"input": "activities, either by increasing or decreasing activity in the close geographic area, we will end\n\nup estimating the impact of these sectors jointly. In a later stage, should the opportunity arise,\n\nwe encourage researchers to try to disentangle the effects of small-scale and large-scale mining.\n\n**3 Data**\n\nTo conduct this analysis, we combine different data sources using spatial analysis. The main\n\nmining data is a dataset from InterraRMG covering all large-scale mines in Ghana, explained\n\nin more detail in section 3.1. This dataset is linked to survey data from the DHS and GLSS,\n\nusing spatial information. Geographical coordinates of enumeration areas in GLSS are from\n\nGhana Statistical Services (GSS). [2] Point coordinates (global positioning system [GPS]) for the\n\nsurveyed DHS clusters [3] allow us to match all individuals to one or several mineral mines. We\n\ndo this in two ways.\n\nFirst, we calculate distance spans from an exact mine location given by its GPS coordinates,\n\nand match surveyed individuals to mines. These are concentric circles with radiuses of 10, 20,\n\nand 30 kilometers (km), and so on, up to 100 km and beyond. In the baseline analysis where\n\n---\n[2] The data was shared by Aragón and Rud (2013)\n[3] Both the DHS and GLSS enumeration area coordinates have a 1-5 km offset. The DHS clusters have up to", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "survey data from the DHS and GLSS"}, {"text": "dataset from InterraRMG"}], "vague_data": []}}}
{"input": "The new asylum legislation provides a robust legal framework for guaranteeing access to justice for\nrefugees and asylum-seekers. This includes outlining specific provisions regarding legal assistance and\njudicial assistance to permit access to justice, legal representation and enforcement of ruling. It is important\n[to consider this framework in conjunction with Law 021-PR-2019 on legal aid and judicial assistance, which](https://www.refworld.org/docid/609f00834.html)\nwas enacted in 2019, though not fully operational in absence of an implementing decree. Article 27 of the\n[2020 Asylum Law](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf) recognizes the refugee right to access Chadian Courts. The same provision also provides\nfor treatment regarding access to judicial assistance on par with nationals and exempts refugees from\nproviding a financial deposit to Courts (caution judicatum solvi) applicable to ordinary foreigners.\n\n[Article 65 of the 2023 Decree](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf) further outlines that refugees and asylum-seekers enjoy access to Court on par\nwith nationals. Additionally, the 2023 Decree outlines the rights of asylum-seekers and refugees to access judicial\nassistance and legal assistance in the conditions outlined by the law. A specific legal provision of the 2023\nDecree also details the different modalities composing legal aid accessible to refugees and asylum-seekers", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\n5. Returning \r refugees \r and \r IDPs \r and \r receiving/hosting \r communities \r have\n\nopportunities \r to \r (re-­‐)establish \r meaningful \r and \r productive \r lives, \r through \r access\nto \r livelihoods \r opportunities.\n6. IDPs \r and \r returned \r refugee, \r together \r with \r the \r communities \r receiving \r or \r hosting\n\nthem \r enjoy \r key \r socio-­‐economic \r rights, \r including \r access \r to \r shelter, \r education \r and\nhealth \r and \r other \r services \r and \r infrastructure.\n\n**9.** **KEY \r ASSUMPTIONS \r AND \r RISKS**\n\nWith \r the \r understanding \r that \r a \r more \r in-­‐depth \r analysis \r is \r needed, \r the \r following \r is \r a \r list \r of\nkey \r assumptions \r and \r risks \r that \r need \r to \r be \r taken \r into \r consideration \r prior \r to \r planning\ndurable \r solutions \r programming \r in \r the \r South-­‐East:\n\n- The \r peace \r process \r remains \r one \r of \r the \r Government’s \r main \r priorities \r including\nadequately \r addressing \r the \r current \r situations \r in \r Kachin \r and \r Rakhine. \r Much \r will\nalso \r depend \r on \r the \r agreements \r that \r are \r reached \r with \r the \r different \r armed \r groups\nand \r the \r level \r of \r political, \r economic \r and \r cultural \r autonomy \r they \r could \r retain. \r Any\non-­‐going \r armed \r clashes \r and/or \r protection \r incidents \r could \r derail \r progress \r made\nso \r far.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The \r proposed \r five \r phases \r reflect \r different \r stages \r in \r IDP \r operations, \r and \r in \r the \r refugee\nrepatriation \r and \r reintegration \r process, \r with \r each \r corresponding \r to \r incrementally\nincreasing \r resource \r requirements \r for \r UNHCR \r and \r its \r operational \r partners.\n\n- Phase \r 1: Strengthening \r of \r IDP \r operations \r and \r preparation \r for \r refugee \r return\nwhile \r providing \r integrated \r assistance \r to \r spontaneous \r returnees;\n\n- Phase \r 2: Expansion \r of \r integrated \r support \r to \r spontaneous \r returnees \r and \r their\ncommunities \r while \r enhancing \r preparedness;\n\n- Phase \r 3: Refugee \r repatriation \r and \r initial \r reintegration \r operations;\n\n- Phase \r 4: Consolidation \r of \r reintegration \r operations; \r and\n\n- Phase \r 5: Reintegration \r operations \r are \r scaled \r down \r and \r phased \r out.\n\n**8.** **OBJECTIVES**\n\nGeneral \r operational \r objectives \r are:\n\n1. Refugees \r are \r empowered \r to \r make \r an \r informed \r choice \r on \r whether \r to \r return, \r and\n\nif \r so, \r when \r and \r to \r where, \r including \r through \r the \r provision \r of \r accurate \r and \r up \r to\ndate \r information \r on \r the \r situation \r in \r areas \r of \r potential \r return.\n2. Refugees \r and \r IDPs \r have \r the \r opportunity \r to \r determine \r which \r solution(s) \r are\n\nmost \r appropriate \r for \r them, \r and \r to \r participate \r fully \r in \r the \r assessment, \r design \r and\ndelivery \r of \r durable \r solutions \r programmes, \r using \r an \r age, \r gender \r and \r diversity\nmainstreaming \r approach.\n3. Legal \r frameworks \r are \r in \r place \r that \r guarantee \r the \r rights \r of \r IDPs \r and \r returning", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "UNHCR Indonesia is working to expand access to complementary pathways for refugees in the country\nand provides information and guidance to refugees who may be eligible for these programs. Solutions\nthrough complementary pathways have increased in recent years, from no individual departures on\npathways in 2020 to over 300 departures in 2023. UNHCR recognizes and amplifies the link between\naccess to education, skills building, and empowerment activities in Indonesia with improved access to\neducation and labour mobility pathways in third countries. In this way, continued success with these\npathways also serves to reinforce and enhance advocacy with Indonesian authorities on the\nimportance of access to opportunities while in Indonesia. Since mid-2021, UNHCR has collaborated\nwith Talent Beyond Boundaries (TBB) on a project that matches refugee candidates in Indonesia with\nemployers in Australia and Canada to offer employment and a pathway to residency through labour\nmobility. In 2023, 328 individuals departed on a sponsorship pathway, eight refugees departed to a\nthird country on family reunification, and seven refugees departed to Canada and Australia on labour\nmobility programs.\n\n### **Solutions - Voluntary Repatriation**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Considering \r that \r decades \r of \r conflict, \r displacement \r and \r poverty \r have \r weakened\ntraditional \r community \r support \r and \r leadership \r structures \r will \r be \r important \r that \r the\ncapacities \r of \r communities, \r as \r well \r as \r local \r partners \r such \r as \r local \r NGOs, \r CBOs \r and\nborder-­‐based \r groups \r working \r out \r of \r Thailand, \r are \r effectively \r harnessed \r in \r support \r of\ndurable \r solutions. \r  \r In \r particular \r border-­‐based \r organisations \r represent \r critical \r assets\nthat \r are \r complementary \r to \r the \r traditional \r agencies. \r The \r networks \r and \r working\nrelationships \r that \r Thai-­‐based \r organisations, \r which \r have \r been \r working \r with \r the \r refugee\nand \r IDP \r communities \r for \r about \r 30 \r years, \r have \r developed \r with \r displaced \r communities\nwill \r be \r invaluable \r in \r building \r trust \r and \r providing \r services.\n\nThe \r scope \r of \r activities \r required \r is \r likely \r to \r be \r significant \r and \r will \r require \r prioritized\nattention \r and \r significant \r donor \r support. \r Early \r support \r to \r kick-­‐start \r the \r reintegration\nprocess \r that \r will \r address \r immediate \r needs \r (initial \r phases) \r should \r transition \r to \r medium\nand \r longer \r term \r development \r projects \r (consolidation \r phase) \r to \r ensure \r the \r achievement\nof \r sustainable \r reintegration \r and \r eventually \r lead \r to \r a \r measurable \r UNHCR \r disengagement.\n\n12", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "# **HIGH EMPLOYMENT** **RATES, BUT LOW** **WAGES: A POVERTY** **ASSESSMENT OF** **UKRAINIAN REFUGEES** **IN NEIGHBORING** **COUNTRIES**\n\n## **An inter-agency exploration of** **socio-economic data** March 2025", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "socio-economic data"}]}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n## Appendix: Modelling strategy\n\n##### Compared to refugees in other countries, Ukrainians in Poland show high employment rates, making their economic impact more positive and comparable to immigrants in general. Most of the migration economics literature quoted in this appendix refers to all immigrants, not just refugees.\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n#### **“Canonical model” and recent advances**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE\n\n### **Summary of** **findings and** **recommendations**\n\nOverall, refugee households from Ukraine are facing a high degree of economic vulnerability, with half of them falling below the poverty line [1] based on reported income. Factoring in accommodation support (provided either via host governments, local homeowners, or other arrangements) as an indirect source of income, reduces the poverty rate to 32%, demonstrating the importance of such interventions.\nThe level of access to regular [2] employment is a key factor influencing the financial wellbeing of households, highlighting the significance of economic inclusion. Despite a predominantly vulnerable population profile (35% of families consist of a single adult woman with dependents, and the overall age dependency ratio [3] stands at 61%), labor force participation rates among refugees are comparable to those of host country nationals.\nHowever, unemployment rates remain alarmingly high at 14%. Additionally, gender gaps are\n\n---\n[1] Defined as being composed of members whose equivalized income is below 50% of the national median\n[2] Defined in the survey as working for an employer full- or part-time on a regular basis, as opposed to temporary work or selfemployment\n[3] Defined as the ratio of people younger than 15 and older than 64 to the 15-64 cohort", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Third, cross-section regression analysis shows that poviats with a higher number of Ukrainian refugees saw a greater increase in wages, which was caused by larger share of refugees in local employment.\nDue to limitations in the wage dataset, our calculations incorporated yearly data.\nCross-section models were estimated using a data sample for all 380 poviats in 2023.\nThe share of Ukrainian refugees among all employed, temporarily employed, and self-employed persons insured at ZUS in a given poviat was averaged across quarters to construct a yearly variable. The wage variable is the GUS data series on gross monthly wages and salaries [30], and taken as nominal change in 2023 from 2022.\nThe ordinary least squares cross-section model shows that in 2023, a 1 percentage point increase in the employment share of Ukrainian refugees was associated with an increase in wages of PLN 66. Given that in a mean poviat gross wage growth amounted to PLN 757 and the gross wage in the previous year was PLN 5,803, wages have grown by 13.1% in nominal terms (including inflation), of which 0.7 percentage points were associated with Ukrainian refugees (considering the fact that the employment share of the Ukrainian refugees in a mean poviat was 0.61%).\n\n---\n[30] Unfortunately, GUS data for these time periods and poviat level include the enterprise sector (firms that employ 10 or more persons) and public sector, which is", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "wage dataset"}]}}}
{"input": "**2. Support economic integration and empowerment of the Shona community through targeted financial inclusion**\n\n**programs and skills development initiatives.**\n\nThe Government of Kenya, in collaboration with development partners, is encouraged to implement tailored\n\nfinancial inclusion strategies to help the newly recognized Shona citizens access credit, savings, and insurance\n\nproducts that are crucial for business growth and household resilience. Establishing entrepreneurship training\n\nprograms, mentorship networks, and providing access to capital for small and medium-sized enterprises would\n\nempower the Shona community to leverage their skills in wood carving, basket weaving, and other economic\n\nactivities. Additionally, promoting employment opportunities in the formal sector for Shona individuals through job\n\nplacement services and partnerships with the private sector will ensure that the community’s transition to full\n\ncitizenship is accompanied by tangible improvements in income and welfare.\n\n**3. Reaffirm and expand Kenya’s commitment to eradicating statelessness by adopting a comprehensive national**\n\n**strategy.**\n\nBuilding on the success of granting citizenship to the Makonde, Shona, and Pemba communities, a National Action\n\nPlan to identify and resolve remaining cases of statelessness, including the estimated 9,800 individuals who remain\n\nstateless, offers many benefits. This strategy should include amending the relevant Sections of the Kenya", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "- The \r Government \r will \r abide \r by \r international \r standards \r for \r return \r namely, \r that\npeople \r have \r a \r right \r to \r return \r voluntarily \r to \r places \r of \r choice, \r based \r on \r their\nindividual \r and \r freely-­‐expressed \r wish \r to \r return, \r and \r that \r return \r and\nreintegration \r is \r carried \r out \r in \r conditions \r of \r physical, \r legal \r and \r material \r safety\nand \r dignity.\n\n- The \r Government \r and \r non-­‐state \r armed \r groups \r engage \r in \r addressing \r the \r problem\nof \r landmines \r as \r an \r early \r priority. \r Landmines \r are \r a \r particular \r threat \r in \r the \r South-­‐\nEast \r and \r a \r serious \r impediment \r to \r any \r possible \r return.\n\n- Land \r reform, \r including \r restoration \r of \r land \r rights \r and \r compensation, \r remains \r at\nthe \r centre \r of \r the \r country’s \r political \r debate \r and \r reform \r agenda. \r The \r current \r laws\nallow \r expropriation \r of \r land \r not \r utilised \r for \r a \r specific \r period \r of \r time. \r In \r addition,\nabandonment, \r widespread \r destruction \r and \r “land \r grabbing” \r may \r mean \r that \r some\nvillages \r of \r origin \r may \r not \r exist \r anymore, \r or \r may \r not \r be \r accessible.\n\n- Humanitarian \r and \r development \r actors \r are \r granted \r full \r access \r to \r return \r areas,\nparticularly \r allowing \r the \r opening \r of \r offices \r and \r regular \r monitoring \r capacity.\nDirect \r access \r to \r key \r areas \r of \r origin \r is \r still \r limited \r for \r many \r humanitarian \r and\ndevelopment \r actors \r in \r particular \r in \r conflict-­‐affected \r areas.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "5. Cross Sectors\n\n### **5. Cross Sectors**\n\n**5.1** **Gender**\n\nGender considerations can generally be enhanced in many sub-dimensions of overall policies, with the\nmost relevant being the national institutional framework for the management and coordination of refugees.\nAdditionally, the limited participation of refugee women in advisory committees often results in inadequate\nconsideration of the concerns and needs of women and girls. This hinders their inclusion in national plans\nand programs.\n\nThe most consequential policy sub-dimensions in terms of socioeconomic development remain therefore\nas follows:\n\n**a.** **Justice and Security:** Challenges remain in preventing and responding to gender-based violence.\n\n**b.** **Land, Housing, and Property:** Refugees in general still face difficulties in accessing and owning land.\n\n**c.** **Education:** Limited access to education for refugee girls, particularly due to high dropout rates. In\n\nthe 2022-2023 school year, girls’ enrolment rates were 47 per cent in primary, 17 per cent in middle\nschool and only 6 percent in high school nationwide. The drop in middle and high school attendance is\nlinked to socio-cultural pressures, leading to issues like child marriages, early marriages, child labour.\n\n**d.** **Healthcare:** Insufficient prioritization of the specific needs of women and girls, including refugee women", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The floods in 2022 had adverse effects in 18 out of the 23 provinces, including Lac, Mayo Kebbi Est, Mayo\nKebi Ouest, Logone Occidental, Logone Oriental, Tandjilé and Mandoul. These consequences resulted in\nthe loss of agricultural land and livestock, and heightened risks to food security. In October 2022, authorities\nresponded by declaring a state of emergency and offering financial assistance to affected individuals,\nincluding refugees hosted in these rural areas, to meet their shelter and essential needs. Specific sites were\nidentified to temporally accommodate the displaced individuals irrespective of their status.\n\n**1.4** **Preparedness for refugee inflows**\n\nThe National Commission for the Reception, Reintegration of Refugees and Repatriates (Commission\nNationale d’Accueil de Réinsertion des Réfugiés et des Rapatriés, CNARR) remains the national institutional\nbody to respond to new refugee inflows. The four-year strategy of CNARR (2019-2023), which includes\nmobilization provisions in case of emergencies, continues to be applied. The CNARR continues to work\nwith UNHCR and other United Nations organizations to support and guide its response to refugee inflows,\nparticularly in cases of emergency.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Note:_ In panel A, active is status of mine in birth year; in panel B, active is active status of mine in survey year.\nRobust standard errors clustered at the DHS cluster level in parentheses. All regressions control for year and district\nfixed effects, urban dummy, age, and years of education. *** p<0.01, **p<0.05, *p<0.1. OLS = ordinary least\nsquares.\n\nAn active mine is associated with a decrease in cough among children under age five (panel B\n\nof table 5), and children are also (insignificantly) more likely to have a health card. An active\n\nmine is associated with insignificant decreases in the anthropometrics measures (World Health\n\nOrganization measures in standard deviations), such as height-for-age and weight-for-age.\n\nHowever, the standard errors for these coefficients are very large relative to the estimated\n\ncoefficients, which is why the effects are imprecisely estimated.\n\n**5.3 Spatial heterogeneity of results**\n\nThus far we have used a cutoff distance of 20 km. Panel A of figure 4 shows that the largest\n\ntreatment effect for services for women is found within 10 km of a mine, with an 8 percentage\n\npoint increase in the probability that a woman works in the service sector. This is equivalent to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**productive native women to increase their labour supply.**\nA caveat in the case of refugees from Ukraine is that this could mean working below their qualifications or in the informal sector, making the overall effect for productivity unclear.\nNevertheless, as availability of care and housework services increases, it becomes easier for women mainly to combine family and professional lives and increase labour supply.\nSuch effects may be stronger for countries with less accessible childcare. Furtado (2015) reviews this literature, finding evidence from Australia, Hong Kong, Italy, Singapore, Spain, Switzerland, Spain, United Kingdom, and the United States.\nAdditionally, Furtado (2016) in the USA in the 1980-2000 period finds that married women and women with graduate degrees increase their fertility in response to low-skilled immigration.\nResults are causal, as the author exploits the role of ethnic network in immigrant location decisions.\n\n40 41\n\n**Firms respond to immigrant inflows by introducing**\n\n**production technologies complementary to their skills, thus**\n\n**making their skill-group and potentially firms themselves**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland Analysis of the impact of refugees from Ukraine on the economy of Poland Vocational or lower Secondary Higher Data is limited, but it appears refugees found work in sectors where the labour market was particularly tight. Publicly available data does not give the numbers of social security registrations of native workers by NACE sector. For this reason, in the absence of administrative data, to approximate the share of Ukrainian workers in particular sectors it was necessary to use Statistics Poland survey data. The share of workers with Ukrainian citizenship grew more in sectors that were experiencing the highest wage and salaries growth before refugee displacement. This eased their entry into the labour market.\nThe refugees were also quick to set-up their own businesses or become self-employed.\nAccommodation and food, as a sector, has been experiencing a particularly large growth in wages and salaries in 2021, as it re-opened after the Covid-19 pandemic, and subsequently it recorded a particularly large growth in the share of Ukrainian workers. Transportation has been the only sector in which the share and number of Ukrainian workers declined.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "Statistics Poland survey"}], "vague_data": []}}}
{"input": "Second, panel regression analysis shows that a larger influx of Ukrainian refugees at the poviat level was accompanied by a larger increase in employment rates for Polish citizens along with a larger decrease in registered unemployment rates. The data sample for all regressions encompassed quarterly data for all 380 poviats from Q1 2022 to Q2 2024.\nThe Ukrainian refugee share variable was constructed as the share of Ukrainian refugees among all employed, temporarily employed, and self-employed persons insured with ZUS in a given poviat at the end of the quarter. The employment rate of Polish citizens was constructed as the share of Polish citizens who are employed, Analysis of the impact of refugees from Ukraine on the economy of Poland", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "quarterly data for all 380 poviats"}]}}}
{"input": "temporarily employed, and self-employed and who are insured with ZUS, divided by the population from GUS in a given poviat in a given quarter (estimated based on halfyear population data). The unemployment rate is the registered unemployment rate series from GUS. Fixed effects panel regressions show that an increase in the employment share of Ukrainian refugees by 1 percentage point correlates with an increase in Polish citizens' employment rates by 0.5% and a decrease in the unemployment rate by 0.3%, in the preferred specification with dummy variables for all quarters. All results are statistically significant at a 0.01 level.\n\n**Chart 26. Polish citizens employment rate** **Chart 27. Polish citizens unemployment rate**\n\nEurostat survey data, 20-64 age group Eurostat survey data, 20-64 age group 3.6% 83.8% 83.6% 83.2%\n\n**Chart 28. Effect of a 1 pp. change in employment share of Ukrainian refugees on**\n\nPanel model of all 380 poviats quarterly data from Q1 2022 to Q2 2024. Results are statistically significant at a 0.01 level.\n\nPolish citizens employment rate Unemployment rate\n\n1.0 1.0\n\n0 0\n\n-1.0 -1.0\n\n-2.0 -2.0\n\nNo time Seasonal Quarterly No time Seasonal Quarterly dummies dummies dummies dummies dummies dummies", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "registered unemployment rate series from GUS"}, {"text": "Eurostat survey data"}, {"text": "halfyear population data"}], "vague_data": [{"text": "halfyear population data"}]}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland © UNHCR / Anna Liminowicz\n\n# **3.** Economic impact modelling\n\nSimple back-of-the-envelope calculations give the intuition behind how additional workers help to grow the economy.\nThe simplest estimate would be to assume that an increase of employment by 1.4-2.2% will grow the Gross Domestic Product by an equal percentage. In such a case, we would need to assume that labour is the only production factor, and thus all of GDP can be equally divided between workers.\nHowever, this is not the case, as GDP is not just a function of labour, but also of capital that workers have at their disposal – all the machines, computer programs, offices, and the like. As displacement is unexpected and refugee status (both legal and intent to stay long term) at first is uncertain, companies take time to increase their stocks of capital to the new workers. A more elaborate estimate would account for the part of GDP Analysis of the impact of refugees from Ukraine on the economy of Poland", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Economic impact modelling**\nEconomic impact of Ukrainian refugees has been estimated in the general equilibrium Deloitte D.Climate model that accounts for their labour, consumption, and tax inputs.\nSuch models are a gold standard in policy modelling used by central banks, academia, and other institutions, because they can simulate counterfactual scenarios.\nThus, we can distinguish the positive labour market shock from the inflow of refugees and analyse various scenarios independently of all other recent macroeconomic developments (Chapter 3).\n\nWe find that refugees from Ukraine as workers, entrepreneurs, consumers, and taxpayers had a positive impact on economic output, which will increase in the long run. The Deloitte D.Climate general equilibrium model finds that refugees from Ukraine in the long-term will contribute 0.9-1.35% to the Gross Domestic Product.\nIn our model, the long-term is defined as the period over which the economy fully adjusts to the shock of the initial refugee inflow; it does not include other aspects, e.g. refugee children growing-up and entering labour market. These results are 08 09", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**downgrading.** With the median wages\nof Ukrainian refugees estimated at 84% (SEIS survey) or 80% (NBP 2024 survey) of the national median (see chapter 2), the difference for average wages may be even larger. This is because medians are insensitive to high earners who typically inflate average earnings. Such high earners may suffer significant downgrading considering the unfavourable occupational structure of Ukrainian refugees. There are many reasons to this, from occupational licensing to a high level of language fluency required by high-skill jobs. [28] Ukrainian Pre-war Other Polish refugees Ukrainians foreigners citizens Drivers (truck, bus) Teachers Medical professions (physician, dentist, nurse, midwife) Legal professions (legal counsel, barrister, notary, bailiff) Taxi drivers Others Source: Deloitte own elaboration based on ZUS data on June 30th 2024.\n\n26 As described in chapter 2, SEIS measures incomes on the household level. Using it to estimate individual wages likely underrepresents lowest and highest incomes.\nDetails are available in the Online Technical Appendix.\n\n27 Note that the GUS (2024) data for the host population is not exactly comparable, as it does not include microenterprises, it covers an earlier period and focuses on gross and average wages.\n\n28\n\n---\n[28] Lessem and Sanders (2020) modelled immigrant wage growth in the United States, finding that in a counterfactual model eliminating barriers to occupational entry", "output": {"entities": {"named_data": [{"text": "SEIS survey"}, {"text": "GUS (2024) data"}], "descriptive_data": [{"text": "NBP 2024 survey"}, {"text": "ZUS data"}], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Recently arrived Ukrainian refugees,**\n\n**those with below tertiary education**\n\n**and in older age group are most**\n\n**likely to communicate in Polish at**\n\n**intermediate and lower levels.** Based\non the SEIS UNHCR survey, a logistic regression has been performed to find out which categories of Ukrainian refugees may most require Polish language improvement. [29] Results show that the odds of only zero to intermediate Polish knowledge decrease with every month since arrival. Ukrainian refugees in the 18 to 29 age group have the lowest odds of having an intermediate or lower level of Polish. It translates into a 38% probability, even lower than the 41% for refugees with tertiary education. The group with the highest odds (70% probability) of zero to intermediate Polish are Ukrainian refugees aged 50 to 64. The results by employment sectors are not statistically significant, other than for manufacturing. The results are intuitive, with the best language skills among refugees working in health and education, and the lowest among those working in construction, other services, and trade.\n\n**Addressing the gap in language**\n\n**fluency would yield significant**\n\n---\n[29] A dummy variable that takes the value of 1 in case of none, beginner, or intermediate language knowledge, and 0 for other levels has been regressed against a", "output": {"entities": {"named_data": [{"text": "SEIS UNHCR survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "With the exception of Republic of Moldova, the poverty line for each country was defined as 50% of the median\n[equivalized disposable income (after social transfers) as reported by](https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Glossary:Equivalised_disposable_income) [Eurostat for 2023. This figure was indexed](https://ec.europa.eu/eurostat) towards 2024 using national annual wage inflation data for the third quarter of 2024. As the Republic of Moldova does not currently run the SILC survey, the absolute poverty line as reported by the country’s National Bureau of Statistics was used instead. Host poverty rates were based on the same poverty threshold. With the except of Republic of Moldova, these were equal to the at-risk-of-poverty (AROP) rate reported by Eurostat. On\n\n**14**", "output": {"entities": {"named_data": [{"text": "SILC survey"}], "descriptive_data": [{"text": "national annual wage inflation data"}], "vague_data": []}}}
{"input": "**taxpayers** . Currently between 225 and\n350 thousand refugees from Ukraine are estimated to be working in Poland. The lower bound is the number from social security data, while the higher bound is the product of employment rate from the surveys and working age population with active PESEL UKR numbers (Chapter 2).\n\nStructural worker shortages, one of the lowest unemployment rates in the European Union, record high vacancies, and high education attainment of refugees eased their labour market integration. The number of Polish citizens aged 20-64 has declined by 2.6 million from its peak in early 2010. [7] Despite COVID-19 and geopolitical shocks, the unemployment rate oscillated in recent years around 3% in Poland, and in February 2022 only Czechia exhibited a lower rate in the EU. [8] In Q4‘2021 the share of companies reporting vacancies stood at 49%, the highest level on record, and has been slowly declining since then. [9] In July-August 2023, 56% of refugees declared possessing tertiary education and their employment rate has been almost one-third higher than for others. [10]\n\n---\n[7] According to the Labour Force Survey data from Eurostat.\n[8] According to the harmonized unemployment rates from Eurostat.\n[9] According to the quarterly NBP survey.\n[10] According to the UNHCR (2023) survey.", "output": {"entities": {"named_data": [{"text": "UNHCR (2023) survey"}], "descriptive_data": [{"text": "quarterly NBP survey"}, {"text": "Labour Force Survey data"}, {"text": "harmonized unemployment rates from Eurostat"}], "vague_data": [{"text": "social security data"}]}}}
{"input": "The Ukrainian refugee population also faces financial barriers to access critical services: one in ten households have no health insurance and 22 % of those surveyed answered that they cannot afford fees at local health care clinics. Households that contain a member with a disability are also more likely to be below the poverty line. This group’s poverty rate stands at 59% versus 43% for households with no members with disabilities.\n\n**Support with accommodation expenses – an**\n\n**important vulnerability shield**\nOverall, almost half (48%) of refugee households in the region report receiving accommodation or housing assistance. Twenty percent are living in With accommodation rent support Bulgaria Hungary Poland Romania Slovakia Region\n\n1. Calculations for Moldova were not conducted, as this country is not\nincluded into the [EU statistics on income and living conditions (SILC)](https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions)\n[survey, which the OECD uses as the basis for host country poverty](https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions) assessments 2. Results for the Czech Republic not individually presented due to sampling limitations 3. Accommodation rent support has been calculated as the difference between the actual equivalized accommodation expense and the median equivalized market rent in the region", "output": {"entities": {"named_data": [{"text": "EU statistics on income and living conditions"}], "descriptive_data": [], "vague_data": []}}}
{"input": "With partners, UNHCR continues to advocate with the Indonesian government at all levels and works\nto strengthen collaboration with coastal communities to ensure boats in distress at sea are rescued\nand able to disembark in Indonesia with adequate sites designated to host those who arrive by sea.\nIn addition to arrivals by sea, UNHCR continues to advocate with competent authorities when\ncontacted by individuals arriving by air if their right to seek asylum was denied at the airport.\n\n### **Resettlement Expectations**\n\nRefugees and authorities consider Indonesia to be a “transit country” prior to the realization of a\nsolution in a third country. The refugee assistance models established by the Comprehensive Plan of\nAction for Indochinese Refugees and the Regional Cooperation Agreement, as well as\ndisproportionately high resettlement opportunities from Indonesia when compared to opportunities\nfrom many other host countries, have perpetuated this narrative. The pervasive and persistent\nmisconception regarding the extent to which refugees are entitled to resettlement and the belief that,\nwith time, resettlement will be accessible for all refugees in the country has a negative impact on the\nrefugee population and the protection space in Indonesia.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Voluntary \r return \r is \r guided \r by \r internationally \r recognized \r standards, \r which \r inter \r alia\nprovide \r that \r refugees \r have \r the \r right \r to \r return \r voluntarily, \r in \r safety \r and \r dignity, \r to \r their\nown \r countries. \r A \r freely \r expressed \r wish \r to \r return \r by \r those \r displaced \r is \r a \r pre-­‐condition \r to\nany \r voluntary \r return. \r Recognized \r principles \r also \r include: \r taking \r measures \r to \r address\nany \r root \r causes \r of \r displacement \r (cross-­‐border \r and \r internal) \r by \r all \r parties \r to \r the \r past\nconflict; \r that \r refugees \r and \r IDPs \r have \r the \r right \r to \r freedom \r of \r movement \r and \r the \r right \r to\nreturn \r to \r their \r place \r of \r former \r residence \r or \r another \r place \r of \r their \r choice \r in \r the \r country\nof \r origin; \r and \r that \r UNHCR \r and \r partners \r have \r access \r to \r returnee \r areas \r in \r order \r to\nmonitor \r their \r return.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\nA \r set \r of \r standards \r and \r qualitative \r and \r quantitative \r indicators \r should \r be \r developed \r to\nmeasure \r progress \r toward \r the \r achievement \r of \r the \r reintegration \r objectives.\n\nThis \r section \r proposes \r various \r activities \r that \r should \r be \r considered \r to \r address \r immediate\nas \r well \r as \r longer-­‐term \r needs. \r UNHCR \r could \r take \r the \r lead \r on \r these \r activities \r or \r provide \r a\nco-­‐ordination \r or \r advocacy \r role, \r depending \r on \r the \r specific \r activity.\n\n**10.1.** **Phase \r 1 \r (current \r phase): \r Strengthening \r of \r IDP \r operations \r and**\n\n**preparation \r for \r refugee \r return \r while \r providing \r integrated**\n\n**assistance \r to \r spontaneous \r returnees**\n\n- Build \r on \r previously \r established \r co-­‐ordination \r mechanisms \r -­‐ \r such \r as \r monthly\ninter-­‐agency \r meetings \r at \r state \r level, \r the \r South-­‐East \r Consultation \r and \r cross-­‐\nborder \r meetings \r -­‐ \r to \r strengthen \r co-­‐ordination \r on \r durable \r solutions. \r Co-­‐\nordination \r systems \r shall \r facilitate \r respect \r for \r key \r protection \r and \r assistance\nstandards \r and \r enable \r the \r development \r of \r a \r strategic \r vision \r for \r durable \r solutions.\n\n- Strengthen \r information \r management \r and \r analysis \r capacities, \r including \r the\ndevelopment \r of \r tools \r to \r capture \r and \r analyse \r patterns \r of \r spontaneous \r returns\nand \r carry \r out \r protection \r assessments \r and \r monitoring. \r  \r  \r  \r Information \r products\nwill \r also \r aim \r at \r supporting \r informed \r decision-­‐making \r by \r refugees \r in \r Thailand.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Power BI Desktop Access to Basic Services Guaranteeing that IDPs have sustained access to essential services such as healthcare, education, water, and sanitation is vital to preventing dependence on humanitarianassistance.\nSimultaneously, ensuring the internally displaced are included in developing national systems, including protection programmes and services and development strategies, is vital for improving the living conditions and well-being of communities.\nPathway #2:", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The structure of the Ukrainian population in Poland changed radically after 24th February 2022. Up until 2021, Ukrainians in Poland were mostly men (close to two-thirds) looking for work, often leaving their families back in Ukraine. After the beginning of the full-scale war in Ukraine, refugees fleeing the war started to arrive.\nThey were primarily women and children.\nThis is consistent with a change in the nature of migration flows, from primarily economic migrants to forcefully displaced refugees.\n\n**Chart 2.** Number of Ukrainian men and women registered in Poland for social security.\n\n800 700 600 500 400 300 200 100 0 2021 Q42 022 Q4 2023 Q3 Number of insured men with Ukrainian citizenship Number of insured women with Ukrainian citizenship", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "4. Access to National Public Services\n\nIn practical terms, a formal State led system for recognizing foreign diplomas of refugees and foreigners does\nexist through an authentication mechanism led by the National Office for Higher Education Examinations\nand Competitions (Office National des Examens et Concours du Supérieur - ONECS). Regarding driving\nlicenses, only Chadian driving licenses can be obtained through ANATS after fulfilling ANATS requirements.\n\n### **4. Access to National Public Services**\n\nThe new asylum legislation guarantees the right to health, education, public assistance and public relief for\nrefugees and asylum-seekers in possession of their individual documentation on par with nationals of Chad.\n\n**4.1** **Education**\n\nArticle 21 of the [2020 Asylum Law](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf) specifies that every refugee or asylum-seeker in possession of individual\ndocumentation enjoys the right to education and vocational training under the same conditions as nationals.\n[The same is reiterated by Article 65 of the 2023 Decree. Despite not explicitly mentioning asylum-seekers](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf)\nin its wording, Article 32 of the 2020 Law and Article 75 of the 2023 Decree should be interpreted in the\nspirit of Article 21 of the law and Article 65 of the Decree that asylum-seekers are equally entitled to the\nsame treatment as nationals regarding education.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The government of Brazil has taken steps towards the recognition of the central role played by\nlocal authorities in protecting and promoting local integration of forcibly displaced persons. In\nNovember 2023 the Ministry of Justice and Public Security has launched the \"National Network\nof Welcoming Cities - Red Nacional de Cidades Acolhedoras\" with the objective of strengthening\ndialogue and actions around public policies and programs for migrants, refugees and stateless\npeople. UNHCR has since 2020 being supporting the Cities of Solidarity initiative in Brazil helping\nsharing experiences among the network of cities forming part of initiative and has recognized best\npractices from 17 municipalities.\n\nIn recent year, Brazil has experienced an increasing number of climate disasters, which have been\nmore frequent and severe and have been affecting a growing number of people, including\npopulations already displaced in Brazil. The Government is developing a Climate Plan as well as\nrisk reduction, adaptation, and resilience plans, which takes into account displacement impact;\nwhile the legislative branch is discussing bills to regulate and respond to internal displacement.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland Analysis of the impact of refugees from Ukraine on the economy of Poland impacts of immigration reviewed in the This outcome is rather modest compared Appendix. [19 ] Because marginal productivity to a cross-country panel model estimated of capital remained the same and the in an IMF report, in which a 1.7% Ukrainian\n\n## 3. population of Poland increased more refugee share in the adult population of\n\nthan the number of workers (primarily by Poland should eventually result in about Ukrainian refugee children), the impact on 3.4% higher GDP per capita (Jaumotte GDP per capita has been smaller – at 0.2%. et al., 2016).\n\n## Economic impact of Chart 17. Gross domestic product growth paths with and without Ukrainian refugees\n\nDeloitte D.Climate model calibrated to the Ministry of Finance GDP growth forecast.\n\n140\n\n## Ukrainian refugees\n\nimpacts of immigration reviewed in the Appendix. [19 ] Because marginal productivity of capital remained the same and the population of Poland increased more than the number of workers (primarily by Ukrainian refugee children), the impact on GDP per capita has been smaller – at 0.2%.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Note:_ Figure 5 shows the main treatment coefficients ( _active*mine_ ) using the baseline estimation strategy (with\nDHS individual-level data; see table 4 for more information) in the top panel, but with different cutoffs (10 km,\n20 km, 30 km, 40 km, and 50 km). *** p<0.01, **p<0.05, *p<0.1. The bottom panel shows the result using a\nspatial lag model that divided the plane into different treatment bins (0–10, 10–20, 20–30, 40–50) and compares\nthem with farther away. Panel A shows the result for nonmigrants, and panel B shows the result for migrants.\n\n**6.2 Access to infrastructure and health care**\n\nAnother source of heterogeneity is asset ownership and access to infrastructure. Table 8 shows\n\nthat fewer households have electricity in active mining communities, but they spend less time\n\nfetching water and are more likely to own a radio (all estimates are statistically insignificant,\n\nhowever). There is no change in the likelihood of having a flush toilet. Moreover, it seems that\n\nhouseholds are just as likely to have access to a pit toilet as not having a toilet (and instead\n\nuse a bucket, bush, and so forth).\n\n**Table 8 OLS estimates for ownership of assets and access to infrastructure**", "output": {"entities": {"named_data": [{"text": "DHS individual-level data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "To facilitate trend monitoring, the questionnaires were standardized across all countries, ensuring consistency in the majority of indicators between 2023 and 2024. Since the 2023 regional survey did not include data from Latvia, Lithuania, and Estonia, values for these countries were excluded from the 2023–2024 comparison. To maintain accuracy, only valid responses were included in the calculations, with responses such as ‘prefer not to answer’ or ‘do not know’ excluded. To facilitate interpretation, certain response options were consolidated into broader categorical variables.\n\nTo protect data privacy and maintain confidentiality, informed consent was obtained and documented from all participants, with clear explanations provided regarding the purpose and use of the data. The complete questionnaires, along with the consolidated anonymized dataset, are available in the [UNHCR Microdata Library.](https://microdata.unhcr.org/index.php/catalog/?page=1&from=2023&to=2024&region%5B%5D=3&ps=100)\n\n# Limitations\n\nThis analysis has several limitations that should be considered when interpreting the findings. First, due to sampling constraints (lack of complete sampling frame) and the non-probabilistic selection of respondents, the results may not fully represent the entire Ukrainian refugee population. Additionally, the choice of sampling locations may have introduced a bias toward more vulnerable segments of the population. Variations in sampling approaches and data collection periods across countries can also affect comparability.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**in Poland.** According to the SEIS survey,\nUkrainian refugees with master’s and PhD degrees earn a 22% higher median net wage than those with only secondary education. This appears to be a small gain, even accounting for the fact that, generally, the differences between median wages are less pronounced than between average wages (which are pulled higher by top incomes) and that our method of wage estimation based on SEIS household incomes [26] flattens the distribution.\nAccording to the most recent estimate in October 2022, in the economy as a whole, the average gross wage of master’s and PhD degree holders was 84% higher than those with only secondary education. [27]\n\n**Most Ukrainian refugees work in**\n\n**a different sector than previously**\n\n**in Ukraine, which also points to**", "output": {"entities": {"named_data": [{"text": "SEIS survey"}, {"text": "SEIS household incomes"}], "descriptive_data": [], "vague_data": []}}}
{"input": "As of the end of 2023, 5.9 million refugees from Ukraine were recorded across Europe, close to 2 million of whom are in the countries covered by the\n[Regional Refugee Response Plan (RRP)](https://data.unhcr.org/en/documents/details/105903) [5] . To better understand their evolving situation, unpack risks and vulnerabilities and inform planning across sectors, Multi-Sectoral Needs Assessments (MSNA) were conducted under the RRP between June and September 2023 by UNHCR’s Regional Bureau for Europe and its Inter-Agency partners. This publication focuses on the results for livelihoods and socio-economic inclusion and attempts to draw conclusions based on survey data of 11,496 households (and 26,857 individuals) living in Bulgaria, the Czech Republic, Hungary, the Republic of Moldova, Poland, Romania, and Slovakia.\n\n### **Socio-economic** **inclusion – key** **findings**\n\n**Refugee households demonstrate a high degree**\n\n**of economic vulnerability**\nThe MSNA survey data demonstrates that refugee households from Ukraine are characterized by a high degree of economic vulnerability. On an individual basis, half live with an equivalized disposable income [6] that falls below 50% of the host population median [7] (a commonly used poverty threshold). This contrasts with just 9% of nationals belonging to the same income bracket.\n\n**THE POVERTY RATE** **[1]** **OF REFUGEES VERSUS HOST**\n\n---\n[7] Based on [OECD data from 2021, which was indexed by the CPI for 2022 and 2023 for each respective country](https://stats.oecd.org/)", "output": {"entities": {"named_data": [{"text": "MSNA survey data"}], "descriptive_data": [{"text": "survey data of 11,496 households"}, {"text": "OECD data from 2021"}], "vague_data": []}}}
{"input": "The high employment rate of refugees in Poland covers not only employees, but also entrepreneurs. Five percent of Ukrainian refugees registered for social security have set up a business or work as freelancers. Similar results can be gleaned from the Multi-Sector Needs Assessment Poland 2023 survey results, which show that slightly more than 5% of respondent households receive income from selfemployment or similar activities.\n\nAll broad sectors of the economy saw an increase in the number of workers with Ukrainian citizenship and social insurance since 2021, apart from storage and transportation. The number increased the most in manufacturing (almost by 34 thousand), accommodation and food (more than 18 thousand), and wholesale and retail trade (more than 18 thousand). [11] While public data does not distinguish between refugees entering these sectors and pre-2022 Ukrainian workers changing jobs, it is largely consistent with the MSNA Poland 2023 survey, in which the most refugees are employed in manufacturing (14%), accommodation and food service (12%), and trade and repair (6%).\n\nUkrainian refugee households in Poland\n\n---\n[11] According to the social security data until 30th September 2023.", "output": {"entities": {"named_data": [{"text": "MSNA Poland 2023 survey"}], "descriptive_data": [], "vague_data": [{"text": "social security data"}]}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n**BARRIERS TO ACCESSING SRH SERVICES**\n\nLong waiting times Could not afford transport Lack of knowledge Could not afford clinic fee Unable make appointment Language barrier Could not afford hospital Do not trust local provider Lack health insurance No means of transport (N=363) 33% 23% 22% 19% 18% 15% 12% 11% 10% 7% In urban areas, financial barriers, such as transportation costs and clinic fees, were the most reported obstacles to accessing SRH services. In contrast, women in rural settings faced challenges primarily related to knowledge of services, appointment-making and language barriers.\n\n**Barriers in accessing SRH care for different**\n\n**groups**\nThe number of respondents who faced barriers in accessing SRH services in the adolescent, youth, pregnant and breastfeeding women, and persons with disabilities categories was low, and data needs to be interpreted with caution. However, the findings offer valuable insights into the experiences of individuals in these categories.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Many of the refugees that settled in Poland remain in special needs or otherwise precarious households. According to the MSNA Poland 2023 survey, nearly half of all refugee households have a person with a chronic illness, while in nearly 10% there is a disabled person (Washington Group level 3 disability). In over a third of all households is a single parent and over a fifth houses an elderly person (10% of households are comprised of exclusively elderly people).\n\nhouseholds with persons with chronic ilness households with a single parent households with one or more older persons households with disabled individuals households exclusively with elderly", "output": {"entities": {"named_data": [{"text": "MSNA Poland 2023 survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "1. Host Communities\n\nEven though the [Law 021-PR-2019 on legal aid and judicial assistance was enacted in 2019, its implementation](https://www.refworld.org/docid/609f00834.html)\nhas been stalled due to the absence of an implementing Decree. Chad is planning to commit to adopting\nthis Decree at the 2023 December Global Forum on Refugees.\n\nFurthermore, it also important to note that the new asylum legislation enacted during the prescribed period\nhas also incorporated a few provisions to promote peaceful coexistence including through securing the\nright of refugees and asylum-seekers to access State legal aid services to prevent and/or resolve conflict.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Citizenship and Immigration Act to remove the time-limitation for registration of stateless persons and align the\n\ndefinition of a stateless person with the definition in the 1954 Convention; acceding to the two UN statelessness\n\nconventions and ratification of the Protocol to the African Charter on Human and Peoples' Rights on the Specific\n\nAspects of the Right to a Nationality and the Eradication of Statelessness in Africa; enhancing birth registration\n\nsystems to prevent future statelessness; simplifying procedures for nationality application and documentation; and\n\nimplementing community outreach programs to raise awareness about the rights and entitlements of citizenship.\n\nThe Kenyan government is also encouraged to continue its leadership on this issue by advocating for regional and\n\ninternational cooperation to address statelessness, including sharing best practices and lessons learned from its\n\nnational experience.\n\n**4. Promote international collaboration and investment to support stateless populations in gaining nationality and**\n\n**legal identity and accessing essential services.**\n\nGovernments, international organizations, and development agencies should work together to ensure stateless\n\nindividuals receive the support needed to obtain nationality and legal documentation. This includes nationality law\n\nand policy changes enabling stateless people to acquire nationality, investing in robust and inclusive civil registration", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**violence**\nServices for survivors of gender-based violence encompass a range of functions, including safety and security, legal assistance, healthcare, mental health and psychosocial support. A critical component is access to clinical management of rape to ensure timely medical treatment and care.\nAs this service is provided by the health care sector, as part of SRH, it is included in this analysis.\n\nThe SEIS identified gaps in awareness about on available GBV services. In 2024, 38% of respondents were unaware of health services providing support to GBV survivors in their area, while 58% were unaware of available psychosocial support services. Respondents were less aware of health services in rural areas (45%) compared to urban areas (37%). Key barriers to accessing GBV-related services in general included lack of awareness (58%), language and cultural barriers (53%) and stigma/ shame (46%). This indicates that additional coordinated efforts between the health, protection and GBV working groups and partners are required to enable access to all lifesaving GBV-related services including clinical management of rape.\n\n**17**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Indonesia’s new president and vice president were inaugurated in October 2024. This new\ngovernment offers an opportunity to renew and expand Indonesia’s humanitarian leadership on\nrefugee issues. The country is a regional and global power – the fourth largest country by population\nin the world, the largest majority Muslim country in the world, the largest economy in southeast Asia,\nand recent leadership roles as the President of the G20 and the Chair of ASEAN. Advocacy efforts will\nseek to ensure Indonesia does not solely embrace political, economic, and military leadership, but that\nthe country also showcases independent humanitarian leadership – particularly on refugee issues.\n\n### **UN Common Pledge**\n\nThe UN Common Pledge offers new opportunities to strengthen the protection environment in\nIndonesia. At the 2023 Global Refugee Forum, several agencies in the UN Country Team (UNHCR, IOM,\nUNFPA, WHO, UNDP, ILO, UNICEF, FAO, and UNESCO) pledged to provide guidance, technical support,\nand advocacy to enable refugee inclusion in Indonesia in four key areas: education, health, selfreliance, and birth registration. UNHCR will work closely with these agencies in 2024 and beyond to\nsecure inclusive policies and an enabling protection environment in the country.\n\n### **Enhancing Engagement with Refugees**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In effect, immigrants increase not just the size of the economy, that is the gross domestic product, but its productivity as well. While this has been well documented on the macroeconomic level, showing the existence of the effect, the exact channels remain unclear. Jaumotte et al. (2016) in an IMF report show that an increase of 1 percentage point in the share of immigrants in the adult population increases GDP per capita by 2% in a sample of 18 developed OECD countries during the period from 1980 to 2010. It should be noted that this model would yield much higher estimates for Ukrainian refugees than those presented in this appendix, given that they currently constitute 2% of Poland’s adult population. Aleksynska and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**tant participated in a two-day MHPSS**\n\n**coaching organized by PAHO and led**\n\n**by an international IASC consultant.**\n\nThis coaching, held during the second\n\nweek of October, aimed to strengthen the\n\nMental Health and Psychosocial Support\n\nTechnical Working Group’s role by eval\nuating its work plan, achievements, and\n\nthe next steps. The coaching agenda\n\nintended to bring accompaniment and\n\nadvice to people with coordination\n\nfunctions for the implementation of an\n\nMHPSS strategy in their organizations,\n\nagencies, and clusters.\n\nThese efforts represent a significant\n\ninter-institutional initiative to empower\n\nprofessionals in the field, providing\n\nknowledge and tools essential for effi\ncient organizational functionality during\n\nhumanitarian emergencies. Following\n\nthese activities, the working group plans\n\nto implement its work plan, emphasizing\n\nMHPSS as a cross-cutting topic in the\n\nhumanitarian architecture.\n\n**XIV. Impact Stories of Series:**\n\n**September and October**\n\n_a. Premiere Urgence Internationale (PUI)_\n\n_(September):_ The subnational cluster of\n\nBolívar, in coordination with the national\n\nPC, visited PUI's activities in Casaco\nima, Delta Amacuro state. PUI's project\n\nfocuses on improving living conditions\n\nthrough mental health, physical health,\n\nand WASH. Beneficiaries of the project\n\nwere interviewed for a better under\nstanding of the projects’ impact. The\n\ninterviews confirmed how mental and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "While there have been some important advancements in refugee inclusion in Indonesia, the\ncharacterization of the refugee experience in Indonesia as a transient one creates little impetus for\npolicy makers to develop comprehensive and inclusive protection policies. For refugees, resettlement\nexpectations have discouraged engagement in constructive experiences in Indonesia, including\neducation, training, skills building, and self-empowerment opportunities; fostered a sense of\nunfairness, anxiety, and frustration; led to a deterioration in mental health; and eroded trust in UNHCR\nand partners.  UNHCR’s efforts to work with and for the refugee community are also undermined by\nthe unique focus on resettlement in the country, impacting outreach and communication efforts, the\nprioritization of human and financial resources, staff security, and programming.\n\n### **Lack of Access to Opportunities for Economic Empowerment**\n\nRefugees are unable to work legally in Indonesia, creating economic vulnerabilities and compounding\nprotection risks for the refugee population. In addition to economic insecurity, lack of access to work\nimpacts refugees in a number of ways: informal work experiences may render refugees vulnerable to\n\nUNHCR / 1 November 2024 7", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "UNHCR will continue to expand the ways in which we engage with refugees in 2024 and 2025. A\ncornerstone of these activities is the rollout of the Digital Gateway, a corporate self-service tool being\npiloted in Indonesia that will address many of the concerns of the refugee community, as well as the\ngeographic challenges in Indonesia, by providing a platform through which refugees can remotely\ncommunicate with UNHCR, view their bio-data, update contact information, book appointments for\nservices, and obtain updates on case processing status.\n\nIn addition to the Digital Gateway, UNHCR is strengthening tools of engagement and communication\nwith the refugee community following several years of more limited contact resulting from COVID\nrestrictions and security challenges in the field. These initiatives include re-instituting walk-in\ncounseling at the UNHCR reception center; revitalizing the UNHCR HELP website; expanding refugee\nTown Halls to respond to queries and share information; undertaking regular outreach missions to\n\nUNHCR / 1 November 2024 9", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n**% OF INDIVIDUALS REPORTED WITH A CHRONIC ILLNESS**\n\n**AND THOSE WITH DISABILITY LEVEL 3 AND ABOVE**\n\nChronicle illness Disability level 3 and above\n\n**% OF INDIVIDUALS WITH DISABILITY BY AGE AND GENDER**\n\nFemale Male 23% 23% Regional Czechia Estonia Lithuania Latvia Poland Slovakia Hungary Bulgaria Moldova Romania 3% 3% 5-17 18-34 35-59 60+ years old (N=18,679) Regionally, 26% of individuals self-reported a chronic illness (5,384 individuals out of a sample of 19,622), with rates ranging from 17% in Czechia to 34% in Moldova and Romania, closely followed by Bulgaria at 32%. Chronic illnesses increase with age, with 77% of individuals over 60 reporting a chronic condition (78% of women, 72% of men).\nRegionally, women above the age of 35 selfreported a higher rate of chronic illness compared to men.\n\n**% OF INDIVIDUALS WITH CHRONIC ILLNESS BY AGE AND**\n\n**GENDER**\n\nFemale Male (Chronic Illness N=19,622, Disability N=18,679)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "## **HELPING HANDS** THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE\n\n#### An inter-agency exploration of socio-economic data April 2024", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "socio-economic data"}]}}}
{"input": "and other forms of violence. Beneficia\nries mentioned that they feel grateful for\n\nall the work of FPM and wish that more\n\ncommunities could benefit from such\n\nsensitizations and trainings, which are\n\nrelevant to the daily realities they expe\nrience.\n\n[Full access to the story through this link.](https://www.globalprotectioncluster.org/publications/1689/reports/report/historias-de-impacto-de-socios-cluster-de-proteccion-octubre-2023)\n\n**XV. Protection Service Mapping**\n\n**Revisions and Edits**\n\n**In line with the Protection Cluster’s**\n\n**efforts to guarantee a functioning and**\n\n**updated service mapping, together**\n\n**with the UNHCR IM Unit, the Pro-**\n\n**tection Service Mapping database**\n\n**underwent a comprehensive review**\n\n**and** **update** **in** **September** **and**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**REFUGEE VS HOST EMPLOYMENT RATES BY COUNTRY**\n\nRefugee (2023) Refugee (2024) Host (2023) 76% 76% 76% 62% Bulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia Region Note: For comparability, employment rates for host countries have been recalculated assuming a similar gender distribution to that of refugees Source: ILO, survey data 14. The employment rate is defined as the number of employed or self-employed individuals of working age (15-64) as a share of the total number of people in this age group 15. The labor force is defined as the number of people that are either employed or unemployed\n\n**10**", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "ILO, survey data"}], "vague_data": []}}}
{"input": "3. Economic Opportunities\n\ncountry, most Chadians traditionally obtain land through the family or lineage, following the principle of\nfirst occupancy and, for women, through marriage.\n\nIn practice, refugees have access to agricultural land through sharecropping, loans or leases.\n\nIt is important to note that before the enactment of the new asylum legislation and in the absence of clear\nrules, refugees theoretically had the right to purchase land. However, this was challenging due to the\nprevalence of the traditional ownership system, their inability to produce financial documents and other\nadministrative obstacles.\n\nIn practical terms, refugees continue to encounter greater challenges than nationals in accessing large,\nfertile land parcels due to their distance from the camps. When engaging in sharecropping agreements\n(métayage), refugees are required to share a portion of the harvest with the landowner or pay rent for\nthese lands, which can sometimes amount to 50,000 FCFA per hectare per year.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "surrounding communities. [ [3], [4]] Acquiring citizenship, brings the promise of improved employment and earnings, [[5]]\n\nespecially among women and the poorest, [[6]] while also offering broader social and economic benefits, as increases\n\nin talent, skills and taxation accompany legalization.\n\n**Since 2014, more than 500,000 stateless people have acquired a nationality globally.** Statelessness for many\n\nothers has been prevented as a result of efforts to improve birth registration and issuance of nationality documents\n\nto populations at risk of statelessness and legislative changes, including those that eliminate discrimination on the\n\nbasis of gender, allowing women to pass on nationality to their children on an equal basis as men, However,\n\nacceleration of efforts is needed to ensure that everyone can enjoy the fundamental right to a nationality, which\n\noften enables the enjoyment of other rights and full participation in the society.\n\n**Kenya has emerged as a global leader in the eradication of statelessness, setting an example for other nations**\n\n**through its continued efforts to reduce the number of stateless persons within its borders.** The country has made\n\nsignificant strides, beginning with the recognition of 1,496 members of the Makonde community as nationals of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Despite a historically enabling environment for refugees and other forcibly displaced in Chad, the lack of\na specific refugee legal framework has been a longstanding issue. The new 2020 asylum Law contributed\nto addressing this vacuum and enhances the existing national institutional framework for the protection\n[of refugees and asylum-seekers assumed by CNARR, as established by the 2011 Decree establishing the](https://www.refworld.org/docid/609efe754.html)\n[National Commission for the Reception, Reintegration of Refugees and Returnees](https://www.refworld.org/docid/609efe754.html) (Décret n°839/PR/PM/\nMAT/2011, CNARR). This latter remains in force given the role played by CNARR to supervise the refugee\nmanagement in the country. The new asylum Law clarifies the principles applicable to refugees and asylumseekers to ensure their protection and provides a legal basis for their civil and socio-economic rights, including\nfreedom of movement, access to justice, the right to work, healthcare, education and land. Additionally, the\nnew asylum Law grants refugees the same rights as Chadian citizens regarding education, healthcare and\nsocial protection. It also provides for the recognition of the refugee identity card as a residence permit.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "individuals in the East, Horn, and Great Lakes of Africa region, as well as the millions of stateless people globally,\n\ndemonstrating that resolving statelessness is not only a matter of human rights but also of inclusive economic\n\ndevelopment.\n\n## **Recommendations**\n\n**1. Develop holistic, long-term policy frameworks that address the socioeconomic and human rights dimensions of**\n\n**statelessness.**\n\nNational governments and international stakeholders should adopt inclusive development policies that go beyond\n\nlegal recognition to ensure the full social and economic integration of stateless and formerly stateless populations.\n\nThis entails ensuring equitable access to education, healthcare, employment, and social protection services for\n\nnewly recognized citizens. Governments should be encouraged to introduce targeted social safety nets and\n\nemployment support programs to reduce poverty and promote resilience among stateless and formerly stateless\n\ngroups. UNHCR and the World Bank, in partnership with national governments and NGOs, can provide technical\n\n**[www.unhcr.org](http://www.unhcr.org/)** 10", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "This communication contains general information only, and none of Deloitte Touche Tohmatsu Limited (“DTTL”), its global network of member firms or their related entities (collectively, the “Deloitte organization”) is, by means of this communication, rendering professional advice or services. Before making any decision or taking any action that may affect your finances or your business, you should consult a qualified professional adviser.\n\nNo representations, warranties or undertakings (express or implied) are given as to the accuracy or completeness of the information in this communication, and none of DTTL, its member firms, related entities, employees or agents shall be liable or responsible for any loss or damage whatsoever arising directly or indirectly in connection with any person relying on this communication. DTTL and each of its member firms, and their related entities, are legally separate and independent entities.\n\n© 2025. For information, contact Deloitte Poland.\n\n**Scan the QR code**\n\n**and download**\n\n**the report!**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n**REGIONAL REFUGEE EMPLOYMENT RATE BY LEVEL OF**\n\n**LOCAL LANGUAGE KNOWLEDGE (2024)**\n\nEmployment rate Share of the refugee population (rhs) 80% 60% 40% 20% 0% 35% Does not understand Beginner Intermediate Advanced Fluent Source: Survey data The 2024 survey introduced a new question on local language proficiency, reinforcing previous findings of a strong correlation between language skills and employment. Respondents with at least an intermediate level of local language proficiency reported nearly twice the employment rate compared to those with no knowledge (9% of respondents). Even Ukrainians with only a basic understanding—limited to a few words or phrases (28% of the sample)—experienced a notable increase in employment compared to those with no local language skills [16] .\n\nFinally, unlike for the host population, refugee employment rates were found to be practically the same for all education levels above technical or vocational [17], implying that local employment markets may not be valuing advanced degrees. Possible explanations include impediments to foreign qualifications recognition and other barriers that are preventing placement into high-skilled jobs (such as language, a mismatch between qualifications and local demand, etc.).", "output": {"entities": {"named_data": [{"text": "The 2024 survey"}], "descriptive_data": [], "vague_data": [{"text": "Survey data"}]}}}
{"input": "# **Population** **Data Analysis**\n\n### **Regional Bureau** **for Southern Africa**\n\n**September 2022**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In 2023, the national utilization rate was 0.31 new consultations per inhabitant per year, while in the camps, it\nstood at 1.2 new consultations per refugee per year. This indicates that healthcare access is more favourable\nin the camps than host populations. The disparity can be attributed partially to improved geographical access\nin the camps, but more significantly, it is driven by financial factors. Notably, healthcare is provided free of\ncharge in refugee camps, whereas state facilities require fees for healthcare services. For refugees living\noutside the camps, UNHCR, through its health partner, has signed agreements with state health centers for\nfree access, with costs covered by partners under UNHCR’s budget.\n\nSexual and reproductive healthcare is integrated into the package of services offered in refugee camps\ncovered by UNHCR and partners’ budget. As of June 2023, the rate of assisted childbirth was 91% in the\nrefugee camps.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "While the majority of people were able to access health care services, 17% were unable to access needed care across the region. The unmet need was reported highest in Romania (28%), Hungary (22%), and Slovakia (21%).\n\nRegionally, unmet health needs were higher for individuals with chronic illnesses compared to those without chronic illnesses (21% vs 12%) and higher compared to 2023 (15% vs 10%). Similarly, unmet\n\n**11**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Attempts to access support differed by age, with caregivers of the youngest age group (5–11 years) being the most likely to seek support on their behalf, while older persons less often attempted to access support. In addition, in both 2023 and 2024, there were consistent gender differences in attempts to access support. In all age groups except children under 11, females attempted to access support more often than males. The gender gap in seeking support was most pronounced in the older age groups: among individuals aged 35-59, 47% of women tried to access services compared to only 31% of men, suggesting potential social and cultural", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**% OF INDIVIDUALS EXPERIENCED HEALTH PROBLEM IN**\n\n**LAST 30 DAYS BY GENDER AND AGE**\n\nFemale Male\n\n### **Access to care**\n\nRegionally, of the individuals who experienced health problems 30 days prior to the survey, 83% were able to obtain care, compared to 88% in 2023.\nWith host countries continuing to implement necessary legislation that allows refugees access to health care, reported access to health services has remained above 70% in all countries. However, after three years of the crisis, a steady improvement in access has been seen in only a few countries notably Bulgaria and Czechia. Notably, access to needed care was highest in Latvia and Czechia at 94%.\n\n**% OF INDIVIDUALS WITH ACCESS TO HEALTH SERVICES**\n\n**(OUT OF THOSE WHO REPORTED A HEALTH PROBLEM IN**\n\n**THE LAST 30 DAYS)**\n\nObtained health services Unmet health care need Regional Latvia Czechia Estonia Bulgaria Moldova Poland Lithuania Slovakia Hungary Romania (N=6,108) 83% 94% 94% 88% 86% 85% 83% 83% 79% 78% 72% 17% 14% 15% 17% 17% 21% 22% 28% 6% 6% 12% 0-4 5-17 18-34 35-59 60+ years old (N=19,637)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "calculate from each mine location to each DHS cluster. This is also the distance measure that\n\nwe use to create the “mine” dummy, which captures whether the cluster lies within 20 km of a\n\nknown gold deposit. Note that we only consider deposits that have been in production at some\n\npoint until December 2012.\n\nAll households are thus within 100 km of one, or several, gold deposits. To ascertain whether\n\nthere is any gold production in these potential mining sites, we construct an indicator variable\n\n_active_, which takes a value of 1 if there is at least one mine within 100 km that was extracting\n\ngold in the year the household was surveyed, and 0 otherwise. While the _mine_ dummy captures\n\nsome of the special characteristics of mining areas (for example, whether mines tend to open in\n\nless urban areas), the _active_ dummy captures long-range spillovers of mining.\n\nThe treatment effect that we are mostly interested in is captured with the _active*mine_\n\ncoefficient. The coefficient for _β3_ tells us what the effect of being close to an actively producing\n\nmine is. Since the inclusion of the three dummies ( _active_, _mine_, and _active*mine_ ) captures the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "work, and the likelihood increases by 5.4 percentage points, which is equal to a 6 percent\n\nincrease.\n\nWhile the directionality of the occupational outcomes is broadly in line with previous results\n\n(Kotsadam and Tolonen, 2016, for 29 African countries, and Benshaul-Tolonen, 2018, for 8\n\nAfrican gold-producing countries), the estimates are largely insignificant, potentially due to a\n\nlimited sample size. Two categories have positive, albeit insignificant, coefficients: services\n\nand manual labor. The (insignificant) estimate for service jobs [9] is equivalent to 6.7% increased\n\nemployment, and manual labor 10.2%, alongside which the likelihood that a woman earns cash\n\nfor her work increases with 6%.\n\nFor men (panel B of table 4), the estimates point toward an increase in agriculture, services,\n\nand professional (all statistically insignificant estimates), but a decreased likelihood of working\n\nin manual labor. Results for men in panel B are largely insignificant, and it is worthwhile noting\n\nthat the sample size is only slightly above 50% than the women sample size due to DHS\n\nsampling frame.\n\n**Table 4 OLS estimates women’s and men’s occupation in the DHS individual-level analysis**\n\nOccupation\n\n---\n[9] Service sector jobs in the wake of structural transformation has been found important in", "output": {"entities": {"named_data": [{"text": "DHS"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Peri, G. (2012). The effect of immigration on productivity: Evidence from US states. Review of Economics and Statistics, 94(1), 348-358.\n\nPeri, G. (2014). Do immigrant workers depress the wages of native workers? IZA World of Labor, 42.\n\nPeri, G. (2016). Immigrants, productivity, and labor markets. Journal of economic perspectives, 30(4), 3-30.\n\nPeri, G., & Sparber, C. (2009). Task specialization, immigration, and wages.\nAmerican Economic Journal: Applied Economics, 1(3), 135-169.\n\nPeterson, B. D., Pandya, S. S., & Leblang, D. (2014). Doctors with borders: occupational licensing as an implicit barrier to high skill migration. Public Choice, 160(1-2), 45–63. doi:10.1007/s11127-014-0152-8 Schmid, L. (2023). The impact of host language proficiency on migrants’ employment outcomes. American Economic Review: Insights, 5(4), 477-493.\n\nSohst, R., Tirado, T., Salgado, L., & Slootjes, J. (2024). Exploring Refugees’ Intentions to Return to Ukraine: Data Insights and Policy Responses.\nInternational Organization for Migration and Migration Policy Institute Europe.\n\nStrzelecki, P., Growiec, J., & Wyszyński, R. (2022). The contribution of immigration from Ukraine to economic growth in Poland. Review of World Economics, 158(2), 365-399.\n\nTokariuk, O. (2025). Ukraine’s fight for its people. Strategies for refugee and diaspora engagement, Ukraine Forum, Chatham House, February.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**4.2** **Health care**\n\n[Article 21 of the Asylum Law](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf) stipulates that every refugee or asylum seeker is entitled to the right to health\nunder the same conditions as nationals.\n\nDuring the prescribed period, Chad has developed a new [National Health Development Plan for 2022-](https://www.afro.who.int/fr/countries/chad/publication/plan-national-de-developpement-sanitaire-pnds-4-2022-2030#:~:text=PLAN%20NATIONAL%20DE%20DEVELOPPEMENT%20SANITAIRE%20(PNDS%204)%202022%2D2030,-Le%20Minist%C3%A8re%20de&text=Le%20PNDS4%20est%20le%20dernier,des%20Objectifs%20de%20D%C3%A9veloppement%20Durable.)\n[2030, aiming to establish an integrated, efficient, resilient, and person-centered health system. This plan](https://www.afro.who.int/fr/countries/chad/publication/plan-national-de-developpement-sanitaire-pnds-4-2022-2030#:~:text=PLAN%20NATIONAL%20DE%20DEVELOPPEMENT%20SANITAIRE%20(PNDS%204)%202022%2D2030,-Le%20Minist%C3%A8re%20de&text=Le%20PNDS4%20est%20le%20dernier,des%20Objectifs%20de%20D%C3%A9veloppement%20Durable.)\nincludes refugees and asylum seekers, ensuring their access to public health services on an equal basis with\nnationals. Refugees and asylum-seekers are also incorporated into national, provincial, and departmental\n\nR E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **R E P U B L I C O F C H A D** 11", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "productivity, which is the part of labour productivity coming from organisational and technological innovations, in a sample of U.S. states in the period 19602006. He finds that a 1 percentage point increase in the shares of immigrants raises labour productivity by 0.9% and TFP by 1.4%. These estimates are causal, as the author uses distance from the Mexican border and previous immigrant communities, which are both orthogonal to economic growth in host states.\nWhat is further interesting, is firms in reaction to immigration adapt production technologies directed to workers without college education. This is consistent with the idea, that firms make workers more productive by adapting technologies to their skill sets. It is also important that these positive effects for productivity have been achieved despite immigrant inflow comprised less educated workers.\n\n39", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "RESETTLEMENT KEY FIGURES\n\n**Submitted Cases**\n\n1,063 4,497\n\n**Cases** **Case Members**\n\n**Active Cases**\n\n986 4,219\n\n**Case** **Case Members**\n\n**Submitted Cases Member by**\n\n**Country of Submission**\n\nREGIONAL BUREAU FOR SOUTHERN AFRICA\n\n**PERSONS OF CONCERN INVOLVED IN RESETTLEMENT IN SOUTHERN AFRICA**\n\nAs of 30 September 2022\n\nMOVEMENTS OF GROUPS OF 10 OR MORE RESETTLEMENT CASE MEMBERS\n\n**Country of Origin** **Country of Submission** **Country of Resettlement**\n\nMAP OF THE DEPARTURES BY COUNTRY OF SUBMISSION\n\n**Departure Cases**\n\n337 2,067\n\n**Case** **Case Members**\n\n**Quota**\n\n6,483 69%\n\n**Allotcated Quota** **% of Submission vs Quota**\n\n**Balance (Quota/Submission) :** 1,986\n\n**Departure Cases by Age and Gender**\n\n**ZAM**\n\n**MLW**\n\n**RSA**\n\n**ZIM**\n\n**MOZ**\n\n**ANG**\n\n**BOT**\n\n**NAM**\n\n**COB**\n\n**COD**\n\n**USA**\n\n**SWE**\n\n**NZL**\n\n**FIN**\n\n**NOR**\n\n**CAN**\n\n**AUL**\n\n**FRA**\n\n**493**\n\n**303**\n\n**205**\n\n**28**\n\n**27**\n\n**13**\n\n**11**\n\n4%\n\n9%\n\n9%\n\n26%\n\n0%\n\n0-4\n\n5-11\n\n12-17\n\n18-59\n\n60+\n\n3%\n\n12%\n\n9%\n\n1%\n\n26%\n\n**Submitted Cases Members**\n\n**by Top 10 Country of Asylum**\n\n**MLW**\n\n**ZAM**\n\n**3,417**\n\n**1,438**\n\n**1,367**\n\n**Departure Cases Members**\n\n**by Top 10 Country of Asylum**\n\n**1,247**\n\n**464**\n\n**169**\n\n**122**\n\n**16**\n\n**15**\n\n**14**\n\n**12**\n\n**2**\n\n**2**\n\n**RSA**\n\n**ZIM**\n\n**NAM**\n\n**BOT**\n\n**MOZ**\n\n**MAD**\n\n**519**\n\n**487**\n\n**355**\n\n**157**\n\n**96**\n\n**36**\n\n**Submitted Cases Members**\n\n**by Top 10 Country of Origin**\n\n**Departure Cases Members**\n\n**by Top 10 Country of Origin**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "[Article 24 of the Asylum Law accords refugees a treatment as favourable as possible and, in any event,](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf)\nnot less favourable than that accorded to aliens generally in the same circumstances, concerning the\nacquisition of movable or immovable property, lease contracts and other associated rights. Article 67\nof the [2023 Decree](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf) adds that refugees lawfully staying in the country shall have the same treatment\nas foreigners in general concerning that right. Article 29 of the Asylum Law also accords refugees\nlawfully staying in Chad treatment as favourable as possible concerning housing which falls under\nnational legislation, or which is submitted to public control, and, in any event, not less favourable than\nthat accorded to aliens generally in the same circumstances. Article 71 of the 2023 Decree specifies\nthat refugees lawfully staying in Chad should be accorded the same treatment as foreigners in general\nregarding housing subject to the laws and regulations in force. Key to note is that Article 61 of the 2023\nDecree, specifically addressing local integration as a durable solution, specifies that the Government\nprioritizes refugees’ right to access land and secure allocated land to achieve self-reliance.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**SCENARIO 1** **SCENARIO 2** **SCENARIO 3** **SCENARIO 4**\n\n**Low employment**\n\n**conservative**\n\n**productivity**\n\n**High employment**\n\n**conservative**\n\n**productivity**\n\n**Low employment**\n\n**baseline**\n\n**productivity**\n\n**High employment**\n\n**baseline**\n\n**productivity**\n\nThe main impact of refugees is in growth of the economy. Refugees increase both supply as workers and entrepreneurs as well as demand as consumers. Increase in GDP is not directly proportional to the increase in population or employment.\nNet benefits are lowered both due to a decrease in capital to labour ratio as well as an increase in competition on the labour market. Moreover, increase in demand in tight labour market conditions results in higher inflation and lower price competitiveness of Polish products which lower its overall positive impact.\nNevertheless, the positive impact of refugees on the economy is significant in every scenario considered.\n\nIn 2022 it amounts to real GDP being higher by 0.5-0.8% and in 2023 cumulatively by 0.7-1.1%.\nThis corresponds to GDP being higher by 24-36.9 billion PLN in 2023 [43] .\n\nIn the long term, total potential GDP should be higher by around 0.9-1.35% due to refugees contributions. [44]\n\n---\n[44] Note that long term refers to the time when the economy fully adjusts with no additional shocks. We do not model the current refugees from Ukraine", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In response to the recent arrival from Sudan from mid-April 2023 to the present, humanitarian agencies\nacted swiftly to support the government’s request. They coordinated a comprehensive, multisectoral\nhumanitarian response on the ground under the Refugee Coordination Model previously used during\nthe inflow of refugees from Cameroon and Central African Republic. This involved establishing sectoral\ngroups to ensure a consistent and comprehensive approach. While development actors were not directly\nengaged in formulating and financing emergency plans, they received regular updates on the implemented\nresponses by CNARR and UNHCR.\n\nR E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **R E P U B L I C O F C H A D** 3", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "reach the north of the continent through the Darien jungle or Europe through the French Guyana.\nIn this context, Brazil plays a crucial regional role and has the potential to offer effective legal and\nsocio-economic integration opportunities for displaced populations, which will contribute to the\nreduction of secondary movements.\n\nTo this end, the Government is set to launch Brazil's first National Policy on Migration, Asylum and\nStatelessness. Developed through an extensive participatory process involving concerned\npopulations, the policy aims to streamline access to rights and services at federal, state, and\nmunicipal levels. This will support the effective reception and integration of these populations into\nthe Brazilian society. Additionally, the Government has also adopted a Plan of Action to address\nthe protection and integration challenges faced by the Haitian population.\n\nMoreover, Brazil is launching a Resettlement, Admission, and Humanitarian Reception Program\nfor Afghan refugees through Complementary Means and Community Sponsorship. Authorities,\nwith the active support of UNHCR, are now developing Standard Operating Procedures for its\nimplementation, and planning ways to identify and train the civil society organizations who will be\nresponsible to receive these refugees in Brazil and support them in their local integration journey.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Two theories have been put forward in the literature to explain this:\n\n**01.** Immigrants and natives differ in terms\nof skills, occupational experiences, contact networks and work tasks.\nHence, they are not in direct competition. Typically, immigrants take on tasks previously performed by natives, who move to higher-valueadded tasks in the process known as “ **occupational upgrading** ” (Beerli and Peri, 2018; Tabellini, 2020; Cattaneo et al., 2015; Foged and Peri, 2016; D’Amuri i Peri, 2014; Ortega and Verdugo, 2014; Peri and Sparber, 2009).\n\nTritah (2015) found that a 1 percentage point increase in the rate of immigration increased GDP per capita growth by 0.3 percentage point in a sample of 20 developed OECD countries during the 1960–2005 period. Peri (2012) in a seminal paper, estimates that a 1 pp increase in the immigrant share raises labour productivity by 0.9% and TFP by 1.4%, using a sample of U.S. states from 1960 to 2006.\n\n37", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In \r 2012 \r the \r programme \r expanded \r to \r cover \r capacity \r building \r of \r government \r officials \r and\nother \r partners \r in \r relation \r to \r IDP \r and \r refugee \r protection \r and \r the \r role \r and \r mandate \r of\nUNHCR. \r Additionally, \r support \r has \r been \r provided \r by \r UNHCR \r to \r the \r Moe \r Pwint \r Operation\nthrough \r a \r pilot \r project \r as \r well \r as \r the \r production \r of \r leaflets \r in \r the \r local \r language \r to\nincrease \r the \r Ministry \r of \r Immigration \r efforts \r in \r enhancing \r awareness \r of \r the \r Operation\nwithin \r the \r communities.\n\n5 \r TBC \r 2012, \r see \r note \r 3 \r above.\n\n6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**2.3** **Institutional framework for refugee management and coordination**\n\nAccording to Article 38 of the [2020 Asylum Law, the institutional framework for the protection of asylum-](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf)\nseekers and refugees remains defined by [Decret n°839/PR/PM/MAT/2011, which establishes CNARR. In](https://www.refworld.org/pdfid/609efe754.pdf)\nessence, the introduction of the new asylum legislation in Chad has not altered the institutional framework for\nasylum. This legal reform has codified existing practices and brought clarity to the implementation of Decree\nNo. 11-839, which outlines the creation, organization and responsibilities of CNARR.\n\nIn practice, CNARR, which still operates under the Ministry of Public Security, Territorial Administration and\nLocal Governance (MSPARGL), remains responsible for coordinating the implementation of legal provisions\n\nR E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **R E P U B L I C O F C H A D** 5", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**1 Introduction**\n\nThe mining sector in Africa is growing rapidly and is the main recipient of foreign direct\n\ninvestment (World Bank 2011). The welfare effects of this sector are not well understood,\n\nalthough a literature has recently developed around this question. The main contribution of this\n\npaper is to shed light on the welfare effects of gold mining in a detailed, in-depth country study\n\nof Ghana, a country with a long tradition of gold mining and a recent, large expansion in capital\n\nintensive and industrial-scale production.\n\nA second contribution of this paper is to show the importance of decomposing the effects with\n\nrespect to distance from the mines. Given the spatial heterogeneity of the results, we explore\n\nthe effects in an individual-level, difference-in-differences analysis by using spatial lag models\n\nto allow for nonlinear effects with distance from mine. We also allow for spillovers across\n\ndistricts, in a district-level analysis. We use two complementary geocoded household data sets\n\nto analyze outcomes in Ghana: the Demographic and Health Survey (DHS) and the Ghana\n\nLiving Standard Survey (GLSS), which provide information on a wide range of welfare\n\noutcomes.", "output": {"entities": {"named_data": [{"text": "Demographic and Health Survey (DHS)"}], "descriptive_data": [{"text": "geocoded household data sets"}], "vague_data": []}}}
{"input": "IT specialists and executives), and 28% of Polish citizens. Their shares increased in the past two years by 3 pp. among Ukrainian refugees and pre-war Ukrainians, 2 pp. among other foreigners, and 1 pp.\namong Polish citizens – this data shows that though Ukrainian refugees may be largely employed in the less attractive occupational groups, they are also the fastest to progress toward more attractive professions. [11]\n\n**Ukrainian refugees in Poland have**\n\n**clearly improved their economic**\n\n**situation over the past year.** As\nindicated in chapter 1, the share of Ukrainian refugee household incomes derived from work in Poland has increased from 74% in the July-August 2023 MSNA survey to 76% in the May-June 2024 SEIS survey. [7] This is not surprising, as the situation of Ukrainians in the Polish labour market has clearly improved. First, employment rate of working-age refugees\n\n---\n[11] Since 2021, ZUS has been requesting information about the occupation of non-agricultural workers who first join the social insurance system (most farmers have a", "output": {"entities": {"named_data": [{"text": "July-August 2023 MSNA survey"}, {"text": "May-June 2024 SEIS survey"}, {"text": "SEIS survey"}, {"text": "MSNA survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "While Article 28 of the Asylum Law permits refugees also to engage in self-employment, the lack of legally\nrecognized refugee identity cards is likely to remain a major obstacle to meeting administrative requirements\nto open a business and pay the necessary tax.\n\nInformation on the number of refugees owning businesses is also lacking.\n\n**3.3** **Land, housing, and property rights**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Since the beginning of the Russian invasion, the number of Ukrainian workers covered by social security insurance in Poland increased by 126 thousand. The true increase of insured refugees however is larger.\nBy checking previous insurance status, ZUS identified 228 thousand newly registered insured persons active on 31st March 2023. [31] Considering the number of Ukrainians with active PESEL UKR at the time, this would yield an employment rate of 43%. As this number does not take into account jobs not covered by social insurance and informal work, this can align with the over 60% employment rate noted in the surveys. This number does not take into account over 500 thousand Ukrainians that were paying social security contributions before the beginning of the full-scale war and remained in Poland after its outbreak.\n\nThe refugees present in Poland, while not without difficulties, are largely able to provide for themselves and their families. As reported in the Deloitte", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Shock to labour supply was calibrated to match data of working Ukrainians presented in chapter 2. As we didn’t have data of number of unemployed refugees, we calibrated it that an increase in the number of workers due to an increase in labour supply matched employment data in two variants: lower (around 225 thou.) and higher employment (around 350 thou.).\nTotal increase in labour supply in Poland was balanced by equal decrease of labour supply in Eastern Europe.\n\nShock to propensity to save was calculated in two steps. First and foremost, it was assumed that due to their precarious life situation refugees won’t save any income.\nAs such shock was set to match shock for the population [54] . Additionally, to account for spending of savings from Ukraine, data from the National Bank of Ukraine on cash withdrawals and retail transactions from Ukrainian bank cards in Poland was used [55] and then calibrated to data for private consumption in Poland. Additionally, the same data was used to calibrate the negative shock to investment in Eastern Europe.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "National Bank of Ukraine"}, {"text": "retail transactions from Ukrainian bank cards"}, {"text": "data for private consumption"}, {"text": "data for private consumption in Poland"}], "vague_data": [{"text": "employment data"}]}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n## **4.** Ukrainian refugees’ skill-job mismatch\n\n##### The disparity between education levels and the jobs performed by Ukrainian refugees indicates their significant over-qualification in comparison to Polish citizens (4.1). Widespread occupational licensing presents an obstacle to efficient use of Ukrainian refugees’ human capital, who – in comparison to Polish citizens – rarely work in regulated professions (4.2). The higher the level of Polish language competence, the higher the wage premium. Older refugees, those who have been in Poland for a shorter period of time or have below tertiary education tend to have poorer language skills (4.3). Refugees who back in Ukraine managed the household or were not employed, remain underemployed in Poland (4.4). Key factors to enhancing the status of Ukrainian refugees in Poland will be language courses, including advanced levels tailored for professionals, easing of occupational licensing restrictions, particularly those based solely on citizenship, and implementation of active labour market policies to help specific groups enter the workforce (4.5).\n\n26", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "UNHCR facilitates voluntary repatriation for refugees and asylum seekers who request to return to\ntheir countries of origin, with arrangements often made in close cooperation with IOM through its\nAssisted Voluntary Return (AVR) program. During the course of 2023, 95 refugees voluntarily\nrepatriated from Indonesia, primarily to Sri Lanka and Iraq. Voluntary repatriation is impacted by\nongoing conflicts and human rights violations in countries of origin, which renders many unable to\nsafely return home and limits interest in repatriation.\n\nUNHCR / 1 November 2024 6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE (selling house or land, using degrading sources of income, taking on high-risk or illegal jobs) and crisis-level (reducing essential health and education expenditures, selling productive assets) coping strategies. This statistic is even worse for those that fall below the poverty line [8], standing at 10% and 18% respectively. Female-led households (where all adult members are female) report having to engage in harmful coping strategies more often than their male-led counterparts.\n\n**SHARE OF REFUGEE HOUSEHOLDS ADOPTING HARMFUL**\n\n**COPING STRATEGIES ABOVE AND BELOW THE POVERTY**\n\n**LINE, %** **[1]**\n\nAbove the poverty line Below the poverty line 10% 10% housing fully subsidized by the government (notably, in Slovakia this share stands at 81%). Eight percent are being hosted free of charge by locals.\nSeventeen percent pay for rent only partially for various reasons, such as living with extended family, partially subsidized by the host government or employer. Those that fully pay rent report this being their number one expense, constituting 40% of the total household budget.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In terms of economic impact, refugees are treated as a subset of all immigrants.\nEconomic literature typically categorises immigrants by their country of birth, regardless of their legal status. Although refugees seek new homes out of necessity rather than for economic opportunity, economic research focuses on their employment rates and other measures of labour market integration, which are usually lower than those of other immigrants and natives (Brell et al., 2020).\nIn this respect, Ukrainian refugees in Poland resemble other immigrants and natives more closely than usual.\n\nThis appendix outlines a revised **Deloitte**\n\n**D.Climate** general equilibrium modelling\nstrategy compared to the previous Deloitte (2024) report, accounting for the impact of Ukrainian refugees on productivity.\nOver the past two decades, research by academic economists has shown that viewing immigration solely through the lens of supply and demand severely constrains our understanding of the process (Peri, 2016). Such a model suggests that immigration increases economic output 36", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Refugees (2023) Refugees (2024) Hosts (2023) Overall Male Female With severe psychological distress With a disability Source: Survey data, SAG estimates 64% 67% 63% 57% 86% 96% 92% 72% 49% Technical or Bachelor's Master's Doctoral Vocational 30% Lower secondary or below Source: Survey data, SAG estimates\n\n**11**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "Survey data"}]}}}
{"input": "particularly when they are at risk of refoulement, arrest, and detention.\n\n### **Financial Assistance**\n\nUNHCR assists a small number of extremely vulnerable refugees and asylum seekers with cash support\nto help meet basic needs. Together with partners, UNHCR conducts a socio-economic assessment of\ncases that have been identified as requiring financial assistance. Those cases that have heightened\nneeds are presented to a Socio-Economic and Health Panel (comprised of YCWS, JRS, and UNHCR) for\na determination of inclusion in the cash program. Those who qualify receive up to six months of cash\nassistance, following which a re-assessment is required to determine continued needs.\n\n### **Economic Empowerment**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\n- Contribute \r to \r the \r CTFMR \r efforts \r in \r documenting, \r verifying, \r reporting \r and\nresponding \r to \r grave \r child \r rights \r violations, \r including \r recruiting \r and \r using\nchildren \r in \r armed \r conflict.\n\n- Conduct \r multi-­‐sector \r baseline \r assessments \r and \r identify \r proxy \r indicators \r for \r self-­‐\nreliance; \r establish \r monitoring \r and \r evaluation \r system \r in \r order \r to \r track \r progress\nmade \r on \r key \r indicators \r over \r the \r framework \r period.\n\n- Support \r and \r participate \r to \r multi-­‐sector \r need \r assessments \r and \r planning \r process,\nin \r particular \r in \r areas \r of \r current \r or \r potential \r return.\n\n- Provide \r an \r initial \r light \r rapid \r response \r to \r spontaneous \r IDP \r and \r refugee\nreturnees, \r identified \r through \r returnee \r monitoring, \r by \r providing \r NFIs \r and\nrelevant \r protection \r interventions \r on \r a \r needs \r basis, \r as \r well \r as \r community-­‐based\nassistance \r to \r receiving \r communities, \r with \r a \r view \r to \r building \r confidence \r in \r the\nreturn \r process.\n\n- Advocate \r with \r Government, \r donors \r and \r private \r sector \r in \r regard \r to \r rehabilitation\nof \r main \r roads \r to \r key \r potential \r returnee \r areas \r and \r establishment \r of \r facilities \r that\ncould \r eventually \r support \r an \r organised \r return.\n\n**10.2.** **Phase \r 2: \r Expansion \r of \r integrated \r support \r to \r spontaneous \r returnees**\n\n**and \r their \r communities**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Refugees are vulnerable and at risk of poor health outcomes due to disruptions in access to health care in their country of origin, experiences during their journey, and challenges in settling in a new country. For the Ukrainian refugee population, predominantly comprised of women, children and older persons, access to primary health care services, including mental health and psychosocial support, child health and nutrition, sexual and reproductive health, non-communicable diseases (NCDs), rehabilitation and health education to increase health literacy and empower health decision-making, is critical. Among older persons, NCDs are most prevalent, necessitating uninterrupted access to care for managing illnesses.\nCommunicable diseases are a concern as the movement of refugees in and out of host countries disrupts access to disease prevention, detection and treatment programmes, increasing the health risks.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**POPULATION PYRAMID**\n\nFemale Male 60+ years old 35-59 18-34 5-17 0-4 (N=19,803) 9% 25% 14% 13% 14% 3% 4% 9% 7% 3% In terms of other demographic characteristics, 6% of individuals self-reported a disability (1,435 individuals out of a sample of 18,679). Among the countries surveyed, Estonia, Hungary, and Poland reported the lowest percentage of refugees with disabilities at 5%, while Romania reported the highest at 12%.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "As per a recent assessment conducted in 21 Brazilian states, 15% of Venezuelan refugees and\nmigrants reported having suffered discrimination and stigmatization in the previous 12 months.\nOut of these, 80.4% were discriminated because of their nationality, 8.2% for their ethnicity, 5.2%\nfor their age, 3.5% for having a disability and 2.4% due to their sexual orientation and gender\nidentity. [9] On the other hand, according to the same source, 33% of indigenous Venezuelans\nexperienced discrimination and stigmatization, mainly due to their nationality (51.1%) but also for\ntheir ethnicity (31.9%), and to a smaller degree because of their age (6.3%). [10] This overlapping of\ndiscrimination causes not only affects the ability of these populations to access dignified\nlivelihoods, but also to exercise their fundamental rights, such as access to health and education.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "By refraining from any refugee dispersal policies, Poland and other EU Member States may have improved labour market inclusion. In many European countries refugees are geographically dispersed after arrival to spread the cost of hosting them, ease the stress on the housing market and public services, and to avoid creating ethnic enclaves. The effects, however, can be detrimental to labour market inclusion and may be contrary to other aims of the policy. Dispersal pushes at least some of the refugees into regions with weak labour markets and few co-nationals already settled, who otherwise could transmit important information about employment opportunities. Fasani, Frattini, and Minale (2022) conducted the first cross-country study of refugee dispersal policies.\nTheir LFS sample covers refugees who experienced dispersal policies in Finland, Germany, Ireland, Netherlands, Norway, Sweden, Switzerland and the UK (no data for Denmark). They find that non-EU15 refugees aged 25-64 who arrived when a dispersal policy was in place experience 4.5 percentage points lower employment rates than for those not exposed to such a policy. This may understate the effect, as for refugees who arrived 10 or less years before the survey, the effect is 17.5 percentage points, while it becomes statistically insignificant afterwards.\nFor the six countries for which data on residence is available, non-dispersed refugees show clearly stronger clustering in economically stronger regions (measured by GDP per capita).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "this tool. This meeting marked the first\n\nunder the leadership of the new cluster\n\ncoordinator.\n\nFor more information request the\n\nmeeting minutes for any cluster member.\n\n**12**\n\n**XVIII. Second Allocation for Ven-**\n\n**ezuela Humanitarian Fund (VHF)**\n\n**The call for proposals for the second**\n\n**allocation of the Venezuela Human-**\n\n**itarian Fund (VHF) was opened on**\n\n**October 13th closing on November**\n\n**6th.** This allocation focuses on \"Multisec\ntoral assistance for the improvement of\n\nessential health services, strengthening\n\ncommunity resilience through livelihood\n\nsupport, gender equality and women's\n\nempowerment, supporting emergency\n\neducation activities, and the provision\n\nof assistance and protection services\n\nin complementarity with CERF funds in\n\n13 municipalities across 5 border states:\n\nBolivar, Delta Amacuro, Falcon, Sucre,\n\nand Zulia.\" The three key prioritized\n\nareas encompass enhancing essential\n\nhealth services (Mental Health and Psy\nchosocial Support (MHPSS), Women's\n\nand Adolescents Health, and Sexual &\n\nducted in 16 states, with the collaborative\n\nefforts of 9 partner organizations. This tool\n\nprovides valuable insights into the evolving\n\nprotection landscape and aids in tailoring\n\nresponses to the specific needs of affected\n\npopulations.\n\n_© FPM/ Franco Chramosta (2023)_", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "of refugees from Ukraine find themselves of all refugee households income above of refugees are unemployed, which\n\n**below the poverty line** [4] based on the poverty line **comes from regular work** **starkly contrasts with just a 3%**\nreported income - this figure stands at 35% for households **unemployment rate for host country** below the poverty line **nationals**\n\n# 32% 56% 14%\n\nof refugees live below the poverty if is the labor force participation rate of of refugee youth is not engaged in\n\n**support with accommodation expenses** refugees from Ukraine, which is **on par** employment, education, or training, which\nis factored in as an indirect income source **with host country nationals** is **comparable to host country national** of all refugee households income above the poverty line **comes from regular work**\n\n- this figure stands at 35% for households\nbelow the poverty line is the labor force participation rate of refugees from Ukraine, which is **on par**\n\n**with host country nationals**\n\nof refugee youth is not engaged in employment, education, or training, which is **comparable to host country national**\n\n**statistics**\n\n---\n[4] Defined as 50% of the median equivalized income in the host country", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "### Call(s) to Action\n\nThe Brazilian state is commendably recognized for its efforts in providing protection to refugees\nand other forcibly displaced populations, in line with international, regional, and national legal\nframeworks. Brazil stands as a beacon of hope for refugees in the region, demonstrating exemplary\ncommitment and leadership in humanitarian response, and striving to go ensure the successful\nlocal integration of displaced individuals.\n\nUNHCR calls upon the international community to boost the support for Brazilian authorities by\nincreasing financial and technical assistance to UNHCR and other humanitarian actors. This\nsupport is crucial for sustaining and expanding Brazil’s protection and assistance programs,\nensuring the rights and needs of refugees and other forcibly displaced people are met, and Brazil’s\nexemplary efforts in this field are fully supported and sustained.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n**Refugee employment rates significantly improved in 2024, moving closer to national levels**\n\nUkrainian refugee employment rates [14] have experienced a sizeable increase from 2023 in most countries, rising by 9 percentage points year-over-year at the regional level to 64%. This indicator now stands just 7 percentage points below the equivalently weighted mean for the host population (71%).\n\nRefugee employment grew both owing to a decrease in unemployment, which declined to 9% from 13% last year, as well as new individuals coming into the labor force [15] . In fact, the 2024 labor force participation rate amounted to 70%, which stands almost in line with the equivalent host country indicator of 73%.\n\n**EVOLUTION OF THE REFUGEE EMPLOYMENT RATE FROM 2023 TO 2024**\n\n70% 60% 50% 40% 30% 20% 10% 0% Employment Decrease in Decrease in rate 2023 unemployment potential labor force Employment rate 2024 Unclear labor force status Expansion of the labor force Note: Only includes data from the 7 countries surveyed in both rounds (Bulgaria, Czech Republic, Hungary, Republic of Moldova, Poland, Romania, and Slovakia) Source: Survey data, SAG estimates", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "Survey data, SAG estimates"}], "vague_data": []}}}
{"input": "**in the literature is language training.**\nFoged et al. (2024) analysed labour market outcomes of language training, placement in strong labour markets, active labour market policies, cutting welfare benefits, and placement in co-ethnic networks that were directed at refugees in Denmark.\nThanks to unusually detailed Danish data, they could follow individual refugees who arrived in Denmark between 1987 and 2008, for at least 10 years, and in most cases for 15 years. They found intensive language training introduced in 1999 to be the most effective of all policies, accounting for a 5-6 pp. increase in the probability of employment and a USD 3,000 increase in annual earnings (2015 figures). While locating refugees in strong labour markets also had considerable positive effects, the report found only some evidence that Active Labour Market Policies (ALMPs) focused on matching refugees with deficit occupations improved their employment prospects and no evidence of positive effects of cutting benefits or placing refugees in co-ethnic networks. Heller and Mumma (2023) exploited randomized enrolment lotteries for a publicly-funded", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "Danish data"}], "vague_data": []}}}
{"input": "Source: Deloitte own elaboration based on GUS and ZUS data, as well as data for instrumental variables from Public Employment Services Portal and Open Data governmental portal. OLS is the standard Ordinary Least Squares model, IV are Instrumental Variables Two Stage Least Squares models with instrumental variables of the share of Ukrainian pupils in Polish schools, distribution of Ukrainians from declarations on entrusting work to a foreigner in Poland in 2019, or both. For details see the Online Technical Appendix.\n\nFurthermore, consistent with a positive productivity shock, Polish citizens have been moving to better-paid occupations – as predicted by the theory of occupational upgrading (e.g., Beerli and Peri, 2018; Foged and Peri, 2016; Peri and Sparber, 2009).\nDeloitte has acquired quarterly data on the occupational groups of Polish citizens who are insured with ZUS from Q1 2022 to Q2 2024. This data is not exhaustive as ZUS only began requiring such information in", "output": {"entities": {"named_data": [{"text": "GUS and ZUS data"}, {"text": "Public Employment Services Portal"}, {"text": "Open Data governmental portal"}, {"text": "GUS"}], "descriptive_data": [], "vague_data": []}}}
{"input": "In this scenario, 19% of Venezuelan households reported being at risk of evictions from rented\nhousing in the three months prior to their interview, with a higher incidence in Roraima (26%) and\nAmazonas (29%), the two states hosting the highest proportion of refugees and other forcibly\ndisplaced people in Brazil. As per the same study, 10% of the indigenous households surveyed\nwere evicted during the three months prior to the interview, which makes them almost five times\nmore likely to face actual eviction when compared to the total surveyed population (2%). [24] The\nrisk of eviction has been also systematically reported by refugees also of other nationalities,\nincluding Haitians, Colombians, and Cubans. [25]", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Data sources: UNHCR PRIMES, UNHCR Resettlement Statistics Report.   For more information or to contribute, please contact UNHCR RBSA DIMA (rsarbdima@unhc\n\n**1,729**\n\n**154**\n\n**57**\n\n**53**\n\n**34**\n\n**13**\n\n**12**\n\n**4**\n\n**3**\n\n**2**\n\n**COD**\n\n**BDI**\n\n**SOM**\n\n**RWA**\n\n**TUR**\n\n**ZAM**\n\n**ETH**\n\n**UGA**\n\n**ANG**\n\n**AFG**\n\n**COD**\n\n**BDI**\n\n**SOM**\n\n**RWA**\n\n**ETH**\n\n**PAK**\n\n**TUR**\n\n**CAR**\n\n**BOT**\n\n**ERT**\n\n**3,619**\n\n**263**\n\n**235**\n\n**220**\n\n**40**\n\n**36**\n\n**19**\n\n**14**\n\n**8**\n\n**8**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "### **Access to Territory**\n\nIn 2023 and 2024, boats carrying nearly 3,000 Rohingya refugees (the majority of whom are women\nand children) have landed in Aceh and North Sumatra, Indonesia. According to information provided\nto UNHCR by the new arrivals, the increase in the number of individuals undertaking the sea journey\nhas been driven by a number of factors, including increasing insecurity in the camps in Bangladesh; a\ndecrease in the cost of the sea journey; continued instability in Myanmar; and a lack of progress in\ncreating conditions that would enable return to Myanmar, including addressing the root causes of\nRohingya displacement.\n\nWhile many Indonesians remain supportive of and sympathetic to the challenges facing Rohingya\nrefugees, the most recent boat arrivals have met unprecedented resistance in Indonesia. Some boats\nwere initially prevented from disembarking, many refugees were forced to relocate several times due\nrejection from local communities, and many of those who have disembarked have yet to be allocated\nan adequate shelter by Indonesian authorities. As a result, hundreds of refugees who have\ndisembarked in recent months are currently living in extremely perilous, overcrowded, and\nsubstandard conditions in which the protection and assistance response remained a challenge.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland much of the heterogeneity inside of these groups. Every two years, GUS publishes information about the average wages in 128 occupational groups, with the latest data for October 2022 (GUS, 2024a).\nWhen ZUS data is aggregated into these occupational groups with the assumption that wage structure remains the same as in October 2022, the rate at which Ukrainian\n\n**The occupational progress of**\n\n**Ukrainian refugees as compared to the**\n\n**host population may be faster than**\n\n**the nine main occupational groups**\n\n**above suggest.** What is particularly\nstriking is the similar pace of progress of Ukrainian refugees and pre-war Ukrainians in the nine main occupational groups presented above. However, it conceals\n\n**Chart 12. Ukrainian refugee wages relative to Polish citizens in the same employee-cells**\nEmployee cells are divided by poviat, sex, age group, and main occupational group 20 2022 Q2 2024 Q2", "output": {"entities": {"named_data": [{"text": "ZUS data"}], "descriptive_data": [{"text": "ZUS data"}], "vague_data": []}}}
{"input": "work in mining, and insignificantly less in agriculture or service and sales. The likelihood that\n\na man works in mining increases by 11.3 to 12.6 percentage points, which is more than a 400\n\npercent increase in likelihood from the mean value which is 2.8%. For both men and women,\n\nthe results are indicative of changes in labor force participation on the extensive and intensive\n\nmargin. Fewer people work, as indicated by columns (1) and (2) (significant for men), but those\n\nwho work, work more hours than before (column 3, albeit insignificant). It should be noted that\n\nthe sample sizes are limited and these estimates may suffer from lack of power.\n\nAnnex figure 2 presents the results graphically and shows the spatial structure for a subset of\n\nthe variables. The likelihood of a woman working in services decreases with distance from\n\nmine, and log wages are higher within 10 to 20 km of an active mine. Men are, intuitively, more\n\nlikely to work as miners if they reside close to an active mine, and the correlation decreases\n\nwith distance. Wages for men are also higher close to active mines (panel D). Beyond 40 km,\n\nthe estimated effects are close to zero.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Indonesia is host to a relatively small number of refugees and asylum seekers, but they reside over a\nwide geographical area in a country of over 17,000 islands. While approximately half of the refugee\npopulation lives in Jakarta and the surrounding areas, the other half is spread throughout the\narchipelago. The UNHCR operation in Indonesia is a small one, both in terms of staffing and resources,\nand the distribution of refugees across this large territory, coupled with complex protection concerns\nand emergency boat arrivals, creates unique operational challenges. UNHCR continually strives to\nprioritize efforts and resources to be as impactful as possible in supporting refugees who are most in\nneed and in advancing a sustainable protection environment in the country.\n\nUNHCR / 1 November 2024 8", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The effects on child health are, however, not all positive. We note, particularly, a statistically\n\nsignificant decrease in weight-for-age, but the other two measures are also negative (panel B of\n\n22", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Individuals \r and \r families \r often \r have \r no \r means \r to \r retain \r legal \r services \r and \r are \r often\nunaware \r of \r their \r rights \r to \r seek \r legal \r remedies \r under \r Myanmar \r law. \r Services, \r security\nand \r the \r rule \r of \r law \r are \r weak, \r and \r effective \r protection \r and \r response \r mechanisms \r to\naddress \r sexual \r and \r gender-­‐based \r violence \r (SGBV) \r or \r the \r specific \r needs \r of \r extremely\nvulnerable \r individuals \r (EVIs), \r are \r still \r rudimentary \r with \r a \r lack \r of \r appropriate \r core\nmechanisms \r and \r services \r available.\n\nCases \r of \r arbitrary \r arrest \r and \r detention \r in \r Myanmar \r continue \r to \r be \r reported. \r Pervasive\nproblems \r with \r the \r rule \r of \r law \r in \r Myanmar \r are \r well \r documented \r and \r detention \r and\nprison \r conditions \r remain \r extremely \r problematic.\n\nIn \r addition, \r under \r the \r 1947 \r Immigration \r (Emergency \r Provisions) \r Act \r (as \r amended),\nillegal \r departure \r or \r entry \r is \r punishable \r by \r a \r fine \r or \r imprisonment \r of \r up \r to \r five \r years.\nUNHCR \r is \r not \r aware \r of \r any \r prosecutions \r brought \r under \r this \r law, \r and \r the \r President \r has\nalso \r stated \r publically \r that \r he \r welcomes \r back \r Myanmar \r people \r who \r ‘for \r various \r reasons’\nleft \r the \r country. \r However \r there \r have \r not \r been \r any \r changes \r or \r amnesties \r pronounced \r in\nrelation \r to \r this \r law, \r and \r this \r would \r therefore \r need \r to \r be \r addressed \r prior \r to \r any \r organised\nvoluntary \r repatriation \r of \r refugees.\n\n**2.3. \r Socio-­‐economic \r environment**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The \r health \r infrastructure \r in \r the \r South-­‐East \r remains \r substantially \r underserved \r with \r a\n\nCommittee. \r The \r Myanmar \r Peace \r Centre \r is \r tasked \r to \r provide \r policy \r advice \r and \r strategic \r guidance \r as \r well \r as\nco-­‐ordinating \r Government \r activities \r in \r the \r key \r areas \r of: \r cease-­‐fire \r negotiations \r and \r implementation; \r peace\nnegotiations \r and \r political \r dialogue; \r co-­‐ordination \r of \r assistance \r in \r conflict \r affected \r areas \r and \r outreach \r and\npublic \r diplomacy.\n\n4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "This paper is a product of the Office of the Chief Economist, Africa Region. It is part of a larger effort by the World\nBank to provide open access to its research and make a contribution to development policy discussions around the world.\nPolicy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be contacted\nat andreas.kotsadam@econ.uio.no, anja.tolonen@economics.gu.se, and pchuhan@worldbank.org.\n\n_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development_\n_issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the_\n_names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those_\n_of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and_\n_its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._\n\nProduced by the Research Support Team", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**02.** Firms recognise changes in the\nabundance of skills in the labour force resulting from immigration and adjust their production technologies accordingly. They thereby increase the productivity of these skill groups and themselves (Peri, 2016; Lewis and Peri, 2015; Lewis, 2013; Peri, 2012). This theory is called “ **directed technical**\n\n**change** ” by Acemoglu (2002). Firms\nadopt production technologies that favour skills that have become abundant (and thus cheaper) in the labour force. This increases their productivity and offsets the negative effects of competition between workers. In the late eighteenth and early nineteenth centuries, firms in English cities engaged in unskilled technical change in response to an influx of unskilled workers from the countryside and Ireland. In the postwar United States of the twentieth century, skilled technical change occurred as the proportion of collegeeducated workers grew rapidly.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Our results are consistent with the previous, similar studies. In estimating GDP impacts we take an approach that is most similar to the previous studies of the pre-2022 Ukrainian migrants by NBP economists (Gradzewicz, Jabłonowski, Sasiela, and Żółkiewski, 2021; Strzelecki, Growiec, and Wyszyński, 2022), but unlike the previous Oxford Economics and ours impact estimates of Ukrainian refugees (Urban, 2022; Deloitte, 2022) we do not allow for the possibility of a positive productivity shock, because there is little data to credibly estimate its size. Below, we summarise impacts yielded by these studies. As studies were done under different assumptions on the number of 41 Aggregate region in model consisting of Ukraine, Russia, Belarus, Moldova, Czechia, Slovakia, Hungary, Romania and Bulgaria.\n42 In other words it was assumed that money that would be spent e.g. through credit action for investments in Eastern Europe were spent for consumption in Poland.\n\n34 43 Data from forecast of Ministry of Finance from October 2023, [Wytyczne dotyczące wskaźników makroekonomicznych - Ministerstwo Finansów - Portal](https://www.gov.pl/web/finanse/wytyczne-sytuacja-makroekonomiczna)\n[Gov.pl (www.gov.pl).](https://www.gov.pl/web/finanse/wytyczne-sytuacja-makroekonomiczna)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "been of 33 % of the funding requested.\n\nAccording to the 345W reports, 478K\n\npeople were impacted until october, which\n\n65% are women and 35% men. 6,479\n\npeople with disabilities were reached\n\nduring the last period.\n\n**violence**\n\nThe states with the higher response\n\ninclude Tachira, Zulia, Bolivar, and\n\nMiranda. Some of the organizations with\n\nthe higher reach include ACNUR, DIOCE\nSIS SC, CODEHCIU, HIAS, ALIADAS EN\n\nCADENA A.C, TINTA VIOLETA and CAR\nITAS.\n\n**Figure 1. Summary of HRP 2022 - 2023 results, by Specific Objetive.**\n\n**Responding**\n\n**to protection**\n\n47% **risks associated** 45%\n\n**with violence of**\n\n**GbV**\n\n**children**\n\n# 47 4\n\n**Prevention,**\n\n**mitigation, and**\n\n13%\n\n# 13\n\n99%\n\n# 99\n\n**Figure 1. Summary of HRP 2022 - 2023 results, by Specific Objetive.**\n\n**Responding to**\n\n**protection risks**\n\n**associated with**\n\n47%\n\n# 47\n\n47%\n\n**Responding**\n\n**to protection**\n\n**risks associated**\n\n**with violence of**\n\n45%\n\n99%\n\n**Access to legal**\n\n**documentation***\n\n45%\n\n77% **Access to**\n\n**livelihoods**\n\n# 77\n\n**children**\n\n**Specialised**\n\n**protection services**\n\n_*Target does not consider birth certificates (EV-25)._\n\n77%\n\n**to people affected**\n\n**Access to** 13%\n\n**livelihoods**\n\n**response to**\n\n**protection risks**\n\n**by all forms of**\n\n36%\n\n36%\n\n# 3", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In order to compute refugee wages, household net employment income was divided by the total number of working hours reported by all employed members. This figure was then weighted by the total number of working hours and averaged overall all households within a given country (while also respecting poststratification weights). The result was then converted to a monthly wage assuming employment at 40 hours per week and 4.33 weeks in a month. For comparability with host population data, net wages were converted to their gross equivalent utilizing local tax regulations.\n\n# **Limitations**\n\nThe statistical significance of the SEIS results is limited by the non-probabilistic selection of respondents.\nMoreover, the use of convenience sampling likely led to a larger share of data being collected from more vulnerable households.\n\nThere was also a notably high non-response rate regarding questions related to income and expenditure, which likely resulted in non-response bias. The income module of the SEIS was also materially different from the one employed by the EU SILC and the Republic of Moldova’s Household Budget Survey, which may limit comparability of this data to that of host populations.", "output": {"entities": {"named_data": [{"text": "Republic of Moldova’s Household Budget Survey"}], "descriptive_data": [], "vague_data": [{"text": "host population data"}]}}}
{"input": "(1.805) (0.039) (0.054) (0.029) (0.021) (0.029) (0.021)\nActive 0.007 0.001 0.050** 0.034** -0.032 0.054** -0.023\n(1.012) (0.026) (0.024) (0.017) (0.021) (0.026) (0.022)\n\nObservations 9,790 9,790 12,226 12,216 12,227 12,227 12,227\nR-squared 0.128 0.180 0.453 0.148 0.208 0.171 0.095\nmean of dep var 0.407 14.84 0.565 0.652 0.151 0.732 11.6\n\n_Note:_ Robust standard errors clustered at the DHS cluster level in parentheses. All regressions control for year and\ndistrict fixed effects, urban dummy, age, and years of education. Active is active status of mine in the survey year.\n\n*** p<0.01, **p<0.05, *p<0.1. OLS = ordinary least squares.\n\nOverall, we estimated in table 8 that a household’s access to electricity decreased when a mine\n\nbecame active. This finding is surprising if we assume that electricity infrastructure is seldom\n\ndestroyed, so that with time, access has generally been increasing. [13]\n\nFigure A1 (Annex) further decomposes the effect, and panel Aa of the figure confirms that the\n\ncoefficient for electricity access is negative using the treatment distance 20 km. However, with\n\na treatment distance of 10 km, the effect is marginally positive and insignificant. If we use a", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Refugees are not legally permitted to work in Indonesia. UNHCR advocates for refugees to be given\naccess to livelihoods opportunities and works with partners to create community empowerment and\nself-reliance programs that benefit Indonesians and refugees. These programs include vocational\ntrainings and entrepreneurships that also promote economic development in Indonesia. At the first\nGlobal Refugee Forum (GRF) in December 2019, the Indonesian Government pledged support to\nrefugee productivity and empowerment activities. This commitment was confirmed in the second\nGlobal Refugee Forum in December 2023. In September 2023, the Ministry of Manpower issued a\nCircular Note allowing refugee participation in skills training programs at government training centers.\nThe Circular and GRF commitment serve as pivotal entry points to advance economic empowerment.\n\n### **Education**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**employed before their displacement.**\nIn the SEIS survey, employment rates among refugees aged 18-64 previously employed or self-employed in Ukraine, are 81% and 91% respectively. That is already very high and any further increase would be marginal. On the other hand, those who back in Ukraine managed the household have an employment rate in Poland of 38%. Even before becoming refugees, they would have required support to enter the workforce and now, in the host country, they would be likely to benefit from such help even more. Some of them may be discouraged by not having been able to find a job, others may be marginally attached workers who fell outside the labour force, but have some desire and ability to return to work.\n\n**Chart 25. Ukrainian refugees’ employment rate in the 18-64 age group by previous**\n\n**status in Ukraine**\n\n91% Household Others Studying Employed Self-employed responsibilities Source: Deloitte own elaboration based on SEIS UNHCR survey conducted in May and June 2024.", "output": {"entities": {"named_data": [{"text": "SEIS UNHCR survey"}, {"text": "SEIS survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# Glossary List of charts and tables\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n**GUS** - Główny Urząd Statystyczny, Polish statistical office, also known as Statistics Poland.\n\n**LFS** - Labour Force Survey, Eurostat labour market survey conducted by national statistical offices.\n\n**MSNA** - Multi-Sector Needs Assessment, a 2023 UNHCR survey of refugees from Ukraine.\n\n**PESEL/PESEL UKR** - Powszechny Elektroniczny System Ewidencji Ludności, Universal Electronic System for Registration of the Population.\nAn ID number of every Polish citizen. **PESEL UKR** is a version issued to Ukrainian citizens in connection with the armed conflict in the territory of that country.\n\n**Poviat** - a middle tier of sub-central government in Poland between voivodship (province) and gmina (commune) level.\n\n**Pre-war Ukrainian migrants** - persons who migrated from Ukraine, primarily for economic reasons, before the full-scale Russian\ninvasion of Ukraine in February 2022.\n\n**SEIS** - Socio-Economic Inclusion Survey, a 2024 UNHCR survey of refugees from Ukraine as a follow-up to MSNA from the year before.\n\n**Ukrainian refugees** - persons fleeing Ukraine after the full-scale Russian invasion in February 2022, covered by EU's Temporary\nProtection Directive.", "output": {"entities": {"named_data": [{"text": "Multi-Sector Needs Assessment"}, {"text": "Socio-Economic Inclusion Survey"}, {"text": "MSNA"}, {"text": "SEIS"}, {"text": "LFS"}], "descriptive_data": [{"text": "Labour Force Survey, Eurostat labour market survey"}], "vague_data": []}}}
{"input": "employment, and unemployment rate of natives or other immigrants, except an actual slight positive impact on the wages of native women.\nDespite our conservative approach, additional government tax revenues trump the costs of refugee-connected expenditure.\nA larger wage pool, higher private consumption, and influx of capital from abroad result in larger tax revenue. In total, the general government revenue increased by 1.05-1.45% in 2023. In monetary terms, this amounts to 10.1-13.7 billion PLN in 2022 and 14.7-19.9 billion PLN in 2023.\nIf estimates quoted by a government official [2] of public expenses on refugees of around 15 billion PLN in 2022 and 5 billion in 2023 are accurate, we can conclude that they were more than offset by the additional tax revenue. In the long term, refugees should increase yearly government revenue by around 0.85-1.3%.\n\n---\n[2] E.g. vice-president of Polish Development Found Bartosz Marczuk estimated it at around 16 billion PLN, but this estimation also included spending of NGOs", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The government quickly granted refugees from Ukraine access to the labour market, healthcare, and schooling, facilitating the process of inclusion described in Chapter 2. Considering their psychological stress and needs in terms of child and elderly care, refugees began entering the labour market surprisingly quickly – attaining an employment rate of 28% in May 2022 and 65% in November 2022 (NBP, 2023).\nBy 30th September 2023 more than 10 thousand ran their own businesses according to the administrative social security ZUS data. Based on the MultiSector Needs Assessment Poland 2023 survey conducted in July-August 2023, we calculate that 80% of the income of refugee households is derived from employment, with an additional 5% coming from remittances and 2% from Ukrainian pension benefits. In economic terms, refugees from Ukraine in Poland are not receivers of social services and charity, but primarily consumers, employees, and entrepreneurs.", "output": {"entities": {"named_data": [{"text": "MultiSector Needs Assessment Poland 2023"}], "descriptive_data": [{"text": "administrative social security ZUS data"}], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland © UNHCR / Anna Liminowicz Analysis of the impact of refugees from Ukraine on the economy of Poland Economists have advanced an array of channels through which immigration could be increasing productivity. Macro-level regressions demonstrate that immigration has a positive influence on productivity, but they are unable to identify the precise mechanisms behind these impacts.\nIn part this may stem from the fact, that immigrants and natives differ in important ways, which triggers complementary occupational upgrading of natives and investment in complementary production technologies by firms [15] . Immigrants often exhibit higher entrepreneurship rates from natives. [16] Furthermore, even when immigrants enter seemingly low productivity childcare, elderly care, and housekeeping services, this can allow highly educated and productive native women to increase their labour supply. [17]\n\n---\n[15] For example, found by Peri (2016), Lewis and Peri (2015), Lewis (2013), Peri (2012).\n[16] For example, found by Anelli, Basso, Ippedico, and Peri (2023), and OECD (2011).\n[17] For example, found by Furtado (2016, 2015).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Applying the same strategies to analyze child health and birth outcomes, we find both positive\n\nand negative effects of mining activity. Mining activity appears to marginally reduce the\n\nanthropometric status (short-term malnutrition) of children in mining districts, which could\n\npoint to less food security. These results are in sharp contrast to the improvements in birth\n\nattendance and the decrease in infant mortality observed in mining communities and mining\n\ndistricts. A child in a mining district born after a mine has become active has had more prenatal\n\nvisits and is less likely to die as an infant. This result is similar to what Benshaul-Tolonen\n\n(2019) finds for a larger sample of gold-producing countries in Africa. Despite substantial\n\nreductions in diarrheal diseases, the analysis highlights that migrant children are more likely to\n\nsuffer from diarrheal diseases. The effects on the migrant community should be interpreted with\n\ncare, however, since it may be that less-well-off people choose to migrate to mining\n\ncommunities and that the mine activities do not make them any less or better off. In addition,\n\nmine closure or downscaling could lead to deterioration in local employment conditions and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n### **Child health,** **vaccination and** **nutrition**\n\nTimely initiation of breastfeeding (within one hour of delivery) Exclusive breastfeeding under 6 months 0-23 153/274 57% months 0-5 15/38 37% months\n\n- Excluding Estonia, Hungary\n\nBreastfeeding practices for infants and young children directly influence their nutritional health during the first two years of life and play a crucial role in child survival. From the survey results, the proportion of children 0-23 months who had timely initiation of breastfeeding was 57% and the rate of exclusive breastfeeding for the first six months of life was 37% in the region. Data need to be interpreted with caution given the very low number of respondents.\n\nTwo doses of measles vaccine are recommended for optimal protection against measles; the survey assessed therefore first and second dose measles vaccination coverage in children aged 9 months to 5 years. In average, 83% of children received at least one measles vaccine, similar to results from 2023 when 84% of children had received at least one dose. Coverage was lowest in Romania with 71% where respondents reported also greater", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Substantial progress has been made by Brazil toward implementing the 2019 GRF pledges which\nfocused on the improvement of the asylum system and the provision of complementary forms of\nprotection, In 2023, the Government made 10 additional pledges at the GRF, covering the\nfollowing topics: improvement and facilitation of the right to family reunion; participation of\npeople in need of international protection in decision making and consultation processes; creation\nof resettlement and complementary pathways programs; strengthening of asylum systems and\nimprovement of refugee access to health, amongst others.\n\nIFC and UNHCR have been working together since 2018 to create innovative solutions to\novercome the challenges faced by refugees and migrants in Brazil. The two organizations sought\nto explore potential ways to engage the private sector in providing solutions with a primary focus\non employment, affordable housing and financial inclusion. IFC and UNHCR, in partnership with\nthe Brazilian Banking Association (FEBRABAN) and the Brazilian Central Bank, prepared a guide\nto inform financial institutions about the profiles and specific documentation of refugees and\nmigrants and their financial needs.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The approach to data collection in each of the countries included in the report differed depending on the availability of sampling frames and information on the distribution of the refugee population by geographic area and accommodation type. All interviews were conducted face to face. As a probabilistic selection of respondents could not be ensured, the primary goal was to collect a diverse sample that would reflect the population’s composition as closely as possible.\n\nFor the regional analysis, weights were applied based on the most up-to-date estimates of the number of refugees staying in each country. This allowed calculated indicators to more accurately represent the broader refugee population across the region.\n\nAppropriate measures were implemented to ensure the protection of personal data and to guarantee confidentiality in all data collection and processing activities. Consent was requested and recorded for all selected participants, providing clear information on the purpose, and expected use of the data.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Table 1.** Ukrainian employment rate in EU.\n\n**Employment rate** **Main sectors of employment** **Date** **Source**\n\n**Source:** Deloitte elaboration based on the aggregation in OECD International Migration Outlook 2023. The calculation methods of employment\nrates vary between the countries, the results for Poland, the United Kingdom, Czech Republic and Italy are based on surveys. Additionally, the different statistical offices and organisations may use different employment and working age definitions.\n\nCurrently, DIW Berlin data shows that the employment of refugees from Ukraine is much lower in Germany, although many aspire to find employment. In a weekly report from 12th July 2023 the German Institute for Economic Research (DIW Berlin), a survey conducted in the first quarter of 2023 finds that only 18% of working age refugees were employed (Kollman, 2023). Among the non-employed, however, as many as 93% declare willingness to begin working, of which 71% as soon as possible or within a year.\nImportantly, many refugees are currently attending language courses in Germany", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "DIW Berlin data"}], "vague_data": []}}}
{"input": "The \r number \r of \r UN \r organisations \r and \r international \r and \r national \r NGOs \r as \r well \r as \r the\nscale \r of \r humanitarian \r and \r development \r activities \r in \r the \r South-­‐East \r are \r currently\nexpanding. \r At \r present \r UNHCR \r is \r reviewing, \r together \r with \r partners, \r how \r leadership \r and\nco-­‐ordination \r in \r support \r of \r durable \r solutions \r in \r the \r South-­‐East \r can \r be \r strengthened \r and\ncentred \r around \r a \r shared \r vision \r and \r strategy \r located \r within \r a \r broader \r protection\nframework \r incorporating \r key \r standards. \r UNHCR, \r in \r accordance \r with \r its \r mandate\nobligations, \r will \r play \r an \r active \r role \r in \r this \r process \r and \r in \r enhancing \r inter-­‐agency \r co-­‐\nordination \r on \r durable \r solutions \r at \r regional \r and \r State/Region \r levels.\n\nOne \r mechanism \r might \r be \r the \r establishment \r of \r a \r Working \r Group \r on \r Durable \r Solutions\nfor \r IDPs \r and \r Refugees \r to \r serve \r as \r a \r platform \r to \r co-­‐ordinate \r durable \r solutions \r related\nactivities \r from \r the \r preparatory \r phase. \r The \r working \r group \r could \r be \r co-­‐led \r by\nrepresentatives \r from \r the \r Government \r and \r UNHCR, \r and \r might \r consist \r of \r relevant \r UN\nagencies, \r NGOs, \r donors, \r civil \r society \r and \r representatives \r of \r parties \r involved \r in \r the \r peace\nprocess. \r In \r cease-­‐fire \r areas, \r all \r activities \r will \r have \r to \r be \r undertaken \r in \r close \r consultation\nwith \r non-­‐state \r armed \r groups \r operating \r in \r those \r areas.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "natives and this gap was largest for men, workers in the highest education level, and nonnaturalized immigrants. This has an important impact on wages, because, as showed in a seminal work by Kleiner and Krueger (2013) and confirmed in several analyses, working in a regulated profession comes with a significant wage premium.\nBrücker et al. (2021), who analysed German data, found that occupational recognition led to full convergence of immigrants’ earnings to those of their native counterparts. Tani (2020) found that in Australia, licensing raised hourly value to the economy. This estimate may underestimate the potential benefits, as the boost in productivity would most likely rise not just employee wages, but employer profits as well. Conversely, the overall impact on wages might be lower, if increased worker competition reduced the average individual premium.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "German data"}], "vague_data": []}}}
{"input": "the refugee inflow. Before the refugee influx, the share of companies reporting vacancies in the quarterly NBP survey stood at 49% in Q4 2021 – the highest level on record. This helps to explain the relative ease of the refugees' labour market inclusion in terms of employment rates.\nAfter refugee inflow, the share of firms reporting vacancies stopped growing and declined slightly to 45% in Q3 2023. This partly indicates the fact that many refugees entered the labour market, and partly a cyclical economic slowdown. Despite that, the labour market remains relatively strong.\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Chart 9.** Change in the number of workers registered for social security with Ukrainian citizenship by NACE sector between end of Q3\n2023 and 2021 Thousands Manufacturing Accommodation and food service activities Wholesale and retail trade; repair of motor vehicles and motorcycles Human heatlh and social work activities Administrative and support service activities Education Information and communication Professional, scientific and technical activities Public administration and defense; compulsory social security Construction Financial and insurance activities Agriculture, forestry and fishing Real estate activities Water supply: sewerage, waste management and remediation activities", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "quarterly NBP survey"}], "vague_data": []}}}
{"input": "The number of workers with Ukrainian citizenship since the beginning of the full-scale war in Ukraine grew in all NACE [21] sectors apart from transportation and storage. Since 2021, just before the escalation of war in 2022 in Ukraine, the number of workers with Ukrainian citizenship and social security insurance grew the most in manufacturing (almost by 34 thousand), accommodation and food\n\n**Source:** Deloitte own elaboration based on estimated data from [https://nbp.pl/publikacje/cykliczne-materialy-analityczne-nbp/](https://nbp.pl/publikacje/cykliczne-materialy-analityczne-nbp/szybki-monitoring/) 21  Statistical Classification of Economic Activities in the European Community (French Nomenclature statistique des Activités économiques dans la\n[szybki-monitoring/](https://nbp.pl/publikacje/cykliczne-materialy-analityczne-nbp/szybki-monitoring/) Communauté Européenne).\n\n18 19", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "3. Economic Opportunities\n\nIn accordance with Article 28 of the 2020 Asylum Law, the restrictions on the employment of foreigners,\nincluding the prerequisite of obtaining a work permit, should be considered not applicable to refugees.\nHowever, Decree No. 96-189 PR/MFPT, still requiring approval from the National Office for Employment\nProtection (ONAPE) for the employment of foreigners, remains silent on refugees. In addition, the decree\nstipulates that, before submission to ONAPE, contracts for foreigners must receive endorsement from\nimmigration authorities. It is unclear whether refugees should be exempted from this endorsement from\nImmigration Department.\n\nFurthermore, Article 11 of the 1996 Decree, which prohibits hiring foreigners for non-specialized jobs, may still\napply for refugees. Companies hiring foreigners are still obligated to pay fees ranging from FCFA 100,000\nto FCFA 250,000, and it is unclear whether these fees will also apply to refugees. The 2023 Asylum Decree\nhas not clarified the type of exemption of restrictive measures for foreigner employment that should benefit\nto refugees.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "##### **September/ October 2023 report**\n\n###### Venezuela\n\n**XII. Focal Group Discussions**\n\n**with LGBTIQ+ Organizations for**\n\n**Thematic Protection Analysis**\n\n**Update (PAU)**\n\n**In view of the preparation of a the-**\n\n**matic Protection Analysis Update**\n\n**(PAU) on the protection situation of**\n\n**LGBTQI+ persons, as part of the PC’s**\n\n**reporting efforts, with support from**\n\n**the Areas of Responsibility (AoRs)**\n\n**and the GenCap Gender Advisor,**\n\na hybrid focus group discussion was\n\norganized with LGBTIQ+ organizations\n\nand relevant actors on September 7th,\n\ncombining face-to-face and remote par\nticipation.\n\nThe focal group aimed to collect infor\nmation from key informants on the\n\nhumanitarian needs and protection\n\nrisks of LGBTIQ+ people, with a focus\n\non changes perceived in the last year.\n\n**10**\n\nThis information supported the drafting\n\nof the document that outlines the current\n\ncontext, main protection risks, affected\n\ngroups by geographical areas, and key\n\nrecommendations for humanitarian\n\nactors, government entities, donors, and\n\ncivil society organizations in Venezu\nela. The report's analytical conclusions\n\naim to provide an evidence base for\n\nprogramming, advocacy, and dialogue\n\nto influence behaviors and policies,\n\nfostering a more favorable protection\n\nenvironment.\n\n**XIII. Mental Health and Psychoso-**\n\n**cial Support (MHPSS) Coaching**\n\n**and Training of Trainers (ToT)**\n\n**The PC through the Protection Assis-**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**more productive.** Firms adjust their production technologies\nto the skill-mix prevalent in the economy, e.g., to the growing number of labour force with tertiary education (Acemoglu, 2002). Similarly, when immigrants arrive and make certain skills more prevalent in the labour force, firms adjust thus making the whole skill-group more productive and countervailing downward pressure on its wages, and possibly increasing overall efficiency (Peri, 2016). This is the mechanism found by previously described seminal paper by Peri (2012), in which immigration caused low-skill-biased technical change and increased productivity. An inflow of low-skilled immigrants can cause firms to adapt labour-intensive technologies or postpone automation, while expanding research and development departments in case of high-skilled immigrants (Lewis and Peri, 2015; Lewis, 2013).\n\n**Immigrants tend to have higher rates of entrepreneurship**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE\n\n**SHARE OF HOUSEHOLDS BELOW THE POVERTY LINE BY**\n\n**GENDER OF ADULTS, %**\n\nFemale with children Mixed without children Female without children Mixed with children Male without children 56% 48% 40% 37% 32% Female-led households with children also demonstrate a significantly higher poverty rate, standing at 56%, than their mixed-gender [18] counterparts (37%). This pattern does not hold true for mixed households without children, likely due to the significantly higher median age of adults in this cohort with 53 years vs. a maximum of 45 for the other groups.\n\nCompared with their initial months in the host country, 42% of female-led households report a decrease in their ability to afford goods and services. This is the highest share among all gender groups.\n\n---\n[18] With both adult males and females present", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# **4.** Unaccounted positive externalities\n\n##### Macroeconomic modelling underestimates the positive economic impacts of immigration, compared to econometric estimates.\n\n**Analysis of the impact of refugees from Ukraine on the economy of Poland**\n\n**Immigration's impact on productivity**\n\n**•** Jaumotte et al. (2016) in an IMF taskforce report examine economic impacts of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The cost of care and language are still barriers among those seeking care, and regionally, when compared to 2023, the proportion of those who reported experiencing cost barriers has increased, while it has not changed for language barriers. In Romania where unmet needs are the highest, cost and language barriers were the most reported barriers after long waiting times. In Hungary, language is the most reported barrier (53%).\n\nWhile the primary barrier to accessing healthcare reported by both women and men was long wait times, women reported unaffordable transport costs (25%) and hospital fees (21%) as their next most significant barriers. In contrast, men reported language difficulties (22%) and the inability to make an appointment (22%) as their top barriers after long wait times.\n\n**BARRIERS TO ACCESSING HEALTH CARE**\n\n2023 2024 Long waiting times* Could not afford transport Unable make appt Could not afford hospital Language barrier Could not afford clinic fee Lack of knowledge Lack health insurance Do not trust local provider Spec med treatment serv unavailable Refused to provide care (2023 N=1071, 2024 N=1,040)\n\n- Included under Others in 2023 (Total Others 2023: 5%)\n\n**13**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "fastgini [15] in STATA). We do this for both the cluster and district level. None of the effects of\n\nmining are statistically significant, but they point to increased asset wealth.\n\n**Table 9 OLS estimates for wealth and inequality in the DHS individual-level analysis**\n\nWealth Gini\n\nwealth cluster district\nindex level level\n\nactive*mine 7,290 -0.004 0.004\n(12,849) (0.013) (0.018)\n\nmine 9,922 0.011 0.006\n(8,676) (0.013) (0.016)\n\nactive 7,854 -0.006 0.034**\n(9,016) (0.010) (0.017)\n\nObservations 4,909 4,909 4,909\n\nR-squared 0.613 0.227 0.548\n\n_Note:_ Robust standard errors clustered at the DHS cluster level in parentheses. All regressions control for year and\ndistrict fixed effects, urban dummy, age, and years of education. Active is active status of mine in the survey year.\n\n*** p<0.01, **p<0.05, *p<0.1. OLS = ordinary least squares.\n\n**6.4 Bottom 40% of the population**\n\nTo understand the welfare effects of the bottom 40 percent of the population in the income\n\nscale, we split the sample according to the wealth score provided by DHS. Given the data\n\nstructure, which is repeated cross-section, we cannot follow a particular household that was\n\nidentified as belonging to the bottom 40 percent in the initial time period. Instead, we identify\n\n---\n[15] Fastgini is a user-written command in STATA that helps calculate the gini coefficient.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "wealth score provided by DHS"}], "vague_data": []}}}
{"input": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE\n\n### **Background**\n\nOver two years have elapsed since the start of the full-scale war in Ukraine leading to a protracted displacement and a humanitarian crisis. The response by the refugee-hosting countries continues to be overall characterized by a spirit of welcomeness and generosity and much has been done to make ensure that those fleeing the war are able to meet basic needs and have access to accommodation, healthcare, education, social assistance, and employment. Despite these efforts, the situation remains a source of deep concern, necessitating a continued and coordinated humanitarian response at the regional level.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**There are substantial barriers for**\n\n**those seeking entry into the teaching**\n\n**profession.** There are three career stages\nfor teachers working in Polish schools: teacher trainee, appointed teacher, and chartered teacher. Three-quarters of teachers in the 2023/2024 school year fell into the last two categories (GUS, 2024). However, to become promoted to an appointed or chartered teacher, a foreigner must possess Polish, EU, Swiss, or other EEA citizenship (Babakova et al., 2024). In effect, only 0.4% of Ukrainian refugees were teachers (ZUS-registered in mid-2024) compared to 2.2% of Polish citizens. There were more teachers’ assistants, who are not regulated, than actual teachers. Furthermore, the data presented in chapter 2 shows that the median net wages of Ukrainian refugees in the teaching profession are just PLN 3,500, constituting 66% of what the host population earns, the lowest earnings of all sectors.\n\n**Occupational licensing rules regarding**\n\n**citizenship have been relaxed for**\n\n**medical professions in the wake of**\n\n**the COVID-19 pandemic in 2020 and in**\n\n**February 2022, but those were often**\n\n**makeshift arrangements.** According to\nthe Babakova et al. (2024) report, during the COVID-19 pandemic, practicing medical professionals from Ukraine were allowed\n\n#### **4.3 Language wage premium**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland © UNHCR / Anna Liminowicz\n\n**Compared to Polish citizens, Ukrainian**\n\n**refugees rarely work in regulated**\n\n**professions** –3.6% of those insured at\nZUS compared to 10.6% of Polish citizens, as of mid-2024. This percentage was higher among pre-war Ukrainian migrants and other foreigners, because of a large share of truck and bus drivers. Overall, Ukrainian refugees are less likely to work in major regulated professions compared to Polish citizens. Among Ukrainian refugees, 0.7% work as truck or bus drivers, much less than among other migrants (4.7% prewar Ukrainians and 6.2% other migrants) or Polish citizens (2.3%). This may be partly attributed to a higher share of women among Ukrainian refugees. An exception is the taxi driving profession, which has lower entry barriers, offers flexibility and has a large share of migrants.\n\nDue to citizenship requirements, the difference is more clearly regulatorydriven in the case of teachers (school and preschool), who account for just 0.4% of Ukrainian refugees and even less of other migrants, but 2.2% of Polish citizens. In recent years, medical 30 Analysis of the impact of refugees from Ukraine on the economy of Poland", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\nhumanitarian \r mine \r action \r programme \r with \r local \r and \r international \r humanitarian\nagencies. \r Despite \r these \r positive \r developments \r there \r are \r still \r no \r activities \r related \r to\nsurvey \r and \r clearance, \r marking, \r or \r fencing \r being \r undertaken. \r Mine \r risk \r education\nprogrammes \r and \r assistance \r to \r mine \r victims \r remain \r still \r limited \r in \r scope.\n\nLand \r registration \r documents \r are \r held \r by \r township \r authorities \r in \r Myanmar. \r Land \r tenure\ndocuments \r and \r deeds \r are \r not \r always \r recorded \r or \r respected \r and \r there \r are \r frequent\nreports \r of \r land \r expropriation \r (or \r “land \r grabbing”) \r by \r the \r Government, \r the \r Myanmar\nArmy, \r non-­‐state \r armed \r groups, \r and \r private \r companies, \r often \r resulting \r in \r internal\ndisplacement \r without \r appropriate \r guarantees \r of \r compensation. \r Although \r the \r reforms\nintroduced \r by \r the \r Government \r in \r 2008 \r provide \r some \r additional \r security \r of \r land \r tenure,\nthey \r still \r fail \r to \r adequately \r recognise \r widely \r used \r customary \r rights.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\n- Contribute \r towards \r a \r comprehensive \r livelihood \r support \r programme. \r As \r per\nlocal \r needs \r and \r opportunities, \r this \r may \r include \r skills \r and \r employment\npromotion; \r support \r to \r productive \r assets \r and \r community \r infrastructure;\nenterprise \r development; \r microfinance \r promotion.\n\n- Ensure \r the \r provision \r of \r mine \r risk \r education \r before \r return \r and \r upon \r arrival,\nensure \r the \r prioritization \r of \r mine \r marking \r of \r contaminated \r areas \r in \r areas \r of\nreturn \r and \r advocate \r and \r support, \r if \r required, \r punctual \r clearance \r of \r critical \r areas\nsuch \r as \r access \r roads \r to \r basic \r services \r (schools, \r hospitals, \r etc).\n\n- Capitalize \r on \r the \r experience \r and \r expertise \r developed \r by \r committees \r in \r the\ncamps, \r such \r as \r the \r GBV \r committees, \r and \r re-­‐mobilize \r their \r members \r in \r places \r of\nreturn \r to \r strengthen \r prevention \r and \r response \r networks.\n\n**10.4.** **Phase \r 4: \r Consolidation \r of \r reintegration \r operations**\n\nUNHCR \r will \r facilitate \r and \r support \r the \r reintegration \r process \r increasingly \r involving\nspecialized development organisations implementing long-­‐term area-­‐based\nprogrammes \r in \r support \r to \r the \r Government \r and \r in \r the \r framework \r of \r national\ndevelopment \r plans, \r ensuring \r appropriate \r delegation \r and \r follow \r up \r on \r commitments.\n\n**10.5.** **Phase \r 5: \r Reintegration \r operations \r are \r scaled \r down \r and \r phased \r out**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Total Population**\n\n**11,735 Individuals**\n\n**(6,548 Cases)**\n\n**Vulnerabilities***\n\nUnaccompanied or\n\nseparated child\n\nWoman at risk\n\nSingle parent\n\nChild at Risk\n\nDisability\n\nChronic Illness\n\n**136**\n\n_*One individual may have multiple specific needs_\n\n**2,288**\n\n2020 2021 2022 2023 2024\n\n_*Pre-registration data refers to a headcount upon arrival or at disembarkation sites. Some individuals departed prior to registration with UNHCR._\n\nUNHCR / 1 November 2024 3", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "Pre-registration data"}]}}}
{"input": "_Figure 4: Labor force participation by gender as a percentage of working age population across 2019 and 2024_\n\n_Source: 2019 Shona socioeconomic survey_ [[8]] _and the authors’ calculation of 2024 survey data._\n\n**Household income**\n\n**Income from business is the primary source of livelihood for the Shona community, followed by wages and other**\n\n**minor sources.** 73 percent of household income in the Shona community comes from business activities like\n\ncarpentry, weaving baskets and hawking on the streets, indicating a strong reliance on entrepreneurship and self\nemployment. Wages from employment and daily labor activities constitute 25 percent of the income, while other\n\nsources like asset earnings or assistance contribute a mere total of 2 percent, showing limited diversification in\n\nincome streams. This heavy dependence on business shows that the Shona community still relies on their traditional\n\nincome sources and suggests that the community might face heightened vulnerability to market fluctuations and\n\neconomic shocks affecting their businesses.\n\n**A majority of households report that their income has remained stable since gaining citizenship, but a notable**\n\n**proportion has experienced an increase.** Half of the households indicated their income stayed the same, while 38", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE The survey also reviewed household coping mechanisms where households had insufficient funds to meet all basic needs. While more than a third of respondents reported spending their savings to meet basic needs, reducing essential health expenditures (including medicines) was the second most common coping mechanisms and used by 13% of the respondents.\n\nThis coping strategy is reported highest in Romania (36%), Hungary (23%), and Bulgaria (18%). Notably, in these countries, cost of care was the second most reported barrier to accessing care after long waiting times. Delaying care has negative implications on the health of individuals, including poorer health outcomes and an increased burden on health systems dealing with more complex and chronic conditions.\n\n**% OF HOUSEHOLDS WHO USED COPING MECHANISMS**\n\n**DUE TO LACK OF FUNDS IN THE LAST 30 DAYS**\n\n### **Reasons for visiting** **Ukraine**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The results are in line with the**\n\n**optimistic scenario from the**\n\n**previous Deloitte (2024) report.** The\ncurrent report is different from the one from 2024 in that we account for the positive productivity shock reflected in the labour market data, which further\n\n**The impact of Ukrainian refugees**\n\n**on the Polish economy is estimated**\n\n**with the Deloitte D.Climate general**\n\n**equilibrium model** **[18]** **in a modelling**\n\n**scenario that includes a productivity**\n\n**shock to account for the positive**\n\n**productivity impacts of migrants.**\nIn the model a marginal productivity of labour shock of a 1.5-2% dependent on the year is set, as to zero out the impact of Ukrainian refugees on the unemployment rate in the economy. This is in line with the lack of negative impacts of Ukrainian refugees on the Polish labour market in our econometric modelling, and empirical literature on productivity 17 For the literature review, underlying empirical evidence, and model calibration refer to the appendix on modelling strategy.\n\n18 Details on Deloitte D.Climate model calibration are outlined in the Appendix on modelling strategy, while further details on this CGE- class (Computable General Equilibrium) model are available in the Online Technical Appendix.\n\n22", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "labour market data"}]}}}
{"input": "(5) Total annual regionally adjusted household expenditure (local currency, regionally deflated).\n(6) Total food expenditure (nondeflated).\n(7) Total housing expenditure (nondeflated).\n(8) Total health and education expenditure (nondeflated).\n(9) Total household energy expenditure (gas and electricity) (nondeflated).\n\n*** p<0.01, **p<0.05, *p<0.1. All regressions control for year and district fixed effects, urban dummy, age, and\nyears of education.\n\n**7. Robustness for district-level estimations**\n\n**7.2 Using production levels**\n\nWe continue by exploring the effects of mining intensity as proxied by district-level production\n\nvolumes. The estimation will be similar to equation (2), but we replace the indicator variable\n\nfor being an active mining district with annual gold production in the district:\n\n𝑌���        - 𝛽�𝑔𝑜𝑙𝑑_𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛��        - ∝�� 𝑔� �𝜆𝑋�� �𝜀���      �4�\n\nThe measure of gold production is in 10 tons of gold produced, and 𝑔𝑜𝑙𝑑_𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛�� is\n\neither _gold_year_district_, which equals the total production of all mines in a district in the\n\ndifferent survey years, or _gold_period_district_, which equals total production for the years\n\nbefore the survey. For the 1993 survey, the period is 1990–93, for 1998 it is 1994–98, and so\n\non.\n\nUsing production levels instead of an indicator of having any production in the district has the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The primary needs identified within the Shona community include access to affordable housing, better integration\n\ninto the labor market, financial support for business development, and political representation. External support in\n\nthese areas, such as land allocation advocacy, education and skills training programs, and inclusion in national safety\n\nprograms, is essential for providing a foundation for sustained community growth and prosperity. Partnerships with\n\ngovernment agencies, NGOs, and international organizations could be instrumental in addressing these needs,\n\nensuring that the Shona community has the necessary resources and support to thrive in a post-citizenship era.\n\n## **Nationality as a tool for development**\n\n**Inclusive national identification systems are recognized as key enablers for development.** Allowing people to\n\nestablish and verify their identity is often a prerequisite for access to services and economic opportunities and\n\nexercising a range of rights, such as property ownership and public participation. For governments and businesses,\n\n**[www.unhcr.org](http://www.unhcr.org/)** 9", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Even with the increase in unemployment and lower real wages, an increase in labour force means a higher wage pool, which means higher tax income.\n\nMoreover, boosts in private consumption both due to increase in population as well as higher average spending rates means that refugees increased state income from taxation on consumption.\nThese effects will be strengthened by influx of capital from abroad. In total it is estimated that this increased the total income of the general government sector by 0.8-1.1% in 2022 and 1.05-1.45% in 2023.\nFinancially this respectively amounts to 10.1-13.7 billion PLN in 2022 and 14.7-19.9 billion PLN in 2023. Comparing this to government expenses on refugees (where although there are no accurate data about government spending on refugees, estimates quoted by a government official put it around 15 billion PLN in 2022 and around 5 billion in 2023 [46] ) we can conclude that the additional income from taxation more than offset the additional expenses [47] that were needed to accommodate them.\nIn the long term, refugees should increase yearly general government revenue by around 0.85-1.3%.\n\n---\n[47] Excluding spending of private households estimated as further 10 billion PLN.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "##### **September/ October 2023 report**\n\n### **MONITORING THE PROTECTION RESPONSE**\n\n###### Venezuela\n\n### **PERFORMANCE AND FUNDING**\n\nThe PC continues to reinforce the impor\ntance of reporting, which allows it to\n\ntrack funding and conduct advocacy.\n\nThroughout the last years the number of\n\npartners that regularly report 5Ws (cur\nrenly 345ws), including the implementing\n\npartners of the lead agencies of the Clus\nter and AoRs, increased notoriously.\n\nThe activity monitoring dashboard co\nvering latest data collection in October\n\n2023 and other information products\n\n[can be accessed in the protection clus-](https://app.powerbi.com/view?r=eyJrIjoiYzg3NGFkM2EtYjZhMS00YWNkLWE1NjItMjg0OThlMTAzMDM1IiwidCI6ImU1YzM3OTgxLTY2NjQtNDEzNC04YTBjLTY1NDNkMmFmODBiZSIsImMiOjh9)\n\n[ter website, and currently 105 partners](https://app.powerbi.com/view?r=eyJrIjoiYzg3NGFkM2EtYjZhMS00YWNkLWE1NjItMjg0OThlMTAzMDM1IiwidCI6ImU1YzM3OTgxLTY2NjQtNDEzNC04YTBjLTY1NDNkMmFmODBiZSIsImMiOjh9)\n\nare supporting the 345W reports. Please\n\nnote the list of Specific Objectives in\n\nFigure 1 are aligned to the HRP 2022.\n\nThe percentage (%) in each chart (see\n\nfigure 1) represent the number of benefi\nciaries (individuals) reached against the\n\ntarget set in the HRP 2022 - 2023.\n\n**14**\n\n353, 037 million USD were received\n\nby the Venezuelan Republic so far in\n\n2023 through the HRP plan, accord\ning to the Financial Tracking Service\n\n(FTS). Requested funding for the Protec\ntion Cluster was 101.2 million USD and\n\n33,385,8929 million USD were granted.\n\nAccording to FTS, the total coverage has", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "malnutrition), and weight-for-height (underweight) show that the children living in mining\n\ncommunities before the mine started operating have the lowest scores of all four groups. The\n\noutcomes seem to improve with mining, although not enough to offset the initial adverse\n\nsituation.\n\nTo test for exogeneity, we run regressions using baseline individual-level data to explore\n\nchanges in observable characteristics among women (the main part of the sample). Table 3\n\nshows that there are no significant effects of the mine opening on the age structure, migration\n\nhistory, marital status, fertility, or education, using the difference-in-difference specification\n\nwith a full set of controls. If anything, it seems that women in active mining communities are\n\nmarginally older, more likely to never have moved, and more likely to be or have been in a\n\ncohabiting relationship or married. Given the women’s slightly higher age, it is not surprising\n\nto find that they have higher fertility and lower schooling (assuming that schooling has\n\nincreased over time in Ghana). All these estimates are, however, insignificant.\n\n**Table 3 Observable characteristics in the DHS individual data**\n\nnon- ever currently ever total any schooling\n\n16", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n# Executive summary\n\nThe war in Ukraine, now in its third year, continues to have devastating effects on the Ukrainian population, triggering one of the largest displacement crises in Europe since World War II. As of December 2024, over 6.2 million Ukrainian refugees have been recorded across Europe, the majority of whom are women, children, and older persons. The European Union extended the Temporary Protection Directive until March 2026, granting Ukrainian refugees access to essential health services, education, and other critical support. The Republic of Moldova followed this model and also introduced Temporary Protection for Ukrainian refugees.\n\nIn 2024, to assess the health and mental health situation of Ukrainian refugees, their access to services, and the barriers they face across countries, Regional Refugee Response Plan (RRP) health and mental health and psychosocial support (MHPSS) partners conducted a regional analysis of the Socio-Economic Insights Survey (SEIS) data from 10 refugee-hosting countries: Bulgaria, Czechia, Estonia, Hungary, Latvia, Lithuania, Poland, Republic of Moldova, Romania, and Slovakia. The analysis includes a comparison with key indicators collected in 2023.\n\nKey finding from the regional analysis include:\n\n**3**", "output": {"entities": {"named_data": [{"text": "Socio-Economic Insights Survey (SEIS)"}], "descriptive_data": [], "vague_data": []}}}
{"input": "mortality and night lights (Benshaul-Tolonen, 2019) for gold mining countries in West and East\n\nAfrica (including Ghana). The baseline differences in observable characteristics – in particular,\n\nlower levels of economic development preceding the mine opening - indicate that a cross\n\nsectional approach using only the post-period may not be sufficient to understand the impact of\n\ngold mining on socio-economic variables.\n\n**Table 2 Summary statistics for women’s survey**\n\n(1) (2) (3)         (4)\n\nBefore mining During Mining\n\n>20 km <20 km >20 km <20 km\n\nMean Coefficient Mean Coefficient\n\n_Woman Characteristics_\nAge 28.79 0.836 28.95 -0.352\nTotal children 2.18 0.417* 2.56 -0.035\nWealth 3.85 -0.619** 3.33 -0.028\nNonmigrant 0.32 0.123** 0.33 -0.028\nUrban 0.62 -0.300** 0.49 -0.150**\nNo education 0.17 -0.045 0.20 -0.042**\n<3 years education 0.77 0.035 0.74 0.045**\n\n15", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**COUNTRY NATIONALS, %** **[1,2,3,4]**\n\nHost country nationals Ukraine refugees Bulgaria Hungary Poland Romania Slovakia Region\n\n1. The poverty rate is defined as the share of individuals with an\nequivalized disposable income that is less than 50% of the host country median 2. Calculations for Moldova were not conducted, as this country is not included into the [EU statistics on income and living conditions (SILC)](https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions)\n[survey, which the OECD uses as the basis for host country poverty](https://ec.europa.eu/eurostat/web/microdata/european-union-statistics-on-income-and-living-conditions) assessments 3. Results for the Czech Republic not individually presented due to sampling limitations 4. The host country poverty rate was based on [OECD indicators for](https://stats.oecd.org/)\n[2021 that were indexed towards 2023 using consumer price index](https://stats.oecd.org/) (CPI) data Refugee households also report having to engage in harmful coping strategies to meet basic needs.\nSome 8% and 15% had to resort to emergency 5 Belarus, Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, the Republic of Moldova, Poland, Romania, and Slovakia 6 Defined as the total after-tax income of the household (including wages, transfers, social protection benefits, etc.) divided by the square root of the household size", "output": {"entities": {"named_data": [{"text": "EU statistics on income and living conditions"}, {"text": "OECD indicators"}], "descriptive_data": [], "vague_data": [{"text": "consumer price index"}]}}}
{"input": "Had to skip a Adults had to meal eat less to feed small children Source: Survey data, SAG estimates\n\n**Employment remains closely associated with significantly lower poverty rates, but size of**\n\n**employment income is key**\n\nJust like in the case of 2023 data, the current survey round suggests a strong link between employment and poverty. Whereas for individuals living in households with no one employed the poverty rate stands at a staggering 62%, it drops to 10% for those with at least one person working. That said, after correcting for excessive housing costs, the poverty rate in the latter group grows to 25%, which is more than double the host country rate. This implies that while employment at refugee household level is important, it is not sufficient to ensure a decent living.\n\nHouseholds that are less financially vulnerable receive more of their income from employment. For those with very low income (below the poverty line), only 26% of their total income comes from work. This figure grows to 67% for those identified as having an income below the poverty threshold after correcting it for housing costs, and to 88% for those living above the poverty line.\n\n**8**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "Survey data"}]}}}
{"input": "A feature of our modelling approach is that the resulting GDP gains are reduced due to increased competition on the labour market, which slightly increases the unemployment rate by 0.18-0.3 pp. in 2023, corresponding to 33-54 thousand additional people being unemployed. This effect also slows down real wage growth by 0.65-1.15% in 2023.\nIn reality, these negative effects are likely to be compensated by positive productivity gains, in the form of adjustments on the part of native workers (by their occupational upgrading, see papers by Peri and Sparber, 2009; Foged and Peri, 2016) and firms (by skill-biased technical change, see papers by Lewis and Peri, 2015, or Lewis, 2013), as econometric studies find only small effects on native wages, clustered around zero (Peri, 2014). The case of refugees from Ukraine in Poland is studied in an early paper by Gromadzki and Lewandowski (2023), who find no effect on earnings,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "documentation has been a major contributor. The acquisition of citizenship has provided some new avenues,\n\nespecially for the youth, such as working in the hospitality industry and the ability to obtain driving licenses, which\n\nhas opened job opportunities in the transportation sector. However, most of the community still relies on traditional\n\ntrades such as carpentry and basket weaving. The competitive nature of these trades, coupled with a lack of\n\ndiversification in skills and economic opportunities, is prompting members to explore new economic avenues. This\n\nsituation highlights the need for economic development initiatives that are tailored to the community's unique\n\nneeds and skills, offering sustainable and diversified economic opportunities.\n\nThe youth within the Shona community demonstrate a keen interest in enhancing their skills and seeking\n\nopportunities beyond conventional trades. The improvement in access to education is a positive development, yet\n\nthe challenge of transitioning into the formal labor market remains significant. Citizenship has facilitated easier\n\nmobility and enabled traditional vending activities, but it has not led to substantial changes in long-term career\n\nprospects. This underscores the need for targeted youth development programs focusing on vocational training,\n\ncareer counseling, and job placement services to help bridge the gap between education and employment.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Co-nationals can provide important information to refugees about employment opportunities. In Germany, Battisti, Peri, and Romiti (2022) found that immigrants initially located in places with more conationals, as well as well as refugees and repatriated ethnic Germans dispersed to such places, are more likely to be employed in the first 3 years. It was found, however, that these groups had lower probability of investing in human capital. In Swiss data, Martén, Hainmueller, and Hangartner (2019) found that refugees dispersed to locations with more co-nationals are more likely to find work, especially in the first 3 years. In Danish data, Damm (2014) found that higher skill levels of non-Western immigrant men in an area raises employment probability of refugee men, while higher employment rates of their co-national men raises their earnings. Also in Danish data, Damm (2009) found that larger size of ethnic network in an area increases earnings of refugees.\nIn Swedish data, Edin, Fredriksson, and Aslund (2003) found that refugees dispersed to areas with more co-nationals experience higher earnings.\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "Danish data"}, {"text": "Swedish data"}, {"text": "Swiss data"}]}}}
{"input": "systems, conducting community-based identification campaigns, and facilitating cross-border collaboration to\n\naddress statelessness among migrant populations. Providing technical and financial assistance to countries with\n\nhigh numbers of stateless individuals would further enable the implementation of comprehensive registration and\n\ncitizenship programs. The new Global Alliance to End Statelessness provides a multi-stakeholder platform to\n\nstrengthen these joint efforts.\n\n**5. Expand efforts to generate evidence on the impacts of statelessness and post-citizenship integration globally,**\n\n**with a focus on Kenya.**\n\nStakeholders should invest in continued, longitudinal studies to track the Shona community’s socioeconomic\n\nprogress over time and take advantage of the pre- and post-citizenship data that is already available, enabling a\n\nbetter understanding of post-citizenship outcomes. Additionally, research should be expanded to include the\n\nMakonde, Pemba, Rundi and other communities alongside the national population, providing comparative insights\n\n**[www.unhcr.org](http://www.unhcr.org/)** 11", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "pre- and post-citizenship data"}]}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n# Health analysis\n\n### **Health remains a** **priority need**\n\nAccess to health services has remained a priority need and is ranked among the top three priorities by 33% of households, second only to employment and livelihoods support. The identification of health as a priority is consistent with 2023, where 34% of households ranked health among their top three needs.\n\nVariations exist across countries, health care was the top priority need for respondents in half the countries (Bulgaria, Hungary, Moldova, Romania, and Latvia). In 2024, health care became a top priority for 49% of households in Romania, a shift from 38% in 2023, potentially indicating barriers and changes in the level of access.\n\n(2023 N=9,466, 2024 N=7,140)\n\n- Not included in 2023 survey\n\n**TOP 10 PRIORITY NEEDS (OUT OF THOSE WHO REPORTED)**\n\n2023 2024 Employment, livelihoods Healthcare services Accommodation Language course Education for children Medicines Food Trainings, education adults Legal status* Registration, legal assistance", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n## Literature\n\nAcemoglu, D. (2002). Directed Technical Change, Review of Economic Studies 69(4):781-80.\n\nAleksynska, M., & Tritah, A. (2015). The Heterogeneity Of Immigrants, Host Countries' Income And Productivity: A Channel Accounting Approach. Economic Inquiry, 53(1), 150-172.\n\nAleksynska, M., & Tritah, A. (2013). Occupation–education mismatch of immigrant workers in Europe: Context and policies, Economics of Education Review 36:229-244.\n\nBabakova, O., Gomon, T., Naranovich, K., & Oliński, P. (2024). Ułatwienia w zatrudnianiu cudzoziemców spoza UE, Kierunek Polska. Rekomendacje dla polskiej polityki migracyjnej, Forum Obywatelskiego Rozwoju, July, ISBN 978-83-63408-04-6.\n\nBeerli, A., & Peri, G. (2018). The labor market effects of opening the border: Evidence from Switzerland, NBER Working Paper No. 21319.\n\nBrell, C., Dustmann, C., & Preston, I. (2020). The labor market integration of refugee migrants in high-income countries. Journal of Economic Perspectives, 34(1), 94-121.\n\nBrücker, H., Glitz, A., Lerche, A., & Romiti, A. (2021). Occupational recognition and immigrant labor market outcomes. Journal of Labor Economics,39(2) Cassidy, H., & Dacass, T. (2021). Occupational licensing and immigrants. The Journal of Law and Economics, 64(1), 1-28.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "It is a general equilibrium model using consumer and producer optimalisation to calculate changes in the economy in response to shocks. This allows to assess the impact of shocks considering supply and demand channels as well as connections between different sectors of economy. This provides information about their total impact on many aspects of the economy including the labour market, government revenue as well as main economic aggregates. It is deemed the most appropriate tool to account for refugees’ multi-layered impact. To account for the effects of other shocks happening in the economy (such as the energy crisis) counterfactual analysis was performed using the newest data for the Polish economy. In other words, we were able to isolate the refugee inflow from all other shocks in the economy, like the other macroeconomic consequences of the war in Ukraine. The results were calculated for 2022 and 2023 with additional long-term analysis to check how the economy would adapt assuming no new shocks including no counter-shocks [35] .\n\n33 [Economics of climate change | Deloitte Australia](https://www.deloitte.com/au/en/services/economics/services/economics-climate-change.html)\n34 [Analiza ryzyk klimatycznych – badanie scenariuszy z modelem D.Climate | Deloitte](https://www2.deloitte.com/pl/pl/pages/risk/solutions/analiza-ryzyk-klimatycznych-badanie-scenariuszy-z-modelem-DClimate.html)\n\n---\n[35] E.g. refugees keep having lower productivity rather than adapt to level of natives.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "newest data for the Polish economy"}]}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\n**7.** **OPERATIONAL \r FRAMEWORK**\n\nWhile \r positive \r developments \r already \r undertaken \r by \r the \r Government \r point \r to \r an\neventual \r return \r of \r refugees \r from \r Thailand, \r the \r timing \r of \r the \r return \r remains \r difficult \r to\npredict. \r  \r The \r Government \r of \r Myanmar \r has \r indicated \r that \r its \r initial \r priority \r will \r be \r to\ncommence \r facilitating \r solutions \r for \r IDPs, \r followed \r by \r the \r voluntary \r repatriation \r of\nrefugees. \r The \r strategy \r for \r the \r South-­‐East \r shall \r therefore \r be \r phased \r in \r its \r approach\nstarting \r by \r strengthening \r involvement \r in \r IDP \r operations \r to \r be \r better \r positioned \r to\nreceive \r returning \r refugees \r under \r organized \r repatriation \r in \r the \r future. \r Beyond \r the\nplanned \r phases \r UNHCR \r and \r partners \r shall \r however \r remain \r alert \r to \r sudden \r changes \r in\nthe \r political \r environment \r and \r being \r ready \r to \r respond.\n\nThe \r decision \r to \r shift \r between \r phases \r will \r be \r dictated \r by \r the \r operational \r context,\nparticularly \r changes \r in \r peace \r and \r security, \r access, \r conditions \r in \r return \r areas, \r and\nindications \r of \r readiness \r of \r IDPs \r and \r refugees \r to \r return. \r It \r is \r expected \r that \r UNHCR \r and\npartners’ \r presence \r and \r activities \r in \r one \r phase \r could \r also \r contribute, \r for \r instance, \r to\nimprovements \r in \r return \r conditions, \r thereby \r catalysing \r a \r shift \r to \r the \r next \r phase.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**ranked lowest on both measures.**\nUkrainian refugees earn the highest wages in manufacturing, health, and accommodation and food service activities, while the lowest in education, other services, and construction. A comparison to median earnings in these sectors in the economy as a whole (after recalculation from gross to net earnings) changes that order, with Ukrainian refugees employed in accommodation and food service activities, and construction earning more than 100% of all workers median, and education, health services, and transportation and storage on the lowest ranks. Earnings relative to the total economy would be lower, if gross wages were compared, because Ukrainian refugees are less likely to have employment contracts and pay social contributions on their entire earnings. [16] Ukrainian refugees employed in education have the lowest median net wages when compared to other sectors. This is likely due to occupational regulations that prevent persons with nonEU citizenship from working as teachers in public schools, which is further discussed in chapter 4.\n\n4,198 4,216 Source: Deloitte own elaboration based on SEIS UNHCR survey and GUS data.\n\n© UNHCR / Anna Liminowicz\n\n---\n[16] As refugees more often than average in the Polish economy work based on civil law contracts or self-employment, they may not be covered by employee", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "GUS data"}], "vague_data": []}}}
{"input": "2. Regulatory Environment and Governance\n\nthe introduction of accelerated procedures in the 2023 Decree, some asylum-seekers with vulnerabilities\nwait for a first-instance asylum decision for several months. It is crucial to note that asylum-seekers do not\nhave the same rights as recognized refugees, limiting their socio-economic integration. Additionally, the\nbudget of CNARR remains mostly funded by UNHCR.\n\nThe asylum legislation, available in French and Arabic, is not well-known among some local administrative\nauthorities and host communities. Despite ongoing information sessions and capacity development\nconducted by CNARR with UNHCR support, the impact is constrained by high personnel turnover in central\nand provincial administrations. CNARR, supported by UNHCR, has launched a campaign to disseminate\ninformation about the new refugee Law. Additional efforts are essential for effective dissemination, especially\nin remote areas hosting refugees and asylum-seekers, particularly with the recent release of the 2023\nDecree implementing the 2020 Asylum Law.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The 2023 Decree outlines the procedures for reception and registering asylum-seekers arriving in Chad. It\ndetails the individualized refugee status determination (RSD) procedure, covering interview modalities, RSD\nassessments, and final adjudication by the Sub Eligibility Commission. Additionally, the Decree introduces\nan accelerated RSD procedure for specific groups, including unaccompanied and separated children,\nvictims of torture and gender-based violence, and vulnerable asylum-seekers. It also addresses prima facie\nrefugee recognition for mass influxes due to violence or unrest, or for groups of asylum-seekers with similar\ncharacteristics. The Decree includes appeal procedures for first instance rejected asylum-seekers which is\ndealt with by a Sub-Commission of Appeal stipulating that the decisions taken by this body are reasoned\nand endorsed by an order taken by the Minister in charge of territorial administration. The same Decree also\nindicates that decisions of the Appeals Sub-Commission are subject to appeal before the administrative\nchamber of the Supreme Court. The Decree also outlines the processes for exclusion, cessation, revocation\nand cancellation of refugee status. Additionally, the Decree outlines the specific legal and judicial assistance\nthat asylum-seekers and refugees can benefit from in the national asylum procedure, but also for the any\nother matters/conflict.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Kleiner, M. M., & Krueger, A. B. (2013). Analyzing the Extent and Influence of Occupational Licensing on the Labor Market. Journal of Labor Economics, 31(2), S173–S202. https://doi.org/10.1086/669060 46 Lessem, R., & Sanders, C. (2020). Immigrant wage growth in the United States: The role of occupational upgrading. International Economic Review, 61(2), 941-972.\n\nLewandowski, P., Górny, A., Krząkała, M., & Palczyńska, M. (2025). The Role of Job Task Degradation in Shaping Return Intentions: Evidence from Ukrainian War Refugees in Poland. IBS working paper, 01/2025. https://ibs.org.pl/wp-content/ uploads/2025/03/Job_task_degradation_return_intentions_Ukrainian_refugees_ IBS_WP_202501.pdf Lewis, E. (2013). Immigration and production technology, Annual Review of Economics 5(1):165-191 Lewis, E., & Peri, G. (2015). “Immigration and the Economy of Cities and Regions”,\n\n[in] Duranton, G., Henderson, J.V., Strange, W., Handbook of Regional and Urban Economics, Volume 5A, North-Holland, Elsevier.\n\nMeager N., & Speckesser, S. (2011). Wages, productivity and employment: A review of theory and international data, Brussels: European Employment Observatory.\n\nMonitor Deloitte (2022). Refugees from Ukraine in Poland: Challenges and potential for integration. October.\n\nNBP (2024). Sytuacja życiowa i ekonomiczna migrantów z Ukrainy w Polsce w 2024 r. Raport z badania ankietowego, Departament Statystyki, Narodowy Bank Polski, Warszawa.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "High employment rate of Ukrainian refugees translates into more workers and thus additional economic growth. In July 2022, OECD estimated the contribution of Ukrainian refugees to the labour force and employment in European host countries, based on a 2014 Labour Force Survey adhoc module that includes refugee labour market outcomes and 2019 LFS with outcomes of recent non-EU migrants.\nThey estimated that Ukrainian refugees would increase employment in Poland by\n1.2-1.8% (Dumont & Lauren, 2022).\nAs refugee employment rates are higher than expected, the actual increase is higher, between 1.4% and 2.2% (estimates of 0,230,35 million relative to LFS employment).\n\n##### To assess the impact of refugees on the Polish economy, a simulation was performed using the Deloitte D.Climate model [33,34] .", "output": {"entities": {"named_data": [{"text": "2014 Labour Force Survey adhoc module"}, {"text": "2019 LFS"}], "descriptive_data": [], "vague_data": []}}}
{"input": "##### **September/ October 2023 report**\n\n###### Venezuela\n\nand Gender-Based Violence for officials\n\nof the Women's Secretariat of the State\n\nof Miranda. Conducted from September\n\n28th to October 11, 2023, the PA facil\nitated the first virtual session on key\n\nconcepts, receiving positive feedback\n\nfrom the 35 participating officials.\n\n**XVII.** **September’s** **Monthly**\n\n**Meeting with Partners**\n\n**On Thursday, September 28th, the PC**\n\n**convened its monthly meeting with**\n\n**53 members representing 41 partner**\n\n**organizations.** The agenda covered an\n\ninformation exchange between partners\n\nwhich expressed concerns on the way\n\nnational IDs are processed in light of the\n\nsoon elections; saw a presentation of\n\nthe New Accountability Framework for\n\nAffected Populations (AAP), its objectives\n\nand work plan; updates from the national\n\nsubcluster of Ciudad Guayana on their\n\n**11**\n\n**October.** The focus was on ensuring\n\nthe accuracy of registered services and\n\ncollaborating with partner organizations\n\nto edit or confirm the removal of inactive\n\nservices. The revised database is under\ngoing verification for coherence by the\n\nIM team before being uploaded onto the\n\nplatform. Considerations regarding the\n\nplatform itself and the inclusion of other\n\nsectors are also under review, and once\n\nfinalized, the PC will implement its com\nmunication strategy on Service Mapping.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE measles vaccination coverage for children stood at 83%, similar to 84% in 2023, falling short of the 95% target.\n\nInformal support also played a vital role, with 33% receiving help from family or friends and 12% accessing spiritual support. Overall, 88% of those who received support reported improved wellbeing, though there are notable differences depending on gender and age.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "differences are identified in 15-19 and 20-24 age groups, with much higher employment rates for Ukrainian refugees due perhaps to the fact that the Ukrainian school system ends at 17 while the Polish one at 19. [13] However, employment rates drop for Ukrainian female refugees in the 25-29, 30-34, and 35-39 age groups when compared to younger and older groups, as well as to Polish women, which may be due to insufficient access to childcare services.\nEmployment rates for Ukrainian female refugees are also substantially lower in the 55-59 age group, perhaps due to the fact that female retirement age in Ukraine has only recently (in 2021) become 60. [14]\n\n**With the current level of integration**\n\n**of Ukrainian refugees into the labour**\n\n**market and the jobs they perform,**\n\n**their median net earnings are about**\n\n**four-fifths of the national median**\n\n**– although likely lower in terms of**\n\n---\n[14] https://www.social-protection.org/gimi/gess/Media.action;jsessionid=U1dm6XAPF38pPk5_pzhfaGoS_rOACMDDVv4w5uevMsKBeQEC5-_g!284293951?id=15680 15 Percentage calculated based on GUS average for the economy as a whole in the months of the SEIS survey.", "output": {"entities": {"named_data": [{"text": "SEIS survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "The regional protection monitoring harmonization established a regional incident typology framework to efficiently\nanalyze the regional protection monitoring data. To this extent, 7,503 protection incidents with 106,673 victims were\nreported in September 2022 in both countries, which affected 10 provinces in the Democratic Republic of Congo\n(DRC) and 1 province in Mozambique. It is worth mentioning that of the protection incidents reported in September\n2022, some occurred in the same month, and some occurred before September 2022.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "regional protection monitoring data"}], "vague_data": []}}}
{"input": "### **Registration and Documentation**\n\nUNHCR Indonesia undertakes registration of persons seeking asylum in Indonesia on behalf of the\nGovernment of Indonesia and issues UNHCR identity documentation. Registration interviews are\nprimarily conducted in-person for verification of biometric data and relevant records. Most\nregistration interviews take place at the Reception Center in Jakarta or during accommodation\nvisits/missions by the respective field team for individuals residing outside the greater Jakarta area. In\n2023, 2,547 individuals (1,324 cases) were registered by UNHCR Indonesia, which includes 1,225\nRohingya refugees registered during emergency registration missions following boat disembarkations\nin Aceh in November and December 2023. UNHCR Indonesia provides continuous registration services\nto registered refugees and asylum-seekers and maintains updated personal data in our internal\ndatabase to ensure vulnerable refugees and asylum-seekers are identified and assisted with\nprotection interventions and solutions.\n\n### **Refugee Status Determination**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "# Appendix. Model Calibration\n\n##### D.Climate is CGE [51] model developed by Deloitte Economic Institute based on GTAP model [52] . If source of data is not specified it means that shocks were calibrated to data from the model database.\n\nIt was assumed that impact of refugees on the Polish economy was felt as combined four different shocks: to population, labour supply, average propensity to save, and productivity, with shocks to population and labour supply being balanced by equivalent shocks in Eastern Europe [53] .\nMoreover, as part of assumed increase in spending by Ukrainians in Poland was financed by savings from Ukraine this was balanced by equivalent negative shock on investment in Eastern Europe.\n\nShock to population was calibrated to match data for residents of Poland from Statistics Poland and number of refugees based on PESEL UKR. Equivalent shock in Eastern Europe was calculated using data for population in this region from World Population Prospects UN.", "output": {"entities": {"named_data": [{"text": "World Population Prospects"}, {"text": "Statistics Poland"}, {"text": "PESEL UKR"}], "descriptive_data": [], "vague_data": [{"text": "data for residents of Poland from Statistics Poland"}]}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n### **Disability and** **MHPSS**\n\nMental health and psychosocial problems were significantly more often reported by individuals with disabilities (51%, up from 42% in 2023) compared to those without disabilities (21%, up from 17% in 2023).\nThis highlights the heightened vulnerability of individuals with disabilities to mental health and psychosocial challenges, which are often exacerbated by social barriers such as limited accessibility, social exclusion, stigma, and a lack of support systems. There are clear variations across countries, with Romania (61%) and Hungary (60%) reporting the highest percentage of problems among individuals with disabilities, while Moldova (29%) and Latvia (31%) reported the lowest percentage.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "##### **September/ October 2023 report**\n\n###### Venezuela\n\nedits to some of the objectives and to the\n\ntimeline stipulated.\n\n**IV. GPC Townhall**\n\n**On October 18th a Townhall was**\n\n**organized by the Global Protection**\n\n**Cluster (GPC) with Field Operations.**\n\nHRP 2024 key messages/instructions\n\nwere discussed and a calendar of\n\nbi-monthly GPC Townhalls with field\n\noperations with planned key topics were\n\npresented. The meeting had the aim to\n\nunderstand the different timelines and\n\nongoing HPC processes in each field\n\noperation as well as provide support to\n\nwhom needed it.\n\n**V. La Carnada Play**\n\n**The Working Group on the Prevention**\n\n**and** **Response** **to** **Trafficking** **in**\n\n**Persons** **(WGTiP)** **organized** **and**\n\nFora for the HNO process are in line with\n\nProtection needs in their area.\n\nThe Protection Cluster assured partic\nipation in the weekly ICCG meetings\n\nwhere HPC ongoing activities have been\n\ndiscussed and planned.\n\nFinally, bilateral meetings have been\n\norganized with PC’s partners NRC and\n\nOHCHR. With both partners their protec\ntion programming has been discuss and\n\npossible coordination in the Cluster.\n\n**III. Accountability for Affected**\n\n**Populations (AAP) WG**\n\n**The PC has participated actively in**\n\n**the monthly meetings conducted by**\n\n**the AAP working group, which aimed**\n\n**at increasing the inputs of affected**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "lack of trust (3%), work commitments (3%), transportation (2%), and insecurity/safety concerns (2%) and other factors (5%). Results show that, despite reporting mental health problems that impede functioning, more than a third of respondents did not perceive a need for MHPSS, which may stem from a lack of mental health literacy, stigma or lack of confidence in services.\nInsufficient awareness about available resources is also a primary barrier across the region, with language barriers posing additional challenges in certain countries. Women were more likely to report lacking time to seek services (12%) than were men (4%), which may be linked to their multiple other responsibilities related to livelihoods, household responsibilities, and care work. Addressing these barriers requires tailored interventions to improve awareness, reduce stigma and increase confidence in services, enhance linguistic accessibility, and address logistical and availability constraints (especially among women), ultimately improving access to MHPSS services.\n\n**SELF-REPORTED BARRIERS TO ACCESSING MENTAL**\n\n**HEALTH AND PSYCHOSOCIAL SUPPORT SERVICES BY**\n\n**GENDER AT REGIONAL LEVEL (TOP 5)**\n\nFemale Male 46%\n\n### **Barriers to** **accessing Mental** **Health and** **Psychosocial** **Support services**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "2021, so the sample size is still growing.\nHowever, it is large enough to allow for some cautious inference with 4.2 million Polish citizens in mid-2022 and 6.2 million in mid-2024. This has been combined with average salaries in 128 occupational groups in GUS data for October 2022 (the most recent data). Over the two-year period from Q2 2022 to Q2 2024, following the arrival of Ukrainian refugees, the occupational group distribution of Polish citizens shifted\n\n**Chart 30. Polish citizens occupational distribution change by salary bracket, Q2 2022 and Q2 2024**\nQ2 2022 distribution, Q2 2024 distribution, and percentage point changes between them\n\n-1.8 pp.\n\n<= 4,000 (4,000; 6,000] (6,000; 8,000] (8,000; 10,000] - 10,000 Q2 2022 Q2 2024 41", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "GUS data for October 2022"}], "vague_data": []}}}
{"input": "to April 2022 on wages of native workers and other immigrants. They find no effect on wages, employment, or unemployment rate, except a very small positive impact on the wages of native women.\nUnderstanding how immigrants create positive productivity effects that counteract negative wage pressures and improve economic efficiency, requires moving beyond the canonical model of labour supply and demand.\nIn reality, immigrants and native residents differ in important ways, which triggers complementary occupational upgrading of natives (Beerli and Peri, 2017; Tabellini, 2020; Cattaneo et al., 2015; Foged and Peri, 2016; D’Amuri i Peri, 2014; Ortega and Verdugo, 2014; Peri and Sparber, 2009) and investment in complementary production technologies by firms (Peri, 2016; Lewis and Peri, 2015; Lewis, 2013; Peri, 2012).\nWe survey this literature in this chapter, underlying that our model should thus be treated as a conservative lower bound of the effect.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES the survey data side, only households that did not have any missing information on income (respondents were asked to provide both sources and amounts) were included in the calculation. For households claiming no or very little income an imputation was made based on expenses and the duration of stay in the host country.\n\nIt is important to note that while the poverty definition adopted in this assessment allows for comparisons across the countries covered (limitations apply to the Republic of Moldova), it may not be directly comparable to other studies, as approaches tend to vary quite significantly. The setup of the questionnaire, the sampling methodology, the processing of income data (including any imputations), the approach to equivalizing income, and finally the location of the poverty line itself in the income range all have a substantial impact on poverty indicators.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "the survey data"}], "vague_data": []}}}
{"input": "Most of the refugees from Ukraine currently living in Poland are women and children, though over half of the total population is of working age.\nThe best population data available is the active PESEL database as of 10th October 2023. According to the registry, 63.7% of them are women and 36.3% are men.\nThe database also includes the age of the Ukrainian PESEL holders, which indicates that over half (56%) are of working age (18-64), which amounts to more than 536 thousand people. More precisely, women younger than 18 make up 19% of the population, women aged 18-64 account for around 41% of the population, while those aged 65 and above are around 3% of total population. The incoming men are mostly young, those younger than 18 stand for around 20% of all refugees, men aged 18-64 make up 15% of the population and men older than 64 account for only 1%.", "output": {"entities": {"named_data": [{"text": "active PESEL database"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Kenya in 2016, followed by the provision of nationality to 1,659 Shona in 2020-21, and most recently, the\n\nrecognition as nationals of approximately 7,000 Pemba in 2023. These milestones underscore Kenya’s commitment\n\nto addressing statelessness, a commitment reaffirmed at the Global Refugee Forum (GRF) in December 2023\n\nthrough four strategic pledges aimed at the progressive eradication of statelessness. Despite these achievements,\n\nan estimated 9,800 individuals in Kenya remain stateless today, highlighting the need for sustained efforts to fully\n\nresolve this issue. Gaps in law continue to be a contributing cause of statelessness, due to Section 15(1) of the\n\nCitizenship and Immigration Act, which limits the scope of the definition of a stateless person to those who were\n\nin Kenya when it gained independence on 12 December 1963, excluding many individuals who arrived later, as well\n\nas their descendants. In addition, neither the Constitution nor the Citizenship and Immigration Act contain a legal\n\nsafeguard to ensure that a child born on the territory who would otherwise be statelessness is granted Kenyan\n\nnationality.\n\n**[www.unhcr.org](http://www.unhcr.org/)** 2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Electricity, gas, steam and air conditioning supply Mining and quarrying Transportation and storage\n\n**-1**\n\n**34**\n\n**Chart 8.** Share of companies reporting vacancies\n\n50% 40% 30% 20% 10% 0% C I G Q N P J M O F K A L E D B H\n\n**Source:** Deloitte own elaboration based on ZUS data.\n\n(more than 18 thousand), and wholesale and retail trade (more than 18 thousand).\nThe only sector that has seen a decline was transportation and storage (by more than 1 thousand). Unfortunately, public data does not report how much of this change is due to the refugees from Ukraine entering these sectors, or how much due to pre-2022 Ukrainian workers changing their jobs.\n\n2006\n-Q4\n\n2008\n\n-Q2\n\n2009\n\n-Q4\n\n2011\n\n-Q2\n\n2012\n-Q4\n\n2014\n-Q2\n\n2015\n\n-Q4\n\n2017\n-Q2\n\n2018\n\n-Q4\n\n2020\n-Q2\n\n2021\n-Q4\n\n2023\n-Q2", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "ZUS data"}], "vague_data": []}}}
{"input": "- Enhance \r awareness, \r developing \r trust \r among \r stakeholders \r and \r building\ncapacities \r of \r central \r and \r local \r authorities, \r implementing \r and \r operational\npartners, \r civil \r society \r and \r local \r communities \r to \r support \r and \r deliver \r protection\nand \r assistance, \r including \r investing \r in \r support \r to \r community \r self-­‐management\nstructures \r and \r community \r mobilisation \r through \r training, \r awareness \r campaigns,\nand \r support \r to \r community \r committees.\n\n- Follow \r up \r and \r advocate \r with \r Immigration \r and \r National \r Registration \r Department\non \r expedited \r procedures \r for \r the \r issuance \r of \r CSCs \r for \r IDPs \r and \r returnees,\nincluding \r measures \r to \r prevent \r statelessness \r which \r properly \r address \r the \r specific\nsituation \r of \r refugees. \r Support \r authorities \r to \r ensure \r that \r internally \r displaced\npersons \r and \r returning \r refugees \r as \r well \r as \r former \r child \r soldiers \r do \r not \r miss \r the\nopportunity \r of \r obtaining \r CSCs.\n\n- Initiate \r negotiations \r for \r the \r removal \r of \r administrative \r and \r legal \r impediments\nwhich \r might \r inhibit \r sustainable \r return, \r such \r as \r taxation-­‐related \r issues.\n\n- Support \r a \r comprehensive \r evaluation \r of \r property \r laws \r and \r provide \r concrete\nproposals \r for \r revisions \r that \r will \r ensure \r the \r restoration \r or \r repossession \r of \r land\nrights \r by \r returnees.\n\n- Provide \r access \r to \r legal \r services \r through \r advocacy \r interventions \r and \r training \r in\nserving \r the \r legal \r needs \r of \r returnees \r and \r offering \r appropriate \r legal \r assistance.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE\n\n### **Contents**\n\nAcknowledgements\b 2 Summary of findings and recommendations\b 3 Background\b 4 Socio-economic inclusion – key findings\b 4 Methodology\b 10 Limitations\b 11\n\n### **Acknowledgements**\n\nWe gratefully acknowledge the contributions of many individuals and organizations who contributed to this report. The regional analysis was facilitated by the Regional MSNA Livelihoods and Socio-Economic Inclusion Sector Analysis Group, co-coordinated by Konstantin Fastovets (UNHCR) and Susanne Klink (UNHCR). The data analysis was conducted by Marco Delogu (UNICEF), Konstantin Fastovets (UNHCR), Erin Neale (IOM), and Mihail Peleah (UNDP). Writing of the report was led by the co-coordinators along with Oxana Maicuca (UNDP), Erin Neale (IOM), Arianna Pearlstein (UN Women), and Alketa Zazo (UNICEF).\n\nAdditionally, we extend our appreciation to Erika Morishita Sarmiento (UNHCR) for her valuable graphic design contributions. Lastly, we express our thanks to Jad Ghosn, Milindi Illangasinghe, and the Data, Identity Management and Analysis team (UNHCR) for their guidance and support on the regional MSNA analysis for socio-economic inclusion and across all the sectors, and to Steven Bunce (UNHCR) for reviewing the report.\n\n**Cover photograph:**\n©UNHCR/Ioana Moldovan\n\n**2**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Poland**\nThe beginning of the full-scale war in Ukraine in February 2022 resulted in large flows of refugees, reaching more than 6 million globally. [3] Much of this exodus happened through the Polish border.\nAs of October 2023, almost 1 million Ukrainian refugees were living in Poland [4] (Chapter 1). In the past decade, Poland experienced large labour migration from Ukraine. The number of workers with Ukrainian citizenship that registered for social security (this data does not include those working in the shadow economy or some minor cases that do not require registration) grew from just 33 thousand in 2013 to 627 thousand in 2021. It has to be noted however, that short-term nature of most of these stays (6 months in a span 12 months), fact that one person could hold several permits (as a result of changing jobs or positions within the same company), legal changes, and decentralized nature of permits all hinder the reliability of these figures. Two-thirds of such migrants have been men, some of whom left families in Ukraine temporarily to bring or send money back. Migration has been primarily based on firm sponsorship, where companies provided job offers and handled formalities, which resulted in very high employment rates – 94% as of November 2022 according to NBP (2023) estimates.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Furthermore, on 1 June 2023, the Transitional National Council also enacted [Law No. 012/PT/2023](https://www.refworld.org/docid/648710104.html) relating to\nthe protection and assistance of internally displaced persons in the Republic of Chad. This Law establishes\nthe legal framework to assist internally displaced persons, serving as a guiding, preventive and assistance\ntool for both the state and other relevant actors in addressing internal displacement.\nThis has resulted in instances of arbitrary arrests and detentions of refugees and asylum-seekers.\n\n**2.2** **Security of legal status**\n\nThe new asylum legislation establishes predictable legal arrangements for the stay of refugees and asylum[seekers in Chad. Article 31 of the 2020 Law mandates the issuance of a refugee ID card by the competent](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf)\nauthority. This card serves as both an authorization to stay in Chad and a residency permit, allowing freedom\nof movement for refugees within the conditions specified by Law. The second paragraph of Article 14 of the\n2020 asylum Law stipulates that an asylum-seeker certificate is valid for six months and equivalent to an\nauthorization to stay in Chad, is issued by CNARR and renewed until the Eligibility Sub Commission takes\na decision on his/her refugee status.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n### **Health** **expenditures and** **health insurance**\n\nRegionally health expenditures, on average, were 8% of all household expenditures in the 30 days preceding the survey, a slight reduction from 9% in 2023. In Latvia, Moldova, Romania and Bulgaria, the share of health expenditures was more than 10% of the household expenditures.\n\n**AVERAGE SHARE OF HOUSEHOLDS’ EXPENDITURE**\n\n**ALLOCATED TO HEALTH**\n\nRegional Latvia Bulgaria Romania Moldova Hungary Poland Slovakia Lithuania Czechia Estonia (N=5,671) In households with a chronically ill member, the share of health expenditure was nearly double compared to those without (12% vs 5%), highlighting vulnerability and financial pressure in these households. The average share of health expenditure in households with children was 7%, while it was 9.5% in households without children.\n\n**AVERAGE SHARE OF HEALTH EXPENDITURE OF**\n\n**HOUSEHOLDS WITH/ WITHOUT MEMBERS WITH CHRONIC**\n\n**ILLNESS**\n\nHH with chronic illness member HH without chronic illness member Regional Latvia Moldova Romania Bulgaria Slovakia Poland Hungary Lithuania Estonia Czechia (N=5,671)\n\n**14**\n\n8% 12% 12% 12% 12% 9% 9% 9% 7% 5% 5%", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Policy Research Working Paper 7250\n\n### **Abstract**\n\nGhana is experiencing its third gold rush, and this paper\n\nsheds light on the socioeconomic impacts of this rapid\nexpansion in industrial production. Using a rich dataset consisting of geocoded household data combined\nwith detailed information on gold mining activities, the\nauthors conduct two types of difference-in-differences\nestimations that provide complementary evidence. The\nfirst is a local-level analysis that identifies an economic\nfootprint area very close to a mine, and the second is a\n\ndistrict-level analysis that captures the fiscal channel. The\nresults indicate that men are more likely to benefit from\ndirect employment as miners compared to men further\naway, and that women in mining communities may more\nlikely gain from indirect employment opportunities and\nearn cash for work. Authors also find that infant mortality rates decrease significantly in mining communities,\ncompared to the evolution in communities further away.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "geocoded household data"}], "vague_data": []}}}
{"input": "mining at birth. In investigating the effects on birth outcomes and infant mortality, we further\n\nclassify a child as treated if he or she is born in a district with active mining during the birth\n\nyear (in contrast to whether the mine is active when the mother was interviewed). We also\n\ninclude controls for the age of the child in the survey year in the child and birth outcome\n\nregressions (but, naturally, not in the infant mortality regressions).\n\n**5. Results using individual-level difference-in-differences strategy**\n\nIn this section, we present results using the two difference-in-differences strategies. Since the\n\nindividual analysis contains district fixed effects, the two strategies are complementary. While\n\nthe district-level analysis informs us about differences across and within districts over time, the\n\nlocal-level analysis gives us the additional impact at the very local level. This means that any\n\ndifferences in effects across district and local analysis should not be interpreted as\n\ninconsistencies, but rather as differential and additional impacts.\n\nIn a difference-in-differences setting, it is important that the sample is balanced, assuming that\n\nthe treatment and control groups are on similar trajectories. Table 2 shows the summary", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Despite the enactment of new asylum legislation, potential inconsistencies may persist with other laborrelated legislation that remain in force or have not been amended in the country. This lack of alignment\ncould create hesitancy among prospective employers when considering the hiring of refugees.\n\nFor instance, [Decree No. 96-189 PR/MFPT of 15 April 1996, and Deecree No. 1793/PR/PM/MECDT/2015 of 24](https://wwwex.ilo.org/dyn/natlex2/natlex2/files/download/97320/TCD-97320.pdf)\nAugust 2015, which address mandatory reporting of hiring, job offers and personnel in companies, as well\nas business-related procedures, are still applicable.\n\n8 R E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **R E P U B L I C O F C H A D**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**population in Poland has changed**\n\n**radically after February 24, 2022.**\nUp until 2021, Ukrainians in Poland were mostly men (close to two-thirds), who came for work-related reasons, often leaving their families back in Ukraine. The onset of the full-scale conflict in Ukraine triggered the arrival of individuals displaced by the war.\nThose were primarily women and children, with men in Ukraine being mobilized for the war effort. Social insurance data does not reflect the full extent of the change, showing only workers, without children and adults outside of employment.\n\n**Chart 3. Number of Ukrainians registered in Poland for social insurance by sex**\n\n2021 Q4 2022 Q4 2023 Q4 2024 Q2 Number of insured men with Ukrainian citizenship Number of insured women with Ukrainian citizenship Number of insured with Ukrainian citizenship Source: Deloitte own elaboration based on ZUS data.\n\n3 Employed person is a person, who during the reference week worked for at least 1 hour for pay or profit, including contributing family workers; had a certain job attachment; or produced agricultural goods for sale or barter. A definition according to the Labour Force Survey: https://ec.europa.eu/eurostat/statistics-explained/ index.php?title=Glossary:Employed_person_-_LFS 08 Source: Deloitte own elaboration based on the PESEL database as of September 2024.", "output": {"entities": {"named_data": [{"text": "Labour Force Survey"}, {"text": "PESEL database"}], "descriptive_data": [{"text": "ZUS data"}], "vague_data": [{"text": "Social insurance data"}]}}}
{"input": "##### **September/ October 2023 report**\n\n###### Venezuela\n\nReproductive Health), reinforcing com\nmunity resilience through livelihoods\n\nand access to adequate food, women's\n\nempowerment, gender equality, and\n\nprovision of assistance and protection\n\nservices (including Gender-Based Vio\nlence (GBV), children and adolescents,\n\nand human trafficking), and supporting\n\nemergency education activities with a\n\nsocio-productive approach.\n\n**XIX. Protection Monitoring Tool**\n\n**(PMT)**\n\n**The outcomes of the Protection Mon-**\n\n**itoring Tool (PMT) were shared with**\n\n**cluster partners. The PMT contin-**\n\n**ues to measure primary protection**\n\n**risks, population needs, access to**\n\n**rights, and humanitarian assistance**\n\n**at the community level.** For the period\n\nof March to August 2023, the PMT\n\nrecorded a total of 674 interviews con\n\nprotection work and the advancements\n\nof their workplan along with areas of\n\nresponsibility (AoRs), and the response\n\nmonitoring for August, showing a total of\n\n385,000 people reached by 95 partner\n\norganizations.\n\nAdditionally, the Service Mapping tool\n\nwas shared with partners, and it was\n\ninformed that together with the UNHCR\n\nInformation Management Unit and the\n\nAoRs, a complete update of the services\n\nregistered in the tool was being made.\n\nOrganizations were invited to always be\n\non the lookout to update services and to\n\nbe able to support the dissemination of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Wages also improved but remain significantly below host levels**\n\nDespite a 28% increase in the regional weighted average wage of refugees in 2024, this figure still stands 30% lower than that of the local population. This means that, on average, Ukrainians earned roughly two-thirds of what their hosts did for the same number of working hours. The wage disparity is particularly striking considering the educational qualifications of Ukrainian refugees—more than half of the working-age population hold advanced degrees (Bachelor’s or higher), compared to the same being true for just 27% of hosts.\n\n16. The data also demonstrates that the employment rate of refugees fluent in the local language is lower than for those with an intermediate or advanced knowledge. The reason for this is that the former group is heavily concentrated in lower age brackets, with almost 30% being 15-19 years old 17. Equivalent to ISCED-11, level 4 (post-secondary non-tertiary education)\n\n**12**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "A stateless person is someone who is not considered as a national by any\n\nState under the operation of its law.\n\n- 1954 Convention relating to the Status of Stateless Persons (Article 1).\n\n**Globally, an estimated 4.4 million people lack a nationality, leaving them stateless, according to statistics published**\n\n**by UN Refugee Agency (UNHCR)** . [[1]] In the East, Horn, and Great Lakes of Africa (EHAGL) region, this includes\n\n97,591 stateless persons or persons of undetermined nationality, of whom 9,800 live in Kenya. Given the lack of\n\nuniversal reporting and other gaps in statelessness data, these figures are likely to be an underestimate. Stateless\n\npeople often live on the margins of society and remain invisible in national statistics and other government\n\npopulation databases due to the complexities of accurate registration and data collection.\n\n**Lack of identifying documents confirming nationality frequently precludes stateless persons from working in the**\n\n**formal economy, owning property, accessing basic services such as health and education, moving freely or**\n\n**accessing financial services, leaving them at an elevated risk of poverty.** [[2]] Children may face restrictions on\n\nattending school, while exclusion from public health services imposes costs on families and creates risks for", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "national statistics"}]}}}
{"input": "Including a productivity shock will allow us to address the limitations of the “canonical model” of immigration. Peri (2016, 2014) refers to the framework that economists typically used to analyse migration in the 1980s and 1990s as the “canonical model”.\nIn this model, immigration is simply a shift in the labour supply for a given labour demand and given labour supply of native workers. It is also assumed that immigrants and natives are essentially identical in that they enter the same occupations and perform the same tasks, while firms do not adjust production technologies. In effect, immigrant workers have a positive impact on output, but a negative impact on wages, employment and activity of natives, and positive – on unemployment.\nHowever, this is difficult to reconcile with empirical evidence. Peri (2014) reviewed 27 empirical studies on the effect of immigration on natives’ wages, showing minimal impacts evenly distributed around zero. All estimates showed an adjustment to a 1 percentage point increase in the share of immigrants in a labour market of between -0.8% and +0.8% of the average native wage. In fact, 70% of estimates were between -0.1% and +0.1%.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Brazil stands as a regional leader, implementing _prima facie_ simplified refugee status determination\nprocedures under the regional refugee definition of the 1984 Cartagena Declaration\n(contemplated in its national legislation as those fleeing serious human rights violations) for\nindividuals from Venezuela, Burkina Faso, Iraq, Mali and Syria. The National Committee for\nRefugees (CONARE) has also granted refugee protection to individuals persecuted due to their\ndiverse sexual orientation and gender identity, as well as women and girls at risk of female genital\nmutilation.\n\nFurthermore, Brazil has established a humanitarian visa and temporary residence permit policy for\nnationals of Afghanistan, Haiti, Syria, and Ukraine. Temporary residence permits are also available\nfor Venezuelans who choose not to apply for asylum, ensuring access to protection and legal status\nfor a wide range of individuals in need.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Yivt = β0 + β1 ꞏ activet + β2 ꞏ mine + β3 ꞏ activet_ _* mine + αd + gt_ _+ λXi + εivt_, (1)\n\nwhere the outcome of an individual _i_ in cluster _v_, and for year _t_ is regressed on district and year\n\nfixed effects, a dummy for whether the respondent lives within 20 km of a mine (which is a\n\ncurrent or future mine [8] ), a dummy for whether the mine is active at the time of the survey\n\n(active), an interaction term between active mines and living close to a mine ( _activet * mine_ ),\n\nand a vector of individual-level control variables. _Mine_ is the terminology chosen to capture a\n\nknown gold resource in the ground, regardless of whether it is being extracted or not. In all\n\nregressions, we also control for living in an urban area, years of education, and age.\n\n---\n[8] A current or future mine could also be called a deposit. We have chosen against this terminology as there may", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "UNHCR \r will \r gradually \r phase \r down \r its \r direct \r assistance \r reviewing, \r together \r with\nstakeholders \r progress \r achieved \r on \r repatriation \r and \r reintegration, \r including \r analysing\nprospects \r for \r durable \r solutions \r and \r efforts \r to \r mainstream \r reintegration \r needs \r in\nnational \r policies \r and \r programmes. \r As \r key \r benchmarks \r are \r met, \r UNHCR \r will \r review \r and\nrefine \r its \r disengagement \r plan, \r including \r the \r timing \r and \r degree \r of \r phasing \r out \r from\nspecific \r projects \r and \r activities. \r A \r communication \r strategy \r will \r be \r designed \r to \r inform\nstakeholders \r of \r UNHCR \r progressive \r disengagement. \r The \r reintegration \r operation \r will \r be\nregularly \r reviewed \r and \r evaluated \r and \r lessons \r gathered \r for \r future \r application \r in \r other\noperations.\n\nUNHCR \r Myanmar\n15 \r June \r 2013\n\n15", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "2. Regulatory Environment and Governance\n\nbiometric and individual data of asylum-seekers in the UNHCR-managed refugee management database,\nensuring that this process remains distinct from the registration of an asylum application carried out strictly\nby CNARR.\n\nArticle 31 of the 2020 Law and Article 73 of the 2023 Decree outline that refugees are entitled by the\ncompetent authorities to be issued with civil status documents including birth certificates, death certificates\nand marriage certificates on par with nationals. Furthermore, the specific legal framework on civil status\n[documents consists of the National Civil Status Code and Law No. 008/PR/2013 of 10 May 2013, governing](http://citizenshiprightsafrica.org/wp-content/uploads/2020/11/Tchad-Loi-no-13-08-Etat-Civil-10-mai-2013.pdf)\ncivil status organizations in the Republic of Chad. Under Decree No. 660/PR/PM/MATSP/2015, establishing\nthe modalities of application of the Law of 10 May 2013, all births in Chad are subject to a mandatory\nregistration requirement. In line with this universal principle of civil registration, all foreigners, including\nrefugees and asylum-seekers to whom vital events have occurred in Chad, are allowed to benefit from civil\nregistry services on par with nationals. Additionally, [Ordinance No. 002/PR/2020](https://citizenshiprightsafrica.org/wp-content/uploads/2020/11/Tchad-Ordonnance-002-PR-2020-Etat-Civil-14-fevrier-2020.pdf) on the organization of civil\nstatus in the Republic of Chad has extended the registration delay for births to three months.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "UNHCR-managed refugee management database"}], "vague_data": []}}}
{"input": "1000 500 0 65+ 55-64 45-54 35-44 25-34 18-24 <18 25% 20% 15% 10% 5% 0% 5% 10% 15% 20% 25%\n\n**Source:** Deloitte own elaboration based on the PESEL database as of October 2023\n\n**Chart 5.** Composition of refugee households in Poland\n\n60% 50% Total entries-exits of the Polish-Ukrainian border Pesel data\n\n**Source:** Deloitte own elaboration based on Polish Border Guard Headquarter and PESEL data.", "output": {"entities": {"named_data": [{"text": "PESEL database"}], "descriptive_data": [], "vague_data": [{"text": "Pesel data"}]}}}
{"input": "Immigration can raise not only economic output (i.e., more workers equal more production), but more importantly labour productivity (i.e., more value added produced per worker). Such a result may appear counterintuitive to a simple supplydemand intuition, where an increase in the number of workers lowers the amount of capital per worker thus lowering productivity until firms invest to return the capital-worker ratio to normal, returning productivity to the previous level (Borjas, 2019). Even if that was the case, GDP per person (though not GDP per worker) would still rise because immigrants are typically younger than the native population, which improves the general worker to population ratio. However, an inflow of immigrants can be more than just an increase in labour supply, e.g., immigrants bring new skills to the workforce, extending the scope of specialisation and thus making workers more productive. In fact, economic research from the past decade has found, that immigration improves not just GDP or GDP per person (Ortega and Peri, 2014), but has a causal positive impact for labour productivity (Jaumotte et al., 2016), GDP per capita growth rate (Aleksynska and Tritah, 2015), and total factor productivity (Peri, 2012).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "68.8% 2024-Q2 2021-Q2 67.5% 2022-Q2 40.3 40.3 40.4 40.4 Source: Deloitte own elaboration based of Eurostat data (Labour Force Survey).\n\nSource: Deloitte own elaboration based of Eurostat data (Labour Force Survey).\n\nPart-time Full-time 31 Deloitte has not received data that would be detailed as to citizenship, poviat, sex, age group, occupational group, and ZUS insurance code that would be suitable for econometric approach.\n\n42", "output": {"entities": {"named_data": [{"text": "Labour Force Survey"}, {"text": "Eurostat data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "consistent with previous, similar studies.\nHowever, they should be treated as lowerbound estimates, as we do not allow for the possibility of an increase in the labour force triggering a positive productivity shock (e.g., due to increased specialisation), because there is little data to credibly estimate its size.\n\nA feature of our modelling approach is that the resulting GDP gains are reduced due to increased competition on the labour market. This slightly increases the unemployment rate, by 0.18-0.3 pp in 2023, which corresponds respectively 33-54 thousand additional people being unemployed. This effect also slowed down real wage growth by 0.65-1.15% in 2023.\nIn reality, these negative effects are likely to be compensated by positive productivity gains, in the form of adjustments on the part of native workers (by their occupational upgrading, see papers by Peri and Sparber, 2009; Foged and Peri, 2016) and firms (by skill-biased technical change, see papers by Lewis and Peri, 2015, or Lewis, 2013), as econometric studies find only small effects on native wages, clustered around zero (Peri, 2014).\nThe impact of refugees from Ukraine in", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE For the regional analysis, population weights were applied based on the most up-to-date refugee population figures for each country, ensuring the findings accurately represented the broader regional refugee population. To maintain comparability, the figures for 2023 presented in this report were also re-estimated using survey weights.\n\nThis report utilises the criteria of the Washington Group on Disability Statistics Short Set on Functioning (WG-SS) [7] . The assessment included a comprehensive set of questions covering mobility, vision, hearing, cognition, self-care, and communication. For the purpose of this report, disability is defined as level 3 and above, indicating significant limitations in functioning (‘a lot of difficulty’ or ‘cannot do at all’). For indicators related to chronic illness and vaccination, respondents self-reported whether they or any household members had a chronic illness and whether children in the household had received measles vaccine.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "- 65% in early 2023 with a further 10%\nalready having completed a course. 87% also took part in inclusion courses that were offered. Per the report, since the beginning of the full-scale war,, around one million people have fled to Germany, while Eurostat data on beneficiaries of temporary protection show that there were around 1.17 million Ukrainians under such schemes in Germany [30] .\n\nAmong working refugees there is a significant number of entrepreneurs.\nThe high employment rate of refugees in Poland covers not only employees, but also the self-employed. The available data also shows that refugees from Ukraine in Poland are likely to start their own businesses. ZUS (social security) statistics on insured refugees indicate that around 5% of them have set up a business or are freelancers. Similar results can be gleaned from the MSNA Poland 2023 survey results, which show that slightly more than 5% of respondent households receive income from self-employment or similar activities.\nThis percentage appears to be slightly higher for men, at over 6%, than women.\n\n---\n[30] Eurostat data, https://ec.europa.eu/eurostat/databrowser/view/migr_asytpsm/default/table?lang=en", "output": {"entities": {"named_data": [{"text": "MSNA Poland 2023 survey results"}, {"text": "ZUS (social security) statistics"}], "descriptive_data": [{"text": "Eurostat data on beneficiaries of temporary protection"}], "vague_data": [{"text": "Eurostat data"}]}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE health needs were regionally reported higher among those with disabilities (23%) and higher compared to 2023 (14%). Notably, respondents with a disability in Latvia, Czechia, Bulgaria, Lithuania and Slovakia reported a similar level of access to health care as those without a disability.\n\nUnmet health needs are higher among recent arrivals. Of those who arrived in 2024, 28% reported difficulties in accessing care, compared to 19% of those who arrived in 2023 and 16% of those who arrived in 2022.\n\n**% OF INDIVIDUALS WITH CHRONIC ILLNESS THAT ARE**\n\n**ABLE TO ACCESS TO HEALTH CARE**\n\nWith chronic illness Without chronic illness\n\n**% OF INDIVIDUALS WITH A DISABILITY THAT ARE ABLE TO**\n\n**ACCESS TO HEALTH CARE**\n\nWith disability Without disability Regional Czechia Latvia Moldova Estonia Poland Bulgaria Hungary Lithuania Slovakia Romania (N=6,052)\n\n**12**\n\nRegional Latvia Czechia Estonia Moldova Bulgaria Poland Lithuania Hungary Slovakia Romania (N=5,695)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In practice, access to these financial services is still hindered by the type of identification documents issued by\nCNARR and UNHCR to refugees. The refugee identity cards, not issued by the national competent authority,\nANATS, is often considered an unofficial document in most cases. Efforts to expand the legally recognized\ndocumentation through the provision of biometric identification and a national identification number by\nANATS for refugees would be the solution to these recurring challenges. Other practical challenges persist\nfor refugees in accessing credit, stemming from their inability to meet the financial guarantees and the\nperception that they pose a high risk profile as borrowers. Some refugees, mainly living in the South of\nChad continue to ably access bank accounts, mainly saving accounts, based on the prior recognition of their\nidentity cards by certain financial institutions.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "1. Compared to the [2023 MSNA data](https://data.unhcr.org/en/documents/details/108068)\n2. For the purposes of this analysis defined as 50% of the host country median equivalized disposable incomed. This approach is equivalent to Eurostat’s at-risk-of-poverty (AROP) methodology 3. Defined as the share of the population with an income below the poverty line 4. The poverty rate for the host communities was defined to be equal to Eurostat’s at-risk-of-poverty (AROP) rate calculated for the 50%-of-median-equivalized-income threshold 5. Equivalent to living being at risk of poverty (as per Eurostat) when setting the at-risk-of-poverty threshold at 50% of the national median disposable income after social transfers 6. MHPSS stands for mental health and psychological support\n\n**3**", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "2023 MSNA data"}], "vague_data": []}}}
{"input": "- Co-­‐existence \r activities \r in \r areas \r of \r return, \r including \r through \r working \r with \r CBOs\nfor \r the \r identification \r of \r key \r points \r of \r current/potential \r tensions, \r designing \r of\njoint \r reintegration \r projects, \r and \r conducting \r cultural \r activities \r that \r foster\ntraditional \r values \r of \r consideration \r and \r peace.\n\n- Constructing/rehabilitating \r basic \r facilities, \r such \r as \r health, \r safe \r drinking \r water\nsystems \r and \r sanitation \r as \r well \r as \r improving/expanding \r services.\n\n14", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Note: Data are based on average social security contributions bases in employee-cells, each cell for a specific poviat, sex, age group, and main occupational group. All data are for the 01XX ZUS insurance code (employees). Data for Q2 2022 encompass 6945 employee-cells of Ukrainian refugees joined with likewise cells for Polish citizens, while for Q2 2024 13477 such cells. Ukrainian refugees have been identified by PESEL UKR and Ukrainian citizenship, Poles by Polish citizenship.\n\nSource: Deloitte own elaboration based on ZUS data.\n\nrefugees move to better-paid occupations becomes clearer. Between June 30, 2022, and June 30, 2024, Ukrainian refugees gained an estimated 7% in earnings having shifted towards better paid occupations, pre-war Ukrainians 5%, non-Ukrainian foreigners 4%, and Polish citizens 1%.\n\n**Ukrainian refugees have been slowly**\n\n**closing their wage gap to Polish**\n\n**citizens across all wage levels.** Once\nZUS administrative data on Ukrainian refugees with employment contracts is divided into employee cells based on 380 poviats, 2 sexes, 7 age groups, and 10 main occupational groups (including", "output": {"entities": {"named_data": [{"text": "ZUS data"}], "descriptive_data": [{"text": "ZUS administrative data"}], "vague_data": []}}}
{"input": "Mental health is a significant concern, with particularly high needs in populations fleeing conflict. WHO estimates that one in five people affected by conflict (22.1%) have a mental health condition, including 13.0% with mild, 4.0% with moderate, and 5.1% with severe conditions [4] .\nRefugees may have experienced conflict-related violence and other adversities prior to displacement and likely face current stressors associated with adapting to new environments, languages, and cultures, economic and housing instability, limited social support networks and uncertainties about their future and those left behind in Ukraine. These factors may contribute to mental health and psychosocial problems that can persist for many years if left unaddressed.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**decreases it.** Some evidence shows that\nwhen refugees from Ukraine have access to education, healthcare, and social services, they may be more likely to consider returning home, precisely because they feel more stable and have the resources to make plans. Sohst et al. (2024) found that short-term return intentions were higher in countries offering strong public services and with healthier economies (lower poverty and higher GDP). In short, when people aren’t just surviving but have some breathing room, they’re better positioned to think about going back.\nOn the other hand, host country labour market integration decreases the chances that refugees will be returning to their country of origin. Personal circumstances clearly play a major role. Refugees who are formally employed in their host countries are 12 percentage points less likely to plan a return in the near future than those who aren’t (Sohst et al., 2024). Furthermore, Lewandowski et al. (2025) find that refugees who underwent greater task degradation were more likely to plan to return to Ukraine by 2023, particularly those who initially, in 2022, did not plan to return. So, while public services seem to increase the likelihood of return, employment has the opposite effect, it gives people a reason to stay. Families with children or elderly dependents are also more hesitant, which makes sense given the ongoing uncertainty in Ukraine and school continuity in host country. Refugees with disabilities are even less likely to return, often because of healthcare needs or limited support options. Return is often less about ‘desire’ and more about 'capacity', what in development terms includes social capital, human capital (like education and skills), and even psychological readiness. That capacity is shaped by a combination of public policies and personal circumstance. [6]\n\n---\n[6] Crucial will also be the ‘pull’ factors in Ukraine, which will be determined by the conditions of future peace. The longer the full-scale war continues, the smaller will", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**•** Aleksynska and Tritah (2015) look for economic impacts of immigration in a\n\nsample of 20 developed OECD countries at 5-year intervals during the 19602005 period. They find that a higher rate of immigration by 1 percentage point increases GDP per capita growth rate by 0.3 percentage point. They try to disaggregate this effect in further regressions, finding positive effects for the growth of income per capita, output per worker, and total factor productivity for higher rate of immigration among prime-age workers (25-54 years old), but negative or statistically insignificant for the young (15-24 years old).\nThese estimates are causal, as authors similarly to Jaumotte at al. (2016) quoted above instrument the immigrant shares by estimating them beforehand based on a separate model, which is orthogonal to subsequent GDP growth.\n\n**•** Peri (2012) in a seminal paper models the impact of immigration on total factor", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "3. Economic Opportunities\n\nwhich aims at preventing conflict, enabling resolution and improving the understanding of law and justice.\n\nIn practice, the availability of judicial services, including Court, remains scarce or too distant from refugee\nhosting areas, including camps. The nascent state legal aid services remain constrained in scale and scope,\nfurther exacerbated by the lack of implementation. In addressing the legal and justice needs of refugees\nand asylum-seekers, despite the support provided by UNHCR and its partners for legal aid services, the\npredominant option remains traditional arrangements made under the auspices of local and traditional\nauthorities.\n\n### **3. Economic Opportunities**\n\n**3.1** **Freedom of movement**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Additionally, insights were drawn from the Kenya COVID-19 Rapid Response Phone Surveys (RRPS), [[9]] conducted\n\nbetween 2020 and 2022, which included the Shona as a distinct stratum. The RRPS monitored the impact of the\n\npandemic on vulnerable groups, capturing critical data on employment disruptions, income losses, and food\n\ninsecurity during the crisis.\n\n**The Shona community in Kenya has faced significant socioeconomic challenges, exacerbated by their stateless**\n\n**status and the impacts of the COVID-19 pandemic.** Before acquiring citizenship, Shona households faced a 24\n\npercent higher likelihood of living in poverty compared to the urban Kenyan population and were more likely to\n\nreside in larger, overcrowded households. Although primary school enrollment rates were similar to those of their\n\nKenyan counterparts, many Shona children struggled to transition to secondary education. Limited access to formal\n\nemployment, driven by a lack of legal documentation, has forced many Shona individuals into self-employment or\n\ninformal work. Even with high employment rates within the community, this does not translate into reduced\n\npoverty, as most of the employment is low-income and lacks stability. [[8] ]\n\n**[www.unhcr.org](http://www.unhcr.org/)** 3", "output": {"entities": {"named_data": [{"text": "Kenya COVID-19 Rapid Response Phone Surveys"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Chart 15. Ukrainian refugees wages median net wage by age group**\n\nMonthly net wage (PLN) Percengate of all workers total economy average Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Chart 16. Median net wages of Ukrainian refugees median net wage by sector**\n\nin PLN Percentage of total economy average 126% 15 to 24 25 to 34 35 to 44 45 to 54 55 to 64 15 to 24 25 to 34 35 to 44 45 to 54 55 to 64 Ukrainian refugees All workers Source: Deloitte own elaboration based on SEIS UNHCR survey and GUS data.\n\n**The Ukrainian refugee groups to earn**\n\n**the highest wages compared to the**\n\n**wages in the economy as a whole are**", "output": {"entities": {"named_data": [{"text": "SEIS UNHCR survey"}, {"text": "GUS data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "The \r ongoing \r presence \r of \r armed \r actors \r in \r places \r of \r displacement \r and \r potential \r return\nremains \r a \r key \r concern. \r Communities \r have \r been \r subject \r to \r protection \r risks \r associated\nwith \r the \r presence \r of \r military \r units \r including \r forced \r labour, \r forced \r recruitment \r and \r the\npayment \r of \r “taxes.” \r In \r addition, \r Myanmar \r is \r believed \r to \r have \r a \r large \r number \r of \r children\nin \r armed \r conflict, \r including \r child \r soldiers, \r with \r both \r the \r Government \r and \r various \r non-­‐\nstate \r armed \r actors \r having \r been \r responsible \r for \r the \r recruitment \r of \r minors. \r On \r 27 [th] June\n2012, \r the \r United \r Nations \r Country \r Task \r Force \r on \r Monitoring \r and \r Reporting \r (CTFMR)\nand \r the \r Government \r signed \r a \r Plan \r of \r Action \r with \r regards \r to \r underage \r recruitment \r in \r the\nMyanmar \r Army. \r Procedures \r are \r underway \r for \r the \r systematic \r identification \r and\ndischarge \r of \r verified \r minors \r from \r the \r national \r forces. \r However, \r plans \r of \r action \r with\nnon-­‐state \r armed \r groups \r in \r the \r South-­‐East \r have \r not \r yet \r been \r agreed \r and \r it \r remains \r to \r be\nseen \r whether \r the \r Plan \r of \r Action \r with \r the \r Government \r will \r be \r comprehensively\nimplemented.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "While \r all \r the \r conditions \r and \r safeguards \r for \r an \r organized \r voluntary \r return \r to \r South-­‐East\nMyanmar \r are \r not \r yet \r in \r place, \r positive \r political \r and \r economic \r reforms \r and \r security\ndevelopments \r have \r increased \r momentum \r for \r preparing \r for \r a \r possible \r voluntary \r return\nof \r refugees \r from \r Thailand \r and \r durable \r solutions \r for \r people \r internally \r displaced \r as \r a\nresult \r of \r protracted \r conflict. \r A \r small \r number \r of \r refugees \r are \r reported \r to \r have \r returned\n\n2 ‘Temporary \r shelters’ \r is \r the \r Royal \r Thai \r Government \r term \r used \r to \r identify \r the \r refugee \r camps \r along \r the\nborder.\n\n2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Access to services**\n\n**Since 2020, the Shona community has made significant strides in the enjoyment of rights and access to essential**\n\n**services and social, economic, and financial opportunities.** The acquisition of citizenship has enabled the\n\ncommunity to access critical documentation, with 86 percent of individuals now holding a national ID, citizenship,\n\nor birth certificate. This remarkable progress has facilitated their inclusion in various social and economic\n\nopportunities.\n\n**Access to financial services has also improved significantly.** The proportion of community members with bank\n\naccounts increased from 9 percent in 2019 to 35 percent in 2024, while mobile wallet usage saw a surge from 52\n\npercent to an impressive 97 percent. This suggests that the community has leveraged citizenship to integrate more\n\nfully into the formal financial system, enhancing their economic participation.\n\n**Health insurance coverage has nearly tripled over the past five years.** The percentage of Shona individuals with\n\nhealth insurance rose from 4 percent in 2019 to 11 percent in 2024, compared to 24 percent nationally _._ [[10]] Although\n\nthe current coverage rate remains low, this growth indicates an increasing awareness and ability to access\n\nhealthcare services, possibly due to better employment prospects and social benefits associated with citizenship.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "2. Regulatory Environment and Governance\n\n### **2. Regulatory Environment and Governance**\n\n**2.1** **Normative framework**\n\n[Chad, already a state party to the 1951 Convention relating to the Status of Refugees and its 1967 Protocol,](https://www.unhcr.org/fr/media/convention-et-protocole-relatifs-au-statut-des-refugies)\nand the [1969 OAU Convention Governing the Specifc Aspects of Refugee Problems in Africa, enacted](https://au.int/sites/default/files/treaties/36400-treaty-0005_-_oau_convention_governing_the_specific_aspects_of_refugee_problems_in_africa_e.pdf)\n[a new asylum Law on 31 December 2020 (Loi No. 027/PR/2020 Portant Asile en République du Tchad).](https://www.refworld.org/pdfid/606334e04.pdf)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Consistent with the recent legislation consolidating past practices, CNARR, through its Eligibility Sub\nCommission, remains the primary authority for asylum at first instance. Over the past three years, CNARR\nhas employed prima facie refugee recognition during the registration phase for asylum-seekers from Central\nAfrican Republican hosted in the South of Chad, those from Nigeria hosted in the Western Chad, and equally\nfor those fleeing Sudan, including for non-Chadian persons forcibly displaced since the outbreak of 15 April\n2023. Other asylum-seekers have undergone an individualized RSD procedure handled by CNARR. While\nthere have been some enhancements in asylum legislation, notably with the recent promulgation of the\n2023 Decree aiming to improve the efficiency of individualized RSD procedures, implementation challenges\npersist. Issues include permanent rotation of CNARR staff, inadequate training for CNARR eligibility officers\nin interview techniques, legal assessments and the use of country-of-origin information. Non-compliance\nwith first-instance asylum processing delays stipulated in the asylum legislation is also observed. Despite", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "mine). Women are more likely to earn cash and less likely to work in agriculture after mine\n\nopenings. We find similar results when we analyze the effects at the district level and when we\n\nuse production levels instead of openings and closings of mines. We interpret this as there being\n\nadditional effects of being very close to a mine (within 20 km), beyond the effects from being\n\nin a mining district. No spillovers into neighboring districts are detected.\n\nThe results are in accordance with the results in Kotsadam and Tolonen (2016), who find similar\n\neffects on occupation in mining communities across the whole of Sub-Saharan Africa, and with\n\nAragón and Rud (2013), who find that agricultural productivity in Ghana is reduced by mining\n\nproduction nearby. We find no statistically significant results on wealth and inequality, although\n\nthe results point toward increases in both. The effects on infrastructure are ambiguous; we\n\ncannot detect any better access to flush toilets and radios, and the effects on electricity access\n\nare negative. Further decomposing these effects, we learn that migrant households are less\n\nlikely to have access to electricity (compared with the change among migrant households living", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Net primary school enrolment shows a slight decline but is attributed to changes in the education system rather**\n\n**than reduced access.** The enrolment rate decreased from 81 percent in 2019 to 75 percent in 2024. However, this\n\nis likely due to the adjustment in the age bracket for primary school in Kenya under national education reforms\n\nlaunched in in 2022, which has led to a temporary underestimation of the enrollment rate. Despite this, the Shona\n\ncommunity's access to primary education remains strong and stable.\n\n_Figure 2: Access to essential services, pre- and post-citizenship_\n\n_Source: 2019 Shona socioeconomic survey_ [[8]] _and the authors’ calculation of 2024 survey data._\n\n**[www.unhcr.org](http://www.unhcr.org/)** 5", "output": {"entities": {"named_data": [{"text": "2019 Shona socioeconomic survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "**Immigrants could possess complementary skills that**\n\n**make native workers more productive as they specialise.**\nThese skills do not even need to be advanced to be complementary. Natives are likely to deal better with communications-intensive tasks and have better networking, all of which may be better paid and not easily transferable between countries. OECD (2016) gives an example of a native carpenter, who employs an immigrant to do his previous manual tasks and himself focuses on marketing and business development.\nSuch occupational upgrading has been first shown in a seminal paper by Peri and Sparber (2009) in the USA data, but has been quickly extended to other countries. From this perspective Foged and Peri (2016) look at refugees in Denmark in the 19912008 period. They find that inflow of low-skill refugees caused less educated native workers to pursue less manual-intensive tasks - improving their wages, employment, and occupational mobility. These effects are causal, as the authors exploit the refugee dispersal system, which is orthogonal to economic opportunities.\n\n**Immigrants could enter childcare, elderly care, and**\n\n**housekeeping services, allowing highly educated and**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "USA data"}]}}}
{"input": "Despite the possible gains in wages for wage earners, we note a decrease in the regionally\n\ndeflated total household expenditure (column 5), and a decrease in per capita expenditure on\n\nfood and nonfood items (column 4). The increase in wages but decrease in total expenditure\n\ncan possibly be explained by rising prices and wages in mining communities, where everyone\n\nhas to pay the higher prices but only some (those who earn wages), benefit from a rise in wage\n\nrate.\n\nColumns 6 through 9 of table 12 look at nondeflated expenditure measures for food, housing,\n\nhealth and education, and household energy. [17] We confirm that total household expenditure on\n\nfood decreases (compared with the per capita deflated measure in column (4)), but find that\n\nhouseholds spend more money on housing, transport, and communication, and household\n\nenergy, such as electricity and gas. The electricity and gas expenditure is only for those who\n\nhave any positive expenditure on these, and we saw earlier that electricity access changes with\n\nthe mine. This confirms that, among those who spend anything on electricity, they spend more\n\non it in mining communities.\n\n**Table 12 Using GLSS: Household income and expenditure**\n\n---\n[17] Additional results for recreation and transport and communication are available upon request. The expenditure", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\nlack \r of \r skilled \r personnel, \r facilities, \r basic \r equipment \r and \r supplies, \r including \r in \r terms \r of\npotentially \r life-­‐saving \r reproductive \r health, \r malaria \r prevention \r and \r control \r and \r HIV\nservices.\n\nThe \r education \r sector \r is \r also \r substantially \r underserved \r and \r not \r of \r adequate \r standards,\nwith \r a \r shortage \r of \r teachers \r and \r an \r inadequate \r number \r of \r primary \r schools \r within\nreasonable \r distance \r of \r many \r communities. \r Regular \r school \r attendance \r is \r hampered \r by\neducation \r costs, \r distances, \r illness, \r work \r requirements, \r insecurity \r in \r conflict-­‐affected\nareas \r and, \r for \r ethnic \r minority \r children, \r “language \r barrier”. \r Most \r children \r have \r limited\nopportunity \r to \r continue \r their \r education \r beyond \r primary \r school.\n\nAccess \r to \r safe \r drinking \r water, \r particularly \r in \r rural \r areas \r and \r during \r the \r dry \r season \r is\nuneven \r and \r in \r many \r locations \r insufficient, \r with \r those \r water \r sources \r available \r during \r the\ndry \r season \r located \r far \r away \r from \r human \r dwellings. \r Standards \r of \r sanitation \r are \r very \r low,\nwith \r open \r defecation \r common \r and \r household \r latrines \r less \r than \r international \r standards.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Sample distribution by geographical strata, Poland 5,645 13,420 Jul-Aug UNHCR, IOM followed by random selection of districts, and convenience sampling for household selection.\n\nCSCM, IOM, Romania 1,222 3,485 Jul-Sep UNHCR UNHCR, IOM, Slovakia 819 1,853 Jul-Aug WHO, UNICEF, SHC\n\n**Total** **11,530** **27,302** **Jun-Sep**\n\nSample distribution by geographical strata, and simple random selection of households from cash enrolment lists.\n\nTwo strata (collective sites vs. private accommodation); random selection of districts and convenience sampling for household selection.\n\n### **Limitations**\n\nThe statistical significance of the MSNA results is limited by the non-probabilistic selection of respondents. Moreover, the use of convenience sampling likely led to a larger share of data being collected from more vulnerable households.\n\nThere was also a notably high non-response rate regarding questions related to income and expenditure, which likely resulted in non-response bias. The income module of the MSNA was also materially different from the one employed by EU SILC, which may limit comparability of this data to that of host populations.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "dropping from 33 percent to 21 percent.  The literacy rate has remained constant at 93 percent, reflecting sustained\n\naccess to education. Overall, the Shona community's demographic profile suggests stability and gradual socio\neconomic integration following their acquisition of citizenship.\n\n_Table 1: Demographic characteristics of Shona community in Kenya._\n\n_Source: 2019 Shona socioeconomic survey_ [[8]] _and the authors’ calculation of 2024 survey data._\n\n**[www.unhcr.org](http://www.unhcr.org/)** 4", "output": {"entities": {"named_data": [{"text": "2019 Shona socioeconomic survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Many \r people \r do \r not \r possess \r a \r Citizenship \r Scrutiny \r Card \r (or \r “CSC”) \r either \r because \r they\nlive \r or \r used \r to \r live \r in \r conflict \r areas \r controlled \r by \r ethnic \r armed \r groups \r with \r no\nGovernment \r representation, \r or \r simply \r because \r they \r do \r not \r have \r access \r to \r the\nadministrative \r mechanisms \r that \r issue \r these \r documents. \r Furthermore, \r the \r Government\nin \r the \r past \r limited \r distribution \r of \r CSCs \r in \r border \r areas \r to \r contain \r movement \r of \r people\nlinked \r to \r ethnic \r armed \r groups. \r Very \r few \r IDPs \r held \r CSCs \r before \r their \r displacement, \r and \r it\nmay \r be \r extremely \r difficult \r for \r people \r who \r have \r been \r displaced \r as \r refugees \r or \r IDPs,\nparticularly \r from \r areas \r controlled \r by \r ethnic \r armed \r groups, \r to \r provide \r the \r necessary\ndocumentation \r to \r obtain \r CSCs. \r Additionally, \r persons \r not \r belonging \r to \r one \r of \r the\nofficially \r recognized \r “ethnic \r groups” \r face \r difficulty \r in \r acquiring \r CSCs, \r despite \r the \r fact\nthat \r there \r are \r relevant \r provisions \r available \r for \r them \r under \r the \r Myanmar \r Citizenship\nLaw. \r In \r July \r 2011, \r the \r Immigration \r and \r National \r Registration \r Department \r of \r the\nMinistry \r of \r Immigration \r and \r Population \r initiated \r the \r Moe \r Pwint \r Operation, \r which \r is \r an\naccelerated \r procedure \r to \r issue \r CSCs, \r especially \r in \r areas \r that \r were \r remote \r and/or\ndifficult \r to \r access \r in \r the \r past \r because \r of \r the \r presence \r of \r non-­‐state \r armed \r groups.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Indonesia’s National Refugee Task Force, established in 2019, remains an important Government entity\nin the management of refugee affairs. Deputy V in POLHUKAM is the head of the National Refugee\nTask Force and members include the Ministry of Foreign Affairs and a wide range of security-focused\nactors. Several local refugee task forces operate in provinces hosting refugees and remain active and\nimportant counterparts. UNHCR also works with a range of partners in Indonesia, particularly IOM,\nYCWS, and YKMI in several areas of protection and assistance. In addition, UNHCR works with nongovernmental, civil society and refugee-led organizations, as well as other UN agencies working with\nand advocating for the rights of the refugee population in Indonesia.\n\n**Locations of Persons Registered with UNHCR**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "can promote reconciliation and a sense of national unity and identity. [[11]]\n\n**Acquiring Kenyan citizenship has significantly improved the socioeconomic conditions of the Shona community,**\n\n**enabling them to access essential services, economic opportunities, and social benefits.** Before gaining citizenship\n\nin 2020, the Shona faced numerous barriers due to their stateless status, which excluded them from formal\n\nemployment, financial services, and government programs. Following the acquisition of nationality, the Shona now\n\nenjoy access to legal identity documents, increased livelihood opportunities, better health insurance access, and\n\nfinancial inclusion. These positive changes align with findings in the academic literature, which highlight the\n\nimportance of citizenship in reducing poverty and enhancing human capital by allowing individuals to leverage\n\ngovernment services, engage in formal employment, and contribute more productively to society.\n\n**Citizenship has also enhanced the Shona community’s labor market potential, though employment rates are still**\n\n**recovering from the adverse impacts of the COVID-19 pandemic.** Legal identity has granted many Shona\n\nindividuals the ability to seek formal employment and broaden their economic activities beyond informal self\nemployment. This has enabled the community to slowly rebuild their livelihoods post-pandemic. Nevertheless,\n\nemployment levels remain below pre-pandemic rates, especially for women, reflecting challenges in labor market", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Moreover, Chad developed a national strategic plan for the progressive implementation of universal health\ncoverage from 2017 to 2019, starting with vulnerable populations. Eventually, it should cover all individuals\nresiding in Chad, including refugees. However, the implementation of this plan was disrupted by the\nCOVID-19 pandemic. As of June 2023, its implementation was not yet effective.\n\n**4.3** **Social protection**\n\nState social protection programmes are guaranteed to refugees and asylum-seekers under Article 21 of the\n[2020 Asylum Law. Article 33 of the Law specifies that refugees and asylum-seekers are entitled to the same](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf)\n[treatment as nationals regarding assistance and public relief. Article 77 of the 2023 Decree reiterates the](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf)\nsame.\n\nThe 2016-2020 National Social Protection Strategy (SNPS) faced implementation challenges. Subsequently,\na new SNPS for 2022-2026, developed with support from UNICEF, the World Bank, UNFPA, WFP and FAO,\nis now awaiting validation and government approval. This strategy, distinct from its predecessor, prioritizes\naddressing financial and livelihood security for the most vulnerable, managing risks, reducing vulnerability\nand ensuring access to basic social services for all residents in Chad, including refugees. Notably, it aligns\nwith the Global Compact on Refugees (GCR). The forthcoming strategy will be accompanied by a priority\naction plan.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In terms of economic violence, only 21% of Venezuelan women of working age access the formal\njob market, compared with 42% of men, and the situation is even worst for young women aged\n18 to 26 who are single head of household (13%). [28] Moreover, women in the formal job market\nearn an average salary that is 7% lower than men, a gap that widens up to 32% at higher and post\ngraduate levels. [29]\n\nAs far as physical and sexual violence is concerned, 18% of Venezuelan women and girls do not\nfeel safe in their communities, a proportion that is three times higher in Roraima and Amazonas\nstates, compared with the rest of the country. [30] Among the places that are perceived as most\ninsecure, respondent mentioned: the way to school (44%), community and religious spaces (44%),\nshelters (35%) and their own homes (28%). [31] A recent study also found that in the state of Roraima,\n9% of key informants witnessed some form of sexual violence against children. [32]\n\n_26_ ACNUR (2023), cit. p. 14\n\n_27_ Idem, p.17\n\n_28_ R4V (2024), cit.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The top 5 protection incidents reported in the region are homicide (30 per cent), assault and battery (29 percent),\nextortion of property (16 per cent), destruction of properties (13 per cent), and looting (12 per cent). Also, those\nprotection incidents affected 99.88 percent of Internally displaced persons (IDPs), 0.11 percent of refugees, and 0.01\nper cent of asylum-seekers. The protection incidents affected more males (53 per cent) than females (47 per cent),\nand the protection incidents affected the age group (0 to 17), children, who represent 44 percent of all victims\nreported in September 2022. In addition, the perpetrators of those protection incidents are armed groups (46 per\ncent), host communities (26 per cent), others (23 per cent), and unknown (5 per cent). It is worth mentioning that 1.3\npercent of the regional population, compared to September 2022 regional data, was affected by the protection\nincidents reported in September 2022.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "September 2022 regional data"}], "vague_data": []}}}
{"input": "have a stronger focus on all households’ members, rather than focusing only on women and\n\nyoung children. In addition, they provide more detailed information on labor market\n\nparticipation, such as exact profession (where, for example, being a miner is a possible\n\noutcome), hours worked, and a wage indicator. The data estimate household expenditure and\n\nhousehold income. Wages, income, and expenditure can, however, be difficult to measure in\n\neconomies where nonmonetary compensation for labor and subsistence farming are common\n\npractices.\n\n**4 Empirical Strategies**\n\n**4.1 Individual-level difference-in-differences**\n\nTime-varying data on production and repeated survey data allow us to use a difference-in\n\ndifferences approach. [7] However, due to the spatial nature of our data and the fact that some\n\nmines are spatially clustered, we use a strategy developed by Benshaul-Tolonen (2018). The\n\ndifference-in-difference model compares the treatment group (close to mines) before and after\n\nthe mine opening, while removing the change that happens in the control group (far away from\n\nmines) over time under the assumption that such changes reflect underlying temporal variation\n\ncommon to both treatment and control areas.\n\nWe limit the data to include households within 100 km of a mine location and estimate the\n\nfollowing:\n\n---\n[7] We have not done a synthetic control approach because of limited ability to explore pretreatment trends.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "repeated survey data"}]}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n#### **Model calibration**\n\nWe introduce a positive productivity shock into the Deloitte D.Climate model, reflecting empirical findings that refugee inflows coincided with stronger labour-market outcomes, to offset any potential adverse effects. Although higher employment rates among Ukrainian refugees correlate with improved job and wage outcomes for Polish citizens, we take a deliberately conservative approach in our general equilibrium simulations. While descriptive statistics and econometric estimates point in a positive direction, the available data remain too sparse for firm\n\n**Chart 31. Labour market activity rates**\n\nWomen in 15-64 age group conclusions. [31] On the other hand, a default Deloitte D.Climate model estimation is in line with the previously mentioned canonical model. This yields a 1.35% decrease in wages and a 0.4 percentage point increase in the unemployment rate, which is implausible. Therefore, a positive marginal productivity of labour shock has been added to the model and calibrated to eliminate the impact on the unemployment rate throughout the simulation years of 2022, 2023, and 2024. While it is possible that the unemployment rate could fall despite the influx of Ukrainian refugees due", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "health care access, as has been observed in Tanzania (Rhee et al., 2018).\n\nThe analysis shows that mining has created structural shifts in labor markets, and that it has\n\nreduced infant mortality rates. However, along with increased wage rates, we find that\n\nhousehold level expenditure on housing and energy increases. In addition, the migrant\n\npopulation may have lower living standards with less electricity and a higher disease burden\n\namong children. We have no information where the migrant population moved from, and we\n\ncannot tell whether they have migrated to the area to benefit from the industry, or whether they\n\nwere part of a relocation program due to the mining. One caveat is that these observed\n\ndifferences among migrant households in mining communities and non-mining communities\n\ncould stem from untestable selection, as we do not observe the migrant households before the\n\nmigration. Regardless of the motivation behind the migration decision, the policy\n\nrecommendation is to ensure policies are in place to ensure sustainable living conditions in this\n\ngroup.\n\nThese district level findings should be placed in the context of seminal work by Caselli and\n\nMichaels (2010) who found weak increases in living standards in Brazilian municipalities after", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The Indonesian Ministry of Education, Culture, Research and Technology issued a Circular Note in\n2019, with amendments in 2022, allowing refugees and asylum seekers to access primary and\nsecondary formal and informal education in the national education system. Enrollment in local schools\nrequires a valid UNHCR document and competency in Indonesian language. UNHCR and our partners\nprovide preparation classes, covering Indonesian language and basic skills (reading, writing, and\nmath), as well as additional support (tuition fees, transport allowance and school supplies) to assist\nchildren to access local schools. IOM similarly supports refugee children living in IOM\naccommodations. Challenges to increase enrolment rates among refugee children include limited\ninterest on the part of refugee children to learn Indonesian, financial barriers, resettlement\nexpectations, the inability to obtain official documentation certifying completion of school (due to the\nlack of an Indonesian identification number), and inadequate physical space within classrooms to\naccommodate non-Indonesian children. As a result of these and other challenges, as of September\n2024, only 769 refugee children (of approximately 3,000 school age children) are enrolled in\naccredited national schools.\n\n### **Health**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n**TOP 5 REFUGEE EMPLOYMENT SECTORS SPLIT BY**\n\n**EMPLOYEE BACKGROUND (2024)**\n\n**TOP EMPLOYMENT BARRIERS FOR EMPLOYED REFUGEES**\n\n**(2024)**\n\nEmployed in the same sector in Ukraine Manufacturing Hospitality Construction Wholesale IT Lack of local language knowledge Cannot find a job with decent pay Few jobs for my skills or experience Lack of jobs with a suitable schedule Degree or skills recognition issues Source: Survey data 17% 15% 35% 5% 2% 4% Employed in a different sector in Ukraine 16% 9% 5% 24% 6% 4% 1% Note: Percentages are based on the distribution of relevant responses in the survey Source: Survey data Moreover, in the latest survey round, nearly 35% of employed refugees identified inadequate pay, a lack of positions that match their skill set, and challenges in having their qualifications recognized as barriers to employment. All of these answers also suggest a mismatch between qualifications and job placement.\nConsistent with the findings on having to shift to jobs outside of previous employment backgrounds, working women reported the above employment barriers more frequently than men, supporting the hypothesis that they may be facing underemployment more often.\n\n# **Methodology**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "Survey data"}]}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE The survey methodology relied on a single household member (the respondent) answering health and MHPSS questions on behalf of all household members, which may have limited the ability to fully capture the unique needs and experiences of each individual. Furthermore, the questionnaire itself was constrained to a limited range of questions, which may have restricted the depth of data collected on complex and multifaceted topics, such as mental health and psychosocial well-being. Additionally, sensitive topics such as mental health and sexual and reproductive health may have been underreported, depending on the respondent’s comfort level and the presence of others during the interview.\n\n**8**\n\n# Sample demographics\n\nThe sample comprises 8,720 households, encompassing 19,803 individual household members. The population pyramid for this sample indicates that the majority of individuals are women aged 35–59 (25%), followed by women aged 18–34 (14%). To minimize potential biases due to gender imbalances, indicators were disaggregated by gender and age, allowing comparisons within consistent age groups. No significant gender disparity is observed in the sample in children; consequently, indicators related to child health were not impacted. The sample included 194 pregnant women and 247 breastfeeding women.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Power BI Desktop Solutions Pathways Action Plan Protection and Conflict Sensitivity\n-\nBaardheere: A high occurence of violence and sexual and gender-based violence (SGBV) perpretrated by non-state actors as well as private individuals, highlighting a complicated conflict landscape. There is a need for strengthened protection services and provision of basic services.\n-\nBaydhaba: Findings suggest high rates of sexual and gender based violence (SGBV) took place, and were mostly perpretrated by non-state actors and private individuals. There is a need for enhanced protection from violence, and provision of basic services such as food and shelter.\n-\nBerdaale: Notably high incidents of violence and SGBV were recorded, mostly by non-state actors and private individuals, highlighting localized conflict dynamics. There is a need for strengthened protection for vulnerable groups.\n-\nDoolow: Escalating conflict was highlighted, with a high occurrence of violence and SGBV perpetrated by non-state actors, alongside private individuals.\nThere is a need for strengthened security services.\n-\nKismayo: A high level of violence and killings were reported, perpetrated by private actors, which suggests the prevalence of opportunistic violence with unaffiliated private groups exploiting insecurity. There is a need for strengthened law enforcement capacity, and community-based protection mechanisms.\n-\nBanadir (including Daynile and Kahda): Very high displacements were recorded due to violence, SGBV, and killings with a combination of actors involved - predominantly unaffiliated private individuals and non-state actors.\nThere is a need for strengthened law enforcement capacity and a prioritization of basic services as well as livelihoods support to meet the needs of displaced communities.\n-\nXudur: High rates of SGBV, exploitation and child protection violences were recorded, with penetrators identified as unaffiliated private actors, suggesting a limited state presence. There is a need to strengthen community mechanisms which are commonly relied upon by affected populations. There is also a need to improve access to food and shelter, and address exploitation through targeted protection measures.\nIn 2024, UNHCR conducted several assessment and analysis activities focused on protection and conflict sensitivity analysis. Key findings from these activities in the eight locations referred to in this report are detailed below. Note that analysis from the whole year is summarised.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**situation over the past year.** In\nthe 15-59/64 age group, employment rate of Polish citizens stood at 75% in Q2 2024 according to Eurostat, slightly more than the 69% for Ukrainian refugees in the SEIS 2024 survey and 73% when adjusted for a different sex and age structure. In the 15-64 age group, the employment rate of Ukrainian male refugees was 67% while that of Polish citizens in Q2 2024 was 77%. For women, the rates for Ukrainian refugees and Polish citizens are closer in the 15-59 age group (female retirement age in Poland is 60) with 70% for refugees and 72% for Poles. Visible", "output": {"entities": {"named_data": [{"text": "SEIS 2024 survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "### TABLE OF CONTENTS September/ October 2023 report Venezuela\n\n**Operational highlights**\n\n4 Humanitarian Program Cycle 2024: Humanitarian Needs Overview (HNO) Process\n\n4 Coordination with other platforms, subnational Clusters, ICCG, and Partners\n\n5 Accountability for Affected Populations (AAP) WG\n\n5 GPC Townhall\n\n5 La Carnada Play\n\n6 Annual TiP Bulletin 2022-2023\n\n6 Food Security and Livelihoods (FSL) and Trafficking in Persons (TiP)\n\n6 Monthly Meetings of the WGTiP\n\n6 Protection Mainstreaming Training\n\n8 Training on Mixed Migration and Durable Solutions\n\n8 Reporting Transition to 345W\n\n8 Focal Group Discussions with LGBTIQ+ Organizations for\n\nThematic Protection Analysis Update (PAU)\n\n10 Mental Health and Psychosocial Support (MHPSS)\n\nCoaching and Training of Trainers (ToT)\n\n10 Impact Stories of Series: September and October\n\n11 Protection Service Mapping Revisions and Edits\n\n11 Participation in the Gender ToT for Government Officials\n\n11     September’s Monthly Meeting with Partners\n\n12 Second Allocation for Venezuela Humanitarian Fund (VHF)\n\n12 Protection Monitoring Tool (PMT)\n\n**14** **Protection response: performance and funding**\n\nHumanitarian Response\n\n**3**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "2. Regulatory Environment and Governance\n\nrelated to refugees. CNARR continues to be responsible for coordinating the protection of refugees. Its tasks\ninclude safeguarding the well-being of refugees and asylum-seekers, managing issues related to them (such as\nidentification and registration, document issuance and camp administration), and maintaining communication\nwith relevant ministries. These ministries encompass Foreign Affairs, Security, Defence, Justice, Finance, Social\nAffairs, Human Rights, Economy, Education, Health and Water. CNARR also provides advice to the MSPARGL\non sustainable solutions. Challenges faced by CNARR in coordinating efforts among various stakeholders and\ndonors persist, mainly due to a shortage of stable, qualified human resources and limited financial capacity. In\nthese circumstances and as specified by Article 55 of the [2023 Decree, UNHCR continues to support CNARR](http://2023 Decreehttps://www.ecoi.net/en/file/local/2091861/645b938a4.pdf)\nfor the refugee response coordination using the established refugee coordination model. Coordination\nmeetings with external partners are jointly chaired by the government counterpart (CNARR or prefect) and\nUNHCR. CNARR maintains a presence in all refugee camps and most refugee hosting areas.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Power BI Desktop Climate Change & Resilience Enhancing the climate adaption and resilience of IDPs and host communities is a priority.\nStrengthening their ability to cope with and recover from current and future shocks, such as conflicts or climate change disasters, is essential for sustainable development and reducing the risk of further displacement.\nPathway #5:", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "UNHCR conducts case management for survivors of gender-based violence and refers them to support\nservices with their consent. Assistance may include medical care, psychosocial support, temporary\nsafe accommodation, assistance to report to police and in any legal process, and interventions to\nprotect impacted children, if required. UNHCR and YCWS run a GBV hotline that can be accessed by\nsurvivors of GBV 24 hours/day.  Since July 2023, UNHCR has conducted a GBV prevention program\nthat seeks to increase awareness of the root causes of GBV and to build the capacity of the community\nto prevent and respond to GBV by Engaging Men in Accountable Practices (EMAP).\n\n### **Legal Support**\n\nUNHCR provides support to refugees and asylum seekers experiencing legal protection concerns,\nincluding individuals seeking international protection at air and sea borders who are unable to access\n\nUNHCR / 1 November 2024 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Note:_ This figure shows the mine locations and the district in which the mines are located.\n\nThe baseline specification is shown in the following equation:\n\n𝑌���         - 𝛽�𝑎𝑐𝑡𝑖𝑣𝑒_𝑑𝑖𝑠𝑡𝑟𝑖𝑐𝑡��         - ∝�� 𝑔� �𝜆𝑋�� �𝜀���      �3�\n\nThe outcome for individual _i_ in district _d_ in time period _t_ is regressed on district and year fixed\n\neffects, an indicator for whether the individual lived in an active mine district at the time of the\n\ninterview, and time varying individual-level factors. Even though the treatment is defined at the\n\ndistrict level, we use individual-level data to be able to control for individual- level factors and\n\nexplore heterogeneity at the individual level. The standard errors are, however, clustered at the\n\ndistrict level to take into account the interdependence induced by the higher-level treatment.\n\nSince the treatment variable is at the same level as our district fixed effects, the _β1_ coefficients\n\nare directly interpretable as difference-in-differences estimates. That is, they capture the\n\ndifference between mining districts and nonmining districts before and after mining starts.\n\nIn estimating the district-level effects of mine openings on birth outcomes, we control for birth\n\nyear fixed effects instead of survey-year fixed effects, as we are interested in the effect of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "individual-level data"}]}}}
{"input": "Children from households with members living below the poverty line were also found to significantly less frequently attend school. The enrollment rate in local schools for 5–17-year-olds in this group amounted to 72% as opposed to 84% for households with a higher income. Moreover, close to 20% of these children did not participate in online learning either, thus being completely disengaged from formal education.\n\nFinally, one in five refugee households in the poverty group reported having to reduce the number of meals eaten per day over the last week to cope with a lack of food or money to buy it. Roughly the same proportion had to borrow money or rely on friends and relatives at least once over the same period for sustenance. Almost one in three households resorted to reducing food intake for adults, so that small children could eat. When asked to assess their income level qualitatively, 26% of respondents living in poverty indicated that this amount is insufficient to cover their food needs as opposed to just 3% in the higher income group.\n\n**7**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "reintegration. The employment rate for women dropped from 72 percent in 2019 to 61 percent in 2024, suggesting\n\na slower recovery in sectors traditionally dominated by women. Overall, the Shona community’s gradual\n\nemployment recovery indicates the value of citizenship in building economic resilience and highlights the need for\n\ncontinued support to ensure inclusive recovery for all members of the community.\n\n**The Shona experience provides valuable lessons for addressing statelessness and promoting inclusive**\n\n**development for other stateless communities globally.** Gaining citizenship has been transformative for the Shona,\n\ngranting them access to a range of socioeconomic benefits and reducing their vulnerability to poverty and exclusion.\n\nThis case underscores the importance of grant of nationality to stateless populations and its potential to unlock\n\neconomic and social opportunities that drive sustainable development. As more countries around the world seek\n\nto address statelessness through legislative changes and the expansion of citizenship rights, the Kenyan experience\n\nwith the Shona can serve as a model. By providing legal identity and addressing structural barriers, policymakers\n\ncan empower stateless communities to participate more fully in their economies and societies, leading to improved\n\nlivelihoods, social cohesion, and economic growth. These findings have broader implications for the many stateless", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The paper contributes to the growing literature on the local effects of mining. Much of the\n\nacademic interest in natural resources is focused on country-wide effects, and this research\n\ndiscusses whether the discovery of natural resources is a blessing or a curse to the national\n\neconomy. Natural resource dependence at the national level has been linked to worsening\n\neconomic and political outcomes, such as weaker institutions, and more corruption and conflict\n\n(see Frankel 2012 and van der Ploeg 2011 for an overview). While all these effects can have\n\nhousehold-level implications, fewer analyses have, thus far, analyzed the geographic dispersion\n\nof such impacts. A recent literature on the local and subnational effects of natural resources\n\ncontributes to the understanding of such effects (for example Aragón and Rud 2013, 2015;\n\nAxbard et al., 2016; Benshaul-Tolonen 2018, 2019; Caselli and Michaels 2013; Corno and de\n\nWalque 2012; Fafchamps et al. 2016; Kotsadam and Tolonen 2016; Loyaza et al 2013;\n\nMichaels 2011; von der Goltz and Barnwal 2019; Wilson 2012). A growing number of papers\n\nexplore the mining industry, in particular, see Aragón, Chuhan-Pole, and Land (2015) for an\n\noverview. We contribute to this literature by showing the importance of analyzing local level", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "to credit, which is critical for expanding small businesses or starting new ventures. These changes underscore the\n\ntransformative role of citizenship in enabling the Shona community to overcome previous barriers to economic\n\nparticipation and build sustainable livelihoods.\n\n**Moreover, citizenship has also led to increased access to training and educational opportunities, while reducing**\n\n**discrimination in the workplace.** Over a third of the Shona noted that they have had more opportunities for training\n\nor education since becoming citizens, helping them to build skills and enhance their employability. Another 30\n\npercent reported experiencing less discrimination at work, which has contributed to more positive employment\n\noutcomes and a more inclusive work environment. Overall, these improvements indicate that legal recognition has\n\nbeen pivotal in unlocking the economic potential of the Shona community, setting the stage for greater\n\nsocioeconomic mobility and long-term development.\n\n- **Box 2: Findings from focus group discussions**\n\nMany of the survey results are consistent with findings from qualitative focus group discussions, including\n\nchallenges associated with securing economic opportunities. The Shona community faces challenges predominantly\n\nstemming from low education levels and the absence of formal qualifications to which the lack of nationality and", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "of intent to employ foreign workers. The results are similar to the OLS estimation; however, when the second instrument is used without the first one, it gives a higher result. Instrumental variables regressions show that in 2023, a 1 percentage point higher employment share of Ukrainian refugees caused a PLN 70 higher wage growth (0.7 pp.) when instrumented by school pupils' share, PLN 132 (1.4 pp.) when instrumented by 2019 Ukrainian workers distribution, and PLN 75 (0.8 pp.) when both instruments were used. That said, the results should be treated with caution, as the instruments used may not be sufficiently exogenous to allow for fully credible causal inference.\n\nThe early analysis by Gromadzki and Lewandowski (2023), mentioned previously also found a statistically significant effect of Ukrainian refugees on earnings. In their estimation, the share of the Ukrainian refugee population had a small positive and statistically significant relationship with the earnings of Polish women at a 0.1 level.\nTheir results for foreign women were also positive, albeit smaller and lacking statistical significance.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "2019 Ukrainian workers distribution"}], "vague_data": []}}}
{"input": "English for Speakers of Other Languages programme in Massachusetts. The policy targeted all immigrants, including those who had lived in Massachusetts for several years, with data for 2008–2016 and 4,700 individual lottery applicants. Authors found a causal effect, with annual earnings increasing by USD 2,400. These earnings gains generated additional tax revenue that produced a 6% return for taxpayers.\nSchmid (2023) studied African refugees who applied for asylum in Switzerland between 2008 and 2017. He exploited the random assignment of refugees to French, German, and Italian cantons, as well as their prior language knowledge (e.g. French speakers placed in French or German speaking cantons). The results showed that language proficiency more than doubled the employment level in the first five years after arrival.\n\n**The econometric model estimated**\n\n**in the SEIS UNHCR survey shows**\n\n**substantial wage gains from Polish**\n\n**language proficiency for Ukrainian**\n\n**refugees.** Deloitte has estimated an\neconometric model incorporating individual income determinants of Ukrainian refugees. Our study has", "output": {"entities": {"named_data": [{"text": "SEIS UNHCR survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "REGIONAL BUREAU FOR SOUTHERN AFRICA\n\n**2022 VOLUNTARY REPATRIATION IN SOUTHERN AFRICA REGION**\n\nAs of 30 September 2022\n\nMAP OF VOLUNTARY REPATRIATION WHERE THE FLOW INVOLVE 5 POCs OR MORE\n\nKEY FIGURES\n\n15,042\n\nTotal Individuals\nrepatrieted since\n\nJanuary 2022\n\nIndividuals repatrieted\n\n**within Southern Africa**\n\n**Region** since January\n\n2022\n\n6,786 8,256\n\nIndividuals repatrieted\n\n**from Southern Africa**\n\n**Region** to other countries\noutside of the region since\n\nJanuary 2022\n\nVOLREP* WHERE THE FLOW INVOLVE 5 POCs OR MORE\n\nTRENDS\n\nMONTHLY REPATRIATION SINCE JANUARY\n\n**3,874**\n\nANNUAL REPATRIATION SINCE 2019\n\n*VolRep = Voluntary Repatriation  PoCs = Persons of Concern Source : UNHCR PRIMES   Author : DIMA/RBSA    Data sources: UNHCR PRIMES.  For more information or to contribute, please contact UNHCR RBSA DIMA (rsarbdima@unhcr.org)", "output": {"entities": {"named_data": [{"text": "UNHCR PRIMES"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Ultimately, refugees provide the Polish economy an additional boost both in total product and demand. That allowed for an increase in real GDP. This situation was especially beneficial for public finance.\nAlthough the influx of refugees was costly at the start, the additional revenue they provided was more than enough to compensate for this [48] . The cost for local labour force due to increased competition was in most part mitigated due to a tight labour market.\n\nAs such, the increase in unemployment was much lower than increase in employment.\nTo maximise the positive impact of refugees on economy, policies helping their integration into the labour market that both allow their maximal employment as well minimise market mismatch between demand for specific skills and their abilities are crucial. The second part of this recommendation, achieved either through improvements in utilisation of skills of refugees or trainings giving them abilities demanded by the labour market, is integral as it should lower costs for the local labour force.\n\n---\n[48] Model treats general government sector as a whole, as such cost and income internal structure may differ creating institutions with financial loses while", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The 2024 SEIS equivalized [8] disposable income data indicates that just over one in five refugees (23%) residing in the region are living in poverty [9] . This figure is almost double that of host country nationals (12%), implying a large gap in economic vulnerability. Compared to 2023, poverty rates have decreased substantially (from 36% [10] ), suggesting an overall improvement in the economic well-being of Ukrainian refugees over time.\n\n**REFUGEE VERSUS HOST POVERTY RATES BY COUNTRY**\n\nUkrainian refugees (2024) Host country nationals (2023) Bulgaria Czechia Hungary Moldova Poland Romania Slovakia Estonia Latvia Lithuania Region Note: Poverty rates for all countries apart from the Republic of Moldova are based on a calculation that follows Eurostat’s at-risk-of-poverty (AROP) methodology with the at-risk-of-poverty threshold set at 50% of the national median disposable income after social transfers. Refugee disposable income has been computed based on survey data. For the Republic of Moldova, the poverty threshold was taken to be the 4Q23 absolute poverty line reported by the National Bureau of Statistics of Moldova.\n\nSource: Survey data, [Eurostat,](https://ec.europa.eu/eurostat) [National Bureau of Statistics of Moldova, SAG estimates](https://statistica.gov.md/en)", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "2024 SEIS equivalized disposable income data"}], "vague_data": [{"text": "survey data"}]}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE Respondents who faced constrains in accessing care were more likely to identify seeking health care as reason for visiting Ukraine in all countries, with the exception of Latvia.\n\n**REASONS SEEKING HEALTHCARE FOR VISIT TO UKRAINE**\n\n**BY OBTAINED CARE STATUS**\n\nUnable to access health care Able to access health care Hungary Poland Czechia Bulgaria Romania Estonia Slovakia Lithuania Moldova Latvia (N=3,596) Respondents with a chronic illness were more likely to cite accessing health care as reason for visiting compared to those without (33% vs 23%). Among households with a member who has a disability, healthcare access was the primary reason for visiting (38%), compared to 26% for households without a member with disability. There were no immediate gender differences concerning the prevalence of healthcare as a reason for women and men to visit Ukraine.\n\n**16**\n\n### **Access to sexual** **and reproductive** **health services**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Poland is studied in an early paper by Gromadzki and Lewandowski (2023), who find no effect on earnings, employment, and unemployment rate of native or other immigrants, except an actual slight positive impact on the wages of native women.\nEven in a conservative scenario that assumes negative effects of labour market competition in the form of higher unemployment and slower real wage growth, an increase in the labour force translates into larger personal incomes and higher private consumption, which results in a larger tax revenue. These effects were strengthened by an influx of capital from abroad.\n\n###### In total, the general government revenue increased by 0.8-1.1% in 2022 and 1.05-1.45% in 2023. In monetary terms, this amounts to 10.1-13.7 billion PLN in 2022 and 14.7-19.9 billion PLN in 2023.\n\nIf estimates quoted by a government offical of public expenses on refugees of around 15 billion PLN in 2022 and 5 billion in 2023 [13] are accurate, we can conclude that they were more than offset by the additional tax revenue. In the long-term, refugees should increase yearly government revenue by around 0.85-1.3%.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n## **1.** Ukrainian refugees in Poland\n\n##### The large influx of refugees since February 2022, added to a hefty and growing Ukrainian migrant population in Poland (1.1). Refugees have changed the demographics of the local Ukrainian residents, with most of them being women and children and many households led by women alone (1.2). In the past year, refugee household income sources have become more Poland-based (1.3).\n\n#### **1.1 Influx since February 2022**\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Chart 1. Poland-Ukraine border movement balance and registered/active PESEL data**\n\n**Prior to the 2022 conflict in Ukraine,**\n\n**the population of Ukrainians in**\n\n**Poland was already significant and**\n\n**on the rise, but the exact number of**", "output": {"entities": {"named_data": [{"text": "registered/active PESEL data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "**GDP.** This is the amount that would be\nlost, should refugees “disappear” from the Polish economy. It is mainly driven by a higher number of workers in the economy, but also accounts for increased productivity brought about by more specialization. Considering all aspects, the overall impact of the refugees has been predominantly positive, and it moved the Polish economy to a higher growth path.\nRefugees contribute to the economy slightly more than their employment share – they increase the labour supply as both workers and entrepreneurs and expand demand as consumers. The rise in productivity due to more specialization across the labour force further boosts the economy. The impact of refugees is lowered by a temporary decrease in the capital-to-labour ratio (companies need time to invest in equipment and machines to match the rise in the number of workers), as well as an increase in competition on the labour market.\n\n**The figures are higher than those in**\n\n**the previous Deloitte (2024) report,**\n\n**which – due to scant data available**\n\n**at the time – did not account for the**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**the most in the last two years.** The\ndata as of June 30, 2024 shows that 38% of Ukrainian refugees worked in elementary occupations, much more than pre-war Ukrainians (25%), non-Ukrainian foreigners (18%), and Polish citizens (10%).\n\nMSNA Jul-Aug 2023 SEIS May-Jun 2024 MSNA Jul-Aug 2023 SEIS May-Jun 2024 Source: Deloitte own elaboration based on MSNA and SEIS UNHCR surveys conducted in July-August 2023 and May-June 2024.\n\nWhile the share seems least favourable among Ukrainian refugees, their situation improved the most in the two years since June 30, 2022 (by 10 pp. compared with 9 pp. for the pre-war Ukrainians, 2 pp. for non-Ukrainian foreigners and 1 pp. for Polish citizens). On the other hand, in Q2 2024, managers and specialists, the two highest paid occupational groups, comprised 8% of both Ukrainian refugees and pre-war Ukrainians, 22% of nonUkrainian foreigners (who include many", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "MSNA and SEIS UNHCR surveys"}, {"text": "MSNA"}], "vague_data": []}}}
{"input": "The standard of living of refugees from Ukraine may be significantly lower than natives, even at similar incomes due to their lack of housing capital. 87% of the population in Poland resided in owneroccupied housing in 2021 and 2022, according to Eurostat. As most refugees from Ukraine do not possess housing of their own in Poland, they need to rent in a relatively tight market, especially when they reside in large metropolitan areas that offer the most opportunities. Initially, in the first month after the outbreak of the full-scale war in Ukraine, the number of renting offers in the OLX and Otodom portals dropped by approximately 60%, though it later returned to previous levels.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "widespread among Shona households, and access to external support was minimal. Although employment levels\n\nbegan to recover a year later, they remained below pre-pandemic levels, underscoring the prolonged adverse\n\nimpact of the pandemic on this already vulnerable community. [[9]]\n\n_Figure 1: Labor force status after the COVID-19 outbreak (18-64 years)_\n\n_Source: Kenya COVID-19 Rapid Response Phone Surveys (RRPS)_ _[[9]]_\n\n**Two rounds of household surveys taking place over five years before and after the transition of the Shona in**\n\n**Kenya from statelessness to citizenship help us to understand this community – and present one of the first**\n\n**socioeconomic pictures of the impact of citizenship on the welfare of stateless persons.** Between 2019 and 2024,\n\nthe median age of Shona household members remained unchanged at 18 years, underscoring a predominantly\n\nyouth demographic profile. Gender distribution is even, showing only a marginal change, with the female population\n\nincreasing slightly from 49 percent to 50 percent. Average household size has risen modestly from 4.9 to 5.4\n\nmembers, which may reflect greater household consolidation or socio-economic stability following their\n\nnaturalization. The most notable shift is the significant reduction in the proportion of female-headed households,", "output": {"entities": {"named_data": [{"text": "Kenya COVID-19 Rapid Response Phone Surveys"}], "descriptive_data": [], "vague_data": [{"text": "household surveys"}]}}}
{"input": "For productivity two options were tested.\nFirstly, neutral impact: no shock to productivity. Secondly, lower productivity of workers from Ukraine negatively impacting total labour productivity. These shocks were calibrated to match the difference in data between refugees income from labour in UNHCR survey and average wage in Poland from Statistics Poland weighted by refugees share in total workforce.\n\nAs one period in the model is set to one year and refugees started coming to Poland by the end of February 2022 it was assumed that their impact on economy started being felt starting from II quarter of the year.\nAs such shocks were set so that 3⁄4 of shocks were calibrated to data from 2022 and 1⁄4 to data for 2023 [56] .\n\n51 Computational General Equilibrium.\n52 Global Trade Analysis Project, [GTAP Models: Current GTAP Model (purdue.edu).](https://www.gtap.agecon.purdue.edu/models/current.asp) 53 Region combined from: Russia, Belarus, Ukraine, Moldova, Czechia, Slovakia, Hungary, Romania, and Bulgaria.\n54 All shocks are percent deviations.\n55 [Oversight of fnancial market infrastructures (bank.gov.ua)](https://bank.gov.ua/en/payments/oversite)\n\n---\n[56] E.g. for total increase in number of workers of 350 thousand around 262.5 thou. was set to have happened in 2022 while rest in 2023.", "output": {"entities": {"named_data": [{"text": "UNHCR survey"}, {"text": "Statistics Poland"}], "descriptive_data": [], "vague_data": []}}}
{"input": "**macroeconomic benefits.** To illustrate\nthe macroeconomic impact of public intervention, we have assumed that half of the current language gap is addressed, so that the share of working refugees not speaking Polish fluently falls from 82% to 41%. Assuming that the productivity Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n#### **4.5 Recommendations**\n\n##### Language courses\n\n**Ukrainian refugees in Poland earn higher wages when they**\n\n**have higher language skills.** There is substantial scientific evidence\nthat language courses improve labour market outcomes of refugees and other migrants. Financing language courses for refugees would generate positive impacts for them and the economy. Courses should be available not just at beginner to intermediate levels, but also for advanced speakers who want to become proficient and gain access to high-skill jobs.\n\n##### Occupational licensing deregulation\n\n**While some occupational licensing rules with regard to**\n\n**Ukrainian citizens were relaxed, further and permanent easing**\n\n**would benefit both the Polish economy and the inclusion of**\n\n**refugees.** The low-hanging-fruit are the restrictions referring to\ncitizenship only – rather than actual expertise or language skills – which could be scrapped altogether.\n\n##### Active Labour Market Policies\n\n**Active Labour Market Policies (ALMPs) should focus on**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\n- Assistance \r is \r co-­‐ordinated \r and \r complies \r with \r principles \r of \r neutrality \r and\nimpartiality \r as \r well \r as \r humanitarian \r standards. \r  \r Donor \r support \r also \r converges\nwith \r co-­‐ordination \r efforts.\n\n- A \r valid \r Letter \r of \r Understanding \r (LOU) \r between \r UNHCR \r and \r appropriate \r line\nministries \r will \r remain \r in \r effect \r for \r the \r duration \r of \r UNHCR’s \r activities \r and \r could\nbe \r amended \r as \r necessary \r should \r an \r organized \r voluntary \r repatriation \r operation\nbe \r launched.\n\n**10. \r PROPOSED \r ACTIVITIES**\n\nRecognizing \r and \r emphasizing \r the \r need \r for \r all \r durable \r solutions \r decisions \r to \r be \r designed\nand \r implemented \r with \r affected \r communities, \r and \r in \r consultation \r with \r relevant\nauthorities \r and \r non-­‐state \r actors, \r UNHCR \r will \r ensure \r that \r displaced \r populations \r as \r well\nas \r communities \r of \r origin \r and \r return \r are \r equipped \r to \r participate \r fully \r in \r the \r assessment,\ndesign \r and \r implementation \r of \r all \r interventions \r in \r support \r of \r durable \r solutions, \r using \r an\nage, \r gender \r and \r diversity \r mainstreaming \r approach.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "instance, report significantly more instances of racism compared to other South American refugees\nand migrants. [12] This exacerbates barriers to accessing a broad range of rights and services [13] and\nleads to greater vulnerability to both low skilled and temporary jobs, particularly when compared\nto Venezuelans who arrived in Brazil under similar circumstances. [14]\n\n##### Protection Risk II\n\n**Access to dignified housing.** In Brazil, a significant proportion of refugees and other forcibly\ndisplaced people can only afford precarious and overcrowded dwellings, located in impoverished\nand marginalized communities, often controlled by organized crime. [15] According to UNHCR´s\ndata, only 15% of refugees have secured tenure right to housing and\\or land, 27% live in physically\nsafe and secure settlements with access to basic facilities, and 54% feel safe walking alone in their\nneighborhood after dark. [16] In comparison, 65% of the Brazilian population owns the house in\nwhich they live - although 14% lacks the documentation to prove tenure rights [17] - 72% lives in\nphysically safe and secure settlements, [18] and 52% feels safe walking alone in their neighborhood\nafter dark. [19]", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Two per cent of surveyed Venezuelan households reported that at least one member had been\ndeceived, manipulated, coerced into debt, or received false promises intended to force them to\ntravel or migrate. [34] Additionally, one per cent of households reported at least one of its members\nbeing held against his\\her will by someone other than the country´s authorities, which may\nsuggest the possibility of human trafficking. [35]\n\nWomen and girls are particularly vulnerable to exploitation for various purposes of human\ntrafficking, including sexual exploitation, domestic forced labor, illegal adoption, and organs\nremoval. [36] Refugee women and girls in Brazil sometimes have to resort to survival sex, or cash-inhand domestic labor to make a living in Brazil, which increases their exposure to human trafficking\nnetworks. [37] In addition to these risks, domestic workers face numerous safety and health hazards\nrelated to their tasks and the environment they work in. These include chemical and ergonomical\nhazards, but also psychosocial risks, including violence and harassment, which are pervasive in the\nsector. The impact of these risks is amplified when domestic workers provide their services in the\ninformal economy, which is the case for most refugees and other forcibly displaced populations in\nBrazil. [38]", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The refugee inflow had a different demographic composition than the pre2022 economic migration. It primarily included working age women (41%) and children (40%). [5] Refugees from Ukraine did not plan to move, and many had special needs. In October 2023, nearly half of all refugee households included a person with a chronic illness, and some 10% included one with a Washington Group level 3 disability. Over a third included a single parent and a fifth an elderly person. [6] Despite these difficulties, refugees began entering the labour market surprisingly quickly – attaining an employment rate of 28% in May 2022 and 65% in November 2022 among working age persons (NBP, 2023) –\n\n##### **753 thousand** Ukrainian workers, including 225 thousand refugees, had registered for social security by September 30, 2023.\n\n**Situation of Ukrainian refugees on the**\n\n**labour market in Poland**\nUkrainian refugees, despite war trauma and other difficulties, have quickly become a part of society as **consumers,**\n\n**employees, entrepreneurs, and**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Table 10 Summary statistics for bottom 40% of women**\n\n(1)          (2) (3)        (4)\n\nfar from a mine close to a mine\nbefore        during before       during\n\nnot working 0.188 0.183 0.200 0.162\nservice & sales 0.340 0.203 0.179 0.222\nprofessional 0.018 0.005 0.014 0.006\nagriculture 0.362 0.530 0.490 0.539\nmanual labor 0.091 0.079 0.117 0.072\nearning cash 0.876 0.855 0.879 0.901\nwork all year 0.852 0.859 0.879 0.838\n\n_Note:_ Column (1) is bottom 40% of sample at 20 to 100 km from a nonactive mine.\nColumn (2) is bottom 40% of sample at 20 to 100 km from an active mine.\nColumn (3) is bottom 40% of sample within 20 km of a nonactive mine.\nColumn (4) is bottom 40% of sample within 20 km of an active mine.\n\nRegression results comparing these four groups are presented in panel B (urban) of Annex table\n\n3. The results suggest that women in the bottom 40 percent are more likely agricultural workers\n\nin mining communities than elsewhere, but also more often service sector workers. They are\n\nless likely to work in manual labor, less likely to work all year, but more likely to earn cash for", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "panel B shows the effects of increased production in the survey year. There is no evidence of\n\nspillovers in the sense that there is a similar effect in neighboring districts. In fact, most\n\ncoefficients point in the opposite direction for mining and neighboring districts indicating, if\n\nanything, a shift in employment from neighboring districts to the producing ones.\n\n**8 Conclusions**\n\nGhana has a long history of gold production and has recently been experiencing its third gold\n\nrush, during which annual gold production skyrocketed. It was the first gold rush the country\n\nhas experienced as an independent nation, and it brings hope of improving the lives of its\n\ncitizens. Natural resource extraction is often argued to have detrimental effects on countries,\n\nhowever, and the so-called natural resource curse may imply that resource wealth is harmful to\n\nsocial development and inclusive growth. We use rich geocoded data with information on\n\nhouseholds and mining production over time to evaluate the gold boom at the local and district\n\nlevels in difference-in-differences analyses.\n\nMen benefit from direct job creation within the mining sector, and women seem to benefit from\n\nindirectly generated jobs in the service sector (statistically significant within 10 km from a", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "geocoded data"}], "vague_data": []}}}
{"input": "Altogether 42% of respondents have visited Ukraine at least once since February 2022. Regionally, the second most common reason for visiting was to access healthcare services (28%), following visits to relatives (57%). The proportion of those visiting for healthcare varied significantly by country, with respondents in Hungary (40%), Slovakia (37%), and Romania (36%) showing the highest rates, while it was lower in Lithuania (19%), Latvia (13%), and Moldova (10%). These findings align with previously reported higher unmet healthcare needs in Hungary (22%), Slovakia (21%), and Romania (28%), suggesting that seeking healthcare in Ukraine serves as a coping strategy to address these unmet needs.\n\n**% OF HOUSEHOLDS WHO CITED SEEKING HEALTH CARE AS**\n\n**REASON TO VISIT UKRAINE**\n\nSpent savings Reduced essential health expenditure Reduced essential education expenditure Purchased food on credit Migrated / became displaced Sold household assets Engage in high risk job Sold productive assets Sold house or land School-aged children labour Withdraw children from school (N=8,720) 37% 13% 7% 6% 5% 4% 4% 3% 2% 2% 1% Hungary Romania Slovakia Bulgaria Poland Estonia Czechia Lithuania Latvia Moldova (N=3,596) 18% 11% 11% 41% 37% 35% 33% 29% 29% 27%\n\n**15**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "advantage of capturing the intensity of mining production. Since it is somewhat unclear when\n\nmining production spills over to other types of employment, we use two measures of mining\n\nproduction. Panel A of table 13 shows the results of mining production in the period before the\n\nsurvey, including the survey year, on female employment, and we see that mining production\n\nleads to less agricultural employment but more employment in services and sales, as well as in\n\nprofessional work. Panel B shows that the effects are larger but not as precisely estimated for\n\nthe yearly measure. That they are larger is not surprising, since a 10-ton increase one year is\n\nmuch more than a 10-ton increase over a longer time period. The precision is also probably\n\nlower since it is unclear what year the production spills over to other activities. In any case, we\n\nsee that the effects are similar across these two specifications. [18]\n\n---\n[18] The effects for infant health and infant mortality are also stronger when we add production levels (results", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Power BI Desktop Legal Documentation, Housing, Land, & Property (HLP), and Access to Justice Providing necessary documentation and ensuring access to justice, housing, land, and property rights are essential for IDPs. Legal documentation is often necessary to access basic and financial services and secure employment, whilst tenure security and housing and land rights are critical for achieving permanent housing solutions to displacement.\nPathway #4:", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "It is also important to highlight that there were slight differences in the questionnaire across countries.\nNot all questions were consistently included in all country-level surveys, and some answer options were individually adjusted. To mitigate the impact of these differences, the regional analysis focused on data that could be matched. Certain indicators that may have been available by country have thus been excluded from this assessment.\n\nLastly, the survey was conducted during the summer months, coinciding with both host country and Ukraine school holidays. This period often sees many households temporarily visiting Ukraine, which impacted the accessibility of households and posed challenges in meeting targets, particularly in certain countries and geographic locations.\n\n**11**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The most common reported barrier to accessing MHPSS services was not believing that one needed support (36% in women, 34% in men), followed by not knowing where to go (31% in women; 29% in men). One in six (16%) of respondents reported adopting a “wait-and-see” approach. Other barriers included language barriers (14%), lack of time (10%), inability to afford services (7%), lack of service availability (5%), stigma (4%), long waiting time (4%),\n\n**24**\n\nDid not believe need support Did not know where to go Wait and see Language barrier Lack of time (N=1,682)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The findings on disability, chronic illness, and vaccination are based on self-reports and were not verified against medical records, which may impact their accuracy.\n\nA high non-response rate was observed for sensitive questions related to mental health, psychosocial well-being, protection, income and expenditure which could affect the completeness of the data. Additionally, the survey results for certain indicators, such as infant and young child feeding and SRH barriers, should be interpreted with caution due to the small sample size or low response rates. As a result, some indicators could not be further analyzed to assess how factors such as gender, age, disability, or place of residence impact access to health and MHPSS services.\n\nIt is also important to note that there were slight differences in the questionnaire across countries and years, such as adjustments to answer options.\nTherefore, the regional trend analysis was limited to questions that were consistently used across all participating countries and years to ensure comparability. Furthermore, certain indicators were excluded from the regional analysis due to insufficient sample size or the unavailability of data across all countries.\n\n7. [https://www.washingtongroup-disability.com/question-sets/wg-short-set-on-functioning-wg-ss/](https://www.washingtongroup-disability.com/question-sets/wg-short-set-on-functioning-wg-ss/)\n\n**7**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Despite the improved legal framework and the free issuance of birth certificates within the stipulated period,\nchallenges in physically accessing civil registration centres, along with a persistent lack of awareness\nregarding legal obligations surrounding births, contribute to the overall low rates of birth registration in\nChad.\n\nIt is worth noting that there has been an increase in the birth registration rate from 15 per cent in 2020 to\n26 per cent in 2023. The strategic partnership between UNHCR and government agencies responsible for\nissuing birth certificates, specifically the Directorate of Political Affairs and Civil Status (APEC until 2020) and\nANATS since 2021, has facilitated the issuance of birth certificates to over 150,000 refugee children and\nchildren from host communities in refugee hosting areas.\n\n**2.5** **Justice and security**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Source: Deloitte own elaboration based on GUS and ZUS data. All continuous variables have been regressed in first differences to account for non-stationarity Polish citizens employment rates and registered unemployment rates. For details see the Online Technical Appendix.\n\n39 2021-Q2 2022-Q2 2023-Q2 2024-Q2 2021-Q2 2022-Q2 2023-Q2 2024-Q2 Males Males Source: Deloitte own elaboration based Source: Deloitte own elaboration based of Eurostat data (Labour Force Survey). of Eurostat data (Labour Force Survey).\n\nFemales of Eurostat data (Labour Force Survey). Females 38", "output": {"entities": {"named_data": [{"text": "Eurostat data (Labour Force Survey)"}, {"text": "Labour Force Survey"}], "descriptive_data": [{"text": "ZUS data"}], "vague_data": [{"text": "Eurostat data"}]}}}
{"input": "A steady inflow of migrants could be observed in the last decade since 2014, when armed conflict erupted in Eastern Ukraine. As the Ukrainian economy suffered and its currency lost value, many Ukrainians came to Poland looking for work. Most of them came on a guest worker basis, enabled by a law from 2011, that allowed Ukrainians and five other nations to work in Poland for 6 months during a year without a work permit, based on employers' declaration. This was a circular migration, in which they returned to Ukraine once the 6 month period expired.\nIn effect most stayed in Poland for less than twelve months and therefore were not included in the resident population or other national population estimates.\nA National Bank of Poland research paper estimates that between 2014 and 2018, between one and two million Ukrainian workers arrived in the country (Strzelecki, Growiec and Wyszyński, 2022).\nHard data on the number of Ukrainian workers in Poland before 2022 are limited 12", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**XVI. Participation in the Gender**\n\n**ToT for Government Officials**\n\n**As part of the efforts of the Gender**\n\n**Technical Working Group of Miranda**\n\n**(“Mesa** **de** **Genero”)** **to** **support**\n\n**strengthening of local government,**\n\n**the Protection Cluster through the**\n\nProtection Assistant, supported the\n\ndelivery of a ToT on Gender Equality\n\n_b.Fundación Proyecto Maniapure (FPM)_\n\n_(October):_ FPM, a PC partner, imple\nments integrated protection, and WASH\n\nstrategies in Amazonas and Bolivar. The\n\nPC, in coordination with FPM staff, vis\nited the state of Amazonas to showcase\n\nFPM's impactful work in the monthly\n\nimpact stories series.\n\nThe main axis of the organization\n\nrevolves around a community model that\n\ncenters the mental and physical health\n\nas a human right. Their work has been\n\ndistinctive and their projects of great\n\nimpact to the most vulnerable groups,\n\nsuch as the indigenous communities of\n\nthe Venezuelan Amazonia.\n\nThe PA visited the community of Valle\n\nLindo in the municipality of Atures in the\n\nstate of Amazonas, where he was able to\n\ninterview several persons of interest who\n\nparticipate in the foundation's programs,\n\nand in particular those people who were\n\nparticipating in community sensitizations\n\nand trainings on the prevention of TiP", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "5. Cross Sectors\n\n**c.** **Land:** Access to land for sustainable agricultural activities, which is crucial for fostering refugee’s self\nreliance remains challenging.\n\n14 R E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **R E P U B L I C O F C H A D**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "migrant households in mining communities with migrant households elsewhere, and the null\n\nhypothesis would be similar trajectory over time. If we reject the null, we cannot distinguish\n\nbetween selective migration to mining communities and the impact of the mining. The\n\nnonmigrant analysis can plausibly reflect similar households over time, with the limitation of\n\nselective outward migration. We believe inward migration to mining areas to be more common\n\nthan outward migration (in line with Fafchamps et al., 2016).\n\nDiarrhea is a major concern in many developing countries. Diarrheal diseases are, in part, a\n\nmatter of infrastructure, where access to clean water and proper sanitation are important\n\ndeterminants. To further understand the effects on diarrhea, we look at the difference between\n\nmigrants and nonmigrants and the effects by distance (Figure 5). There are, in fact, large\n\ndifferences between the migrant and the nonmigrant populations. Among nonmigrants, a mine\n\nopening is associated with large decreases in incidence, whereas for migrants, the opposite is\n\ntrue. Considering all children between 0 km and 20 km of an active mine, children born to", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Alongside the large-scale, capital-intensive mining industry in Ghana, there is an artisanal and\n\nsmall-scale mining sector (ASM). ASM activities were legalized in 1984, when the state\n\nloosened its monopoly on gold mining. In Ghana, as in many other African countries, the sector\n\nis an important employer (ILO 1999). It is estimated that around 1 million people in Ghana\n\nsupport themselves with revenues from ASM activities.\n\nThe sector is associated with several hazardous labor conditions, however. This includes child\n\nlabor, mercury exposure, and risk of mine collapse (Hilson 2009). The ASM and the large-scale\n\nmining sector sometimes thrive side by side, but sometimes competing interests lead to conflict\n\nbetween the two sectors, such as around Prestea, where domestic _galamsey_ miners (informal\n\nsmall-scale miners) have been in conflict with the multinational concession owner (Hilson and\n\nYakoleva 2007).\n\nIn this analysis, we focus solely on large-scale mining. We understand, however, that small\n\nand large-scale operations may be geographically correlated. Assuming that the start of a large\n\nscale mine does not affect the likelihood or viability of artisanal and small-scale mining, it is\n\nnot a threat to our identifying assumptions. However, should ASM respond to large-scale", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "1. [Ukraine Refugee Situation ( accessed 12 Dec 2024)](https://data.unhcr.org/en/situations/ukraine)\n2. [Ukraine Situation: Regional Refugee Response Plan 2025](https://www.unhcr.org/europe/publications/regional-refugee-response-plan-2025-2026) 3. https://www.consilium.europa.eu/en/press/press-releases/2024/06/25/ukrainian-refugees-council-extends-temporaryprotection-until-march-2026/ 4. Charlson, F., van Ommeren, M., Flaxman, A., Cornett, J., Whiteford, H. and Saxena, S., 2019. New WHO prevalence estimates of mental disorders in conflict settings: a systematic review and meta-analysis. The Lancet, 394: 240-248.\n5. Eurofound (2024), Social impact of migration: Addressing the challenges of receiving and integrating Ukrainian refugees, Publications Office of the European Union, Luxembourg\n\n**5**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "age migrant married cohabiting divorced fertility woman partner\nactive*mine 0.263 0.028 0.025 0.018 -0.003 0.030 -0.036 -0.003\n(0.510) (0.042) (0.027) (0.029) (0.017) (0.115) (0.031) (0.030)\n\n_Note:_ Robust standard errors clustered at the DHS cluster level in parentheses. All regressions control for year and\ndistrict fixed effects, urban dummy, age (not column 1), and years of education (not columns 6 and 7). Active is\nactive status of mine in the survey year. *** p<0.01, **p<0.05, *p<0.1.\n\n**5.1 Employment outcomes**\n\nUsing the difference-in-differences approach (equation 1), we estimate results on occupation,\n\nchild health, and inequality. First, panel A of table 4 indicates that women in active mining\n\ncommunities ( _active*mine_ ) are insignificantly more likely to work in service and sales and less\n\nin agriculture, and 1.7 percentage points less likely to work as professionals (statistically\n\nsignificant). There is no change in the likelihood that she is not working. These 5 categories\n\nstem from the same occupational variable in the DHS data, and are mutually exclusive. The\n\nsurveyed individual is told to report their main occupation. The coefficients can therefore be\n\ninterpreted as relative increases of each specific sector. Women are more likely to earn cash for", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "DHS data"}], "vague_data": []}}}
{"input": "of establishing a theater group with an\n\nexperimental line of work.\n\nLa Carnada, an immersive and\n\ndocumentary-style theatre production,\n\naims to raise awareness about victims\n\nof Trafficking in Persons (TiP), focusing\n\non sexual and labour exploitation. It\n\nsheds a light on contexts where digital\n\nmedia, domestic violence, and deceptive\n\nopportunities pose significant risks,\n\nparticularly for women and girls. As\n\npart of the French-Venezuelan Festival\n\n**5**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In 2022, 15,402 persons have been repatriated voluntarily thus far, with 2,805 persons repatriated in September.\nThe largest group of returns was from Zambia to the DRC, with 2,159 persons repatriated in September. Further,\nthere has been notable movements from Angola to the DRC in September, where, 47 families of 143 persons were\nrepatriated to destinations in the DRC such as Kassai Province, Kinshassa, Kwilu Province and Goma.\n\nFrom January to September 2022, 4,497 individuals of 1,063 cases were submitted for resettlement consideration.\nAmong these cases, half were male and the other half were female with 57 per cent being children under age 18.\n\nIn the same period, 2,067 individuals departed for resettlement. A half of the departed cases were male and another\nhalf were female, similarly to submitted cases. Most persons have been considered for resettlement to the United\nStates (3,417). The highest number of those departed also headed to the United States (1,285). In terms of country of\nasylums, the highest number of submitted applications were from Malawi (1,438) and Zambia (1,367). Congolese\n(DRC) is the nationality with the highest number of submissions (3,618) and departures (1,729).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "antenatal at least 1 doctor midwife has health died\nPANEL A. # visits antenatal attended attended card 12 months\n\nactive\n0.759*** 0.026 0.055 0.125*** 0.039 -0.085***\ndistrict\n(0.244) (0.022) (0.115) (0.033) (0.059) (0.031)\n\nN 9,245 9,245 9,462 9,462 11,047 9,270\n\nR-square 0.242 0.121 0.160 0.154 0.161 0.138\n\nsmall\n\nat birth, the child was\naverage\nlarge height weight weight\n\nPANELB. size size size for age for age for height\n\nactive\n0.066 0.078 -0.148 -6.333 -23.676** -20.080\ndistrict\n(0.057) (0.085) (0.090) (18.753) (9.364) (13.428)\n\nN 11,837 11,007 11,007 9,646 9,646 9,851\n\nR-square 0.041 0.061 0.060 0.199 0.163 0.073\n\nin the last 2 weeks, had\nPANEL C. fever cough diarrhea\n\nactive\n0.016 0.010 0.058\ndistrict\n(0.057) (0.035) (0.036)\n\nN 10,849 10,883 10,887\n\nR-square 0.052 0.046 0.055\n\n_Note:_ Robust standard errors clustered at the district level in parentheses. All regressions control for year and\ndistrict fixed effects, urban dummy, age, and years of education. Active is active status of mine in the survey year.\nPanel b, columns 1, 2, and 3 show size at birth. Panel B, columns 4, 5, and 6 show anthropometrics (new WHO)\nin standard deviations. *** p<0.01, **p<0.05, *p<0.1.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "migrant mothers are 6.9 percentage points more likely to have suffered from diarrheal diseases\n\nin the two weeks prior to the start of the survey.\n\nTo further understand these effects, we decompose them by distance bins in a spatial lag model\n\n(bottom two graphs in figure 5). It becomes evident that, from a high-level incidence (dashed\n\nline) among the original local population (panel A of figure 5), the mine has brought substantial\n\nreductions in diarrheal incidence (as shown by the blue line). In the migrant population, the\n\nincidence is actually higher after mine opening than before, and the likelihood increases by 6.9\n\npercentage points. The spatial lag model in panel B of figure 5 reveals that much of the effect\n\nis driven by a spike in incidence 10 to 20 km away from the mine center point. If more migrants\n\nmove to the area because of the mine, they will be less settled, and health outcomes can\n\ndeteriorate, on average, within that population. Nevertheless, we should be careful in\n\ninterpreting the effects this way. The mine-induced migration, which we partly capture here,\n\ncould be different from the migration happening further away. The deteriorating status of", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The data also shows that poverty [5] has a very tangible effect on living conditions and protection risks. This group feel less safe, less secure in term of accommodation tenure, more frequently misses out on needed healthcare, more often has children out of school, and is much more frequently forced to resort to skipping meals because of lack of funds. In addition, vulnerable populations, such as older adults and individuals with disabilities or MHPSS [6] needs exhibit significantly higher poverty rates when compared to the refugees overall.\nThese connections are important to bear in mind when designing government, development, and humanitarian support programs.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "We suggest interpreting the local effects as being additional to the district-level effects; that is,\n\nthe mine affects the mining district predominantly through the fiscal channel, and local mining\n\ncommunities mainly through employment generation, and other localized factors. Overall, the\n\nresults are more robustly estimated at the district level than at the individual level, and we find\n\nno indications of positive spillover effects across districts. This is in line with a public spending\n\nhypothesis, where mining districts benefit more than adjacent non-mining districts through the\n\nfiscal revenue channel, since 10 percent of mining royalties are redistributed to mining districts.\n\n**2 Gold mining in Ghana**\n\nGhana has a long tradition of gold mining and has produced a substantial portion of the world’s\n\ngold for over 1,000 years (see Hilson [2002] for an extensive overview of gold production in\n\nGhana). During colonial British rule, the country was named the Gold Coast Colony, and gold\n\nproduction was booming. The first gold rush occurred between 1892 and 1901, and the second\n\nafter World War I. Gold production decreased at the dawn of independence in 1957, and\n\nremained low until the 1980s. Over the last 20 years, Ghana has been experiencing its third gold", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "employer sponsorship (immigrants come following a job offer – popular in Poland), family reunions (immigrants have family ties to a citizen abroad – like often in the USA) or point systems (immigrants fulfil certain characteristics judged by the state as valuable – like in Australia), refugees as involuntary migrants may not possess any such characteristics. Additionally, they may suffer from war trauma and be subject to policies that impede their labour market integration (like temporary labour bans or dispersals described in the previous chapter). This translates into lower employment and wages of refugees, which are key characteristics in terms of economic impacts. Moreover, their spending needs due to a sudden shift in living situation may be disproportionally higher, while their propensity to save lower as their future situation is more uncertain, resulting in the need to finance their consumption using capital generated outside the country e.g.\nsavings from their home countries.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Most Ukrainian refugee households**\n\n**are led by women alone.** According\nto the 2024 Socio-Economic Inclusion Survey (SEIS), 67% of Ukrainian refugee households are led by women without adult partners. When changes are compared to the 2023 edition, the MultiSector Needs Assessment (MSNA) survey, 5% of households include a person with disability, down from 10% previous year, and 48% include a chronically ill person, compared to 49% in 2023. Furthermore, average household size is 2.4 persons (compared to 2.7 previous year), 57% include children (compared to 52%), and 6% include a pregnant or breastfeeding mother (same as previously; UNHCR, 2025a). Only 15% of households are nuclear families with a working age man and woman with children.\n\n**Chart 5. Ukrainian refugee households’ demographic composition**\n\nwith one child with two or more children Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Table 1. 10 poviats with most Ukrainian refugees** **Chart 6. Local population shares of Ukrainian refugees**\n\n**1. Warsaw** 109,705\n\n**2. Wroclaw** 53,901\n\n**3. Cracow** 33,057\n\n**4. Poznan** 23,991\n\n**5. Gdansk** 17,829\n\n**6. Lodz** 15,902\n\n**7. Szczecin** 14,318\n\n**8. Poznanski** 14,028\n\n**9. Pruszkowski** 12,206", "output": {"entities": {"named_data": [{"text": "2024 Socio-Economic Inclusion Survey"}, {"text": "MultiSector Needs Assessment"}], "descriptive_data": [], "vague_data": []}}}
{"input": "From Roraima, the Government implements a voluntarily internal relocation program\n(interiorização) to facilitate the socio-economic integration of refugees and migrants. As of\nOctober 2024, over 141,000 Venezuelans have been relocated to some 1,000 municipalities\nacross other Brazilian states. The continued influx of Venezuelans into Brazil – which have been\non the rise since 2023 – has required the Government and the humanitarian community to\ncontinue focusing on the humanitarian response in Roraima, while moving toward the integration\nof “Operacao Acolhida” within the regular national protection system, reducing duplications and\nensuring the sustainability of the response.\n\nIn addition to Venezuelans refugees and migrants, Brazil hosts individuals from various countries,\nincluding from Cuba, Haiti, India, Sri Lanka, Vietnam, Nepal and Bangladesh; which places\nadditional strain on local protection networks, particularly in border states and cities with\ninternational airports, in the absence of a national response mechanism beyond “Operacao\nAcolhida”.\n\nUNHCR / October, 2024 8", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "UNHCR is committed to ensuring that refugees and asylum seekers have access to lifesaving and lifesustaining health services. To achieve this, UNHCR continues to advocate with the Ministry of Health\nfor the inclusion of refugees in the national health system, including enabling access to national health\ninsurance, working towards the achievement of SDG 3 (Good Health and Well-Being). All registered\nasylum seekers and refugees have access to low-cost primary health care at the local Community\nHealth Centers (PUSKESMAS), managed by the Government of Indonesia. Individuals requiring\nemergency or advanced health treatment may be financially supported by UNHCR through our health\npartner YCWS, within the parameters of established guidelines and budgetary restrictions. UNHCR\ncoverage is limited to critical interventions, mental health services, immunization, natal care, and\n\nUNHCR / 1 November 2024 5", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "professions (physicians, dentists, nurses, and midwives) have opened to migrants and refugees to reduce shortages, and while the shares for all of them stand at just 0.9% compared to 1.9% for Polish citizens, the gap is actually very narrow for physicians and dentists, who constitute 0.7% of Ukrainian refugees and 0.8% of Polish citizens. In legal professions (legal counsels, barristers, notaries, and bailiffs), the gap remains wide, although in addition to occupational licensing, the likely causes may be the differences between the Polish and Ukrainian legal systems as well as new entrants’ struggles with attracting clients due to advertising restrictions. In effect, just 0.02% of Ukrainian refugees work in legal professions, compared to 0.4% of Polish citizens. There are also high contrasts across the remaining regulated professions, which employ 0.8% of Ukrainian refugees and 3.3% of Polish citizens. These are construction engineers (0.02% Ukrainian refugees), pharmacists (0.01%), and psychologists (0.09%), compared to the following shares for Polish citizens: 0.26%, 0.19%, and 0.18%, respectively.\n\n**One of the most effective forms**\n\n**of support offered to refugees**\n\n**and other immigrants in terms of**\n\n**employment and earnings to be found**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The primary data for this report come from a comprehensive 2024 socioeconomic survey conducted by UNHCR\n\nwhich recontacted households which were initially surveyed in 2019, prior to the Shona acquiring nationality. The\n\nfollow-up survey aimed to capture the transformative impact of citizenship on the Shona community in terms of\n\nemployment, education, income, and access to essential services, while also incorporating new modules on social\n\ncohesion, community engagement, and civic participation to better understand the broader integration of the Shona\n\ninto Kenyan society. The 2024 survey provides rich insights into the Shona’s post-citizenship journey and the\n\nchallenges and opportunities they face as newly recognized citizens of Kenya.\n\nThe findings are complemented by the 2019 household survey of the Shona community, conducted jointly by\n\nUNHCR and the World Bank [[8]] establishing a baseline of the Shona community’s socioeconomic conditions while\n\nthey were still stateless. This study revealed significant disparities in access to services and opportunities compared\n\nto Kenyan nationals, highlighting the detrimental effects of statelessness on employment, financial inclusion, and\n\neducational attainment. These findings informed policy recommendations that ultimately contributed to the\n\nrecognition of the Shona as Kenyan citizens in 2020-21, providing a crucial foundation for evaluating their post\ncitizenship outcomes.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "2019 household survey of the Shona community"}, {"text": "2024 socioeconomic survey"}], "vague_data": []}}}
{"input": "Mobile network operators still accept refugee identity cards issued by CNARR as valid proof of identity.\nRefugees without an identity card must still be vouched for by those who possess one to enable SIM card\nregistration. Through their phone numbers, refugees have access to payment and money transfer facilities\noffered by telecommunications operators. Asylum-seekers still do not have the right to acquire a SIM card\nwith the asylum-seeker certificate.\n\n10 R E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **R E P U B L I C O F C H A D**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In the absence of comprehensive national refugee laws and national RSD processes, UNHCR\nundertakes refugee status determination (RSD) in Indonesia. As asylum-seekers have access to the\nsame rights and services as refugees in Indonesia, UNHCR uses RSD strategically for individuals with\nan immediate third country solution which requires refugee recognition (resettlement and some\ncomplementary pathways), cases with heightened protection concerns, and cases presenting with\nissues that need to be clarified through the RSD process. UNHCR also conducts RSD as part of its\nemergency response in the context of boat arrivals to identify those in need of international\nprotection.\n\n### **Child Protection**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Gender disparities are also evident in labor force metrics. The labor force participation rate [19] for women is notably lower at 59% compared to 71% for men. Furthermore, 35% of women not in the labor force cite household responsibilities as their primary engagement, a stark contrast to the 6% reported by men. Although the difference in the unemployment rate is less significant, a gender gap is still discernible – this indicator stands at 15% for women versus 12% for men.\n\n### **Methodology**\n\nEach country adopted a unique sampling approach to their respective surveys, dependent on factors such as the availability of sampling frames and information regarding population distribution by\n\n---\n[19] Also defined here for the 15+ age group", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "occupations and perform the same tasks, the native workers do not change their occupations and tasks, while firms do not adjust (at least in the short term).\nIn effect, immigrants grow output, but slightly lower wages. This is the case in the modelling performed (Chapter 3), as well as in the NBP general equilibrium modelling exercise for the pre-2022 Ukrainian workers 2013-2018 performed by Gradzewicz, Jabłonowski, Sasiela, and Żółkiewski (2021). Conversely, Peri (2014) surveys 270 econometric estimates from 27 studies published over the 1982-2013 period on the impact of immigration on native wages. He shows that effects for a very large immigrant inflow of 10 percentage points (five-times larger than the refugees from Ukraine share in Poland) on native wages range from -1% to +1%, with most estimates clustered around zero, from -0.1% to +0.1%. Similarly, Gromadzki and Lewandowski (2023) examine econometrically the monthly impact of refugees from Ukraine inflow from January", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**General SRH Services Access**\nAcknowledging that 63% of the Ukrainian refugees are women and girls, with 34% of the total refugee population being women in reproductive age between 15- 49 of age, the survey added a focus to explore access and barriers to sexual and reproductive health (SRH) services for women. SRH services include family planning; prenatal and postnatal care, safe delivery including Emergency Obstetric and Newborn Care (EmONC); clinical management of rape; prevention, detection and treatment of reproductive tract infections, sexually transmitted infections and HIV; and referrals to higher level obstetric care or specialized SRH services.\n\nAcross the region, 5% of women reported to have faced barriers in accessing SRH services, though access level varies by country. In Latvia and Bulgaria, only 1 % and 2% of women respectively reported barriers, indicating good access to SRH services. However, in Lithuania and Romania 9% and 6% of women respectively reported barriers in accessing SRH services.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n# Mental Health and Psychosocial Support (MHPSS)\n\n### **Reported mental** **health and** **psychosocial** **problems**\n\nRegionally, 23% of individuals reported experiencing mental health and psychosocial problems that affect their daily functioning, with 36% of households reporting at least one member affected. This is an increase compared to 2023, when 19% of individuals and 30% of households reported mental health and psychosocial problems. There are notable regional variations in reported MHPSS needs, with the percentage of individuals with such needs ranging between 13% (Czechia) and 33% (Romania). In 2023, Czechia also had the lowest and Romania the highest percentage of mental health or psychosocial problems on individual and household level. Stigma surrounding the disclosure of mental health challenges within the Ukrainian community likely means that the actual prevalence of mental health and psychosocial problems may be underreported.\n\n**% OF INDIVIDUALS EXPERIENCING MENTAL HEALTH OR**\n\n**PSYCHOSOCIAL PROBLEMS BY COUNTRY**\n\nRegional Romania Lithuania Poland Bulgaria Hungary Slovakia Estonia Moldova Latvia Czechia 23% 33% 27% 26% 25% 24% 21% 20% 18% 17% 13% (N=8,540)\n\n**% OF HOUSEHOLDS WITH AT LEAST ONE MEMBER WITH**\n\n**MENTAL HEALTH OR PSYCHOSOCIAL PROBLEMS BY YEAR**\n\n**AND COUNTRY**\n\n2023 2024 Regional Romania", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n**Living in a vulnerable household is associated with higher poverty risks**\n\nJust like last year, members of households with vulnerabilities were found to more likely be living in poverty than the general refugee population. Almost half of individuals living with an older adult (age 65+) reported an equivalized disposable income below the poverty threshold. For individuals living with household members with a disability or members with MHPSS needs [11] these rates stood at 41% and 27%, respectively. Gender of the head of household, however, was not found to have a significant impact on the poverty rate. Mixed gender (at least one male and one female head) was associated with higher income, though likely due to increased chances of multiple breadwinners being present in the household.\n\n**REFUGEE POVERTY RATES BY VULNERABILITY CHARACTERISTIC AND GENDER OF HEAD OF HOUSEHOLD**\n\nNo Yes Female Male Mixed Head of household gender Older adult Household (65+) present member with a disability present Source: Survey data, SAG estimates Household member with MHPSS needs present\n\n**Refugee housing expenses are on average much higher than for nationals, which implies an**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "Survey data"}]}}}
{"input": "Deloitte (2024). Analysis of the impact of refugees from Ukraine on the economy of Poland, UNHCR Reports and Assessments, March, https://data.unhcr.org/en/ documents/details/106993 Foged, M., & Peri, G. (2016). Immigrants' effect on native workers: New analysis on longitudinal data. American Economic Journal: Applied Economics, 8(2), 1-34.\n\nFoged, M., Hasager, L., & Peri, G. (2024). Comparing the effects of policies for the labor market integration of refugees. Journal of Labor Economics, 42(S1), S335-S377.\n\nGromadzki, J., & Lewandowski, P. (2023). Refugees from Ukraine on the Polish labour market. Social Insurance. Theory and Practice, 155(4), 29-40.\n\nGUS (2024a). Structure of wages and salaries by occupations for October 2022, Statistical Office in Bydgoszcz, https://stat.gov.pl/en/topics/labour-market/ working-employed-wages-and-salaries-cost-of-labour/structure-of-wages-andsalaries-by-occupations-for-october-2022,4,8.html GUS (2024b). Education in the school year 2023/2024 (preliminary data), Statistical Office in Gdańsk, https://stat.gov.pl/en/topics/education/education/ education-in-the-school-year-20232024-preliminary-data,13,2.html Heller, B. H., & Mumma, K. S. (2023). Immigrant integration in the United States: the role of adult English language training. American Economic Journal: Economic Policy, 15(3), 407-437.\n\nJaumotte, M. F., Koloskova, K., & Saxena, M. S. C. (2016). Impact of migration on income levels in advanced economies. International Monetary Fund.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "UNHCR supports CNARR in the popularization of the asylum law and its implementing decree, including\ntowards ONAPE with the aim to develop a Memorandum of Understanding that would lift the challenges met\nby refugees while accessing the job market including in the private sector.\n\nIn the private sector, practical experience shows that some employers still hire refugees without the approval\nof ONAPE and may treat them less favorably in terms of wages and social benefits. There has been no\nlegislative or policy change regarding child labor.\n\nThere is no reliable data on the percentage of refugees employed in the formal sector.\n\nMany refugees work in the informal sector, but data on this is equally unavailable. Most refugees engage\nin independent work, particularly in agriculture, which remains the backbone of the Chadian economy.\nHowever, agricultural value chains are very weak in the country, affecting both refugees and host populations.\nThe main constraints, even more pronounced for women, relate to difficulties in accessing agricultural land,\ninfrastructure, agricultural inputs such as certified inputs, and financial services.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Woman occupation_\nEarns cash 0.90 0.059** 0.89 0.007\nWorks all year 0.88 -0.047 0.88 0.023\nNot working 0.25 -0.021 0.24 -0.015\nAgriculture 0.19 0.055 0.25 0.011\nService & sales 0.39 0.057 0.35 0.016\nProfessional 0.05 -0.028 0.04 -0.010\nManual 0.11 -0.063*** 0.12 -0.003\n\n_Note:_ Column (1) is a sample at 20 to 100 km from a nonactive mine.\nColumn (2) difference for sample at 0-20 km from an nonactive, compared with column (1)\nColumn (3) is a sample within 20 to 100 km of an active mine.\nColumn (4) difference for sample at 0-20 km of an active mine, compared with Column (3)\n\n*** p<0.01, **p<0.05, *p<0.1. Univariate regression model.\n\nAppendix Table A2 also shows selected child health outcomes as summary statistics across the\n\nfour treatment groups. We note that, once again, the sample looks quite balanced in the first\n\nthree columns, although children seem to be worse off in communities close to mines that have\n\nnot started producing, evidenced by the fact that infant mortality is 8 percent compared to 7\n\npercent farther away, and 6 percent in communities with active mines. The anthropometrics\n\nheight-for-age (stunting or chronic malnutrition), weight-for-age (wasting or acute", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The Shona originally came from Zimbabwe and migrated to Kenya as missionaries majorly between the 1950s and**\n\n**1970s, settling in the Greater Nairobi area.** According to community elders, the Shona were issued certificates of\n\nregistration under the Alien Restriction Act upon arrival. However, a change in the Registration of Persons Act of\n\n1978 prevented them from accessing identity cards. As a result, most of those who were among the first wave of\n\narrivals do not hold valid legal identity documents. At the same time, Zimbabwe and Zambia do not consider them\n\nas nationals since many of those who were born there did not have their births registered and lost all traces of their\n\nancestry since they never returned, hence rendering them stateless. [[8]] Subsequently, they settled and assimilated\n\nwith the local Kikuyu community which welcomed them. Since their arrival, they have practiced wood carving for\n\nmen and basket weaving for women as their primary economic activity outside of preaching activities. Ten\n\nindividuals from the Shona community were granted Kenyan citizenship on 12 December 2020 and a further 1,649\n\nwere recognized as Kenyan citizens and issued with registration certificates on 29 July 2021.\n\n- **Box 1: Data Sources**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "UNHCR [1] supports the Government of Indonesia by undertaking core refugee protection functions,\nincluding registration, refugee status determination, gender-based violence prevention and response,\nchild protection, legal protection, and the pursuit of durable solutions. Approximately 48% of the\nrefugee population in Indonesia is residing in IOM-managed accommodation centers, established as\npart of the Regional Cooperation Agreement (RCA) between Indonesia, the Government of Australia,\nand IOM in 2000. 42% of the refugee population – largely those who arrived in Indonesia after 2017\n\n- are living independently and, with the exception of the most vulnerable, do not receive financial\nsupport for food, rent, and basic needs. Approximately 10% of the refugee population is comprised of\nRohingya refugees who arrived by boat in recent years and who are residing primarily in temporary\nshelters in Aceh and North Sumatra.\n\n---\n[1] The Government of Indonesia-UNHCR host country agreement has been in place since 1979.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n### **Barriers in** **accessing care**\n\nFor individuals who experienced challenges in accessing care, the main barriers were long wait times (33%), unaffordable transport costs (23%), and inability to make an appointment (21%), indicating a shift in barriers compared to 2023. With the health worker shortage in Europe long waiting times are renowned and potentially exasperated by the increase in the refugee population. Although challenges in making an appointment remain among the top three barriers, the percentage of those experiencing this difficulty has decreased to 21% from 38% in 2023, when it was the topmost challenge. For those who arrived in 2024, challenges in making an appointment remained however the top barrier (34%). This points to improvements in navigating the host country’s health systems for those who arrived before 2024, supported by the extensive information and awareness efforts of health authorities and RRP health partners. At the same time, it highlights the continuous need for information sharing to ensure effective access to care.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n# Context\n\nIn its third year, the war in Ukraine continues to have a devastating impact on the people in Ukraine and causes massive displacement of populations into the European region and beyond. As of 12 December 2024, 6.2 million refugees from Ukraine were recorded in Europe [1] . Approximately 81% of the refugees are women and children and 13% of the population is older than 60 years [2] . The refugee population includes other vulnerable groups such as persons with disabilities, stateless persons, sexual and gender diverse minorities, and ethnic minorities. In June 2024, the European Council adopted a decision to extend the European Union (EU) Temporary Protection Directive until 4 March 2026 [3], granting Ukrainian refugees in the EU access to benefits, including health.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "International \r Refugee \r Law \r governs \r the \r protection \r of \r refugees, \r including \r the \r realisation\nof \r solutions \r to \r their \r plight. \r UNHCR’s \r mandate \r is \r to \r provide \r protection \r to \r refugees \r and\nseek \r durable \r solutions \r for \r them \r and \r UNHCR’s \r Statute \r and \r numerous \r Executive\nCommittee \r Conclusions \r provide \r the \r legal \r framework \r for \r its \r lead \r role \r in \r voluntary\nrepatriation \r operations [6] . \r UNHCR’s \r Statute \r provides \r for \r key \r activities \r in \r this \r regard,\nincluding \r promoting \r with \r Governments \r measures \r to \r improve \r the \r situation \r of \r refugees\nand \r to \r assist \r Governmental \r and \r other \r efforts \r to \r promote \r voluntary \r repatriation.\n\nIn \r its \r involvement \r with \r durable \r solutions \r for \r IDPs \r UNHCR \r is \r committed \r to \r contributing\nto \r an \r inter-­‐agency \r approach \r framed \r by \r the \r standards \r set \r out \r in \r the \r Guiding \r Principles\non \r Internal \r Displacement \r and \r the \r Framework \r for \r Durable \r Solutions [ \r 7] .", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Over 11,000 indigenous Venezuelans currently residing in Brazil have been identified by UNHCR\nand partners. Compared to the overall Venezuelan population, they face compounded challenges\naccessing basic rights and services, including higher rates of food insecurity (58% vs 52%), health\ncare needs (75% vs 59%) and out of school children (21% vs 15%). [3] Language barriers and limited\nformal education of adults (indigenous refugees are 5 times more likely to have no formal\neducation when compared to the general Venezuelan population in Brazil), significantly affect their\nprospects for successful integration. [4]\n\n### Protection brief in graphics\n\nPopulation category Population category\n\nBreakdown by nationality\n\n_2 World Bank and UNHCR (2021), Integration of Venezuelan Refugees and Migrants in Brazil,_\n\n_[https://documents1.worldbank.org/curated/en/498351617118028819/pdf/Integration-of-Venezuelan-Refugees-and-Migrants-in-Brazil.pdf;](https://documents1.worldbank.org/curated/en/498351617118028819/pdf/Integration-of-Venezuelan-Refugees-and-Migrants-in-Brazil.pdf)_\n_ACNUR & Ministerio do Trabalho e Emprego (2024), Informe sobre o mercado de trabalho formal para Haitianos no Brasil,_\n_[https://www.acnur.org/br/sites/br/files/2024-11/informe-mercado-trabalho-formal-haitianos-brasil-jun-2024.pdf](https://www.acnur.org/br/sites/br/files/2024-11/informe-mercado-trabalho-formal-haitianos-brasil-jun-2024.pdf)_\n_ACNUR & Ministerio do Trabalho e Emprego (2024), Informe sobre o mercado de trabalho formal para pessoas refugiadas afegãs no Brasil_\nhttps://www.acnur.org/br/sites/br/files/2024-11/informe-mercado-trabalho-formal-pessoas-afegas-no-brasil-junho-2024.pdf\n\n---\n[3] R4V (2023), Refugee and Migrant Needs Analysis, https://rmrp.r4v.info/rmna2023/](https://rmrp.r4v.info/rmna2023/) p. 85", "output": {"entities": {"named_data": [{"text": "Refugee and Migrant Needs Analysis"}], "descriptive_data": [], "vague_data": []}}}
{"input": "School feeding programs are largely implemented by the World Food Programme, reaching a total of 13,000\nrefugees in 14 schools in the provinces of Lake Chad and Logone Oriental.\n\nThe Unified Social Registry (RSU), launched in 2019, has made limited progress in capacity, governance and\nfinancing, despite continuous support from WFP and NGOs.\n\n**4.4** **Protection for vulnerable groups**\n\nIn practical terms, the national protection system for the most vulnerable has not undergone any changes\nand the measures in place to support victims of human trafficking are still insufficient. This holds true for\nvictims of Gender-Based Violence (GBV) and at-risk children. The national protection services aimed at\nthese vulnerable groups continue to be underdeveloped and underfunded.\n\n12 R E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **R E P U B L I C O F C H A D**", "output": {"entities": {"named_data": [{"text": "Unified Social Registry (RSU)"}], "descriptive_data": [], "vague_data": []}}}
{"input": "The number of people of working age in Poland is shrinking and is expected to keep declining. Although substantial migrations from Poland after EU accession in 2004 [19] distort population data, the domestic working age population is declining. According to the Labour Force Survey, which better accounts for emigration than the prevalent population definition, the number of Polish citizens aged 20-64 peaked in early 2010, with 23.5 million people. Since then, it has declined by 2.6 million. This trend is set to continue. According to the latest Eurostat projections, without migration, the population (counting all nationalities) aged 20-64 years would decrease by 4.8 million by 2050. [20] © UNHCR / Anna Liminowicz 19 Statistics Poland data, [https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)\n[temporary-stay-from-poland-between-2004-2020,8,14.html](https://stat.gov.pl/en/topics/population/internationa-migration/information-on-the-size-and-directions-of-emigration-for-temporary-stay-from-poland-between-2004-2020,8,14.html)\n\n---\n[20] Eurostat data, [https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-](https://ec.europa.eu/eurostat/databrowser/view/proj_23np__custom_8710248/bookmark/table?lang=en&bookmarkId=97472dd3-3dd2-4aca-a51f-15c98be37466)", "output": {"entities": {"named_data": [{"text": "Labour Force Survey"}], "descriptive_data": [{"text": "Statistics Poland data"}, {"text": "Eurostat data"}], "vague_data": []}}}
{"input": "Interestingly, while women and girls and younger men and boys were more likely to access formal services than informal supports, older men (age 35 and older) were more likely to access informal supports than formal services. These results may suggest that while older men are less likely to access formal MHPSS services, perhaps due to stigma or other factors, some may turn to informal means, such as support from friends, family and spirituality.\n\n**22**\n\n60+ years old 35-59 18-34 12-17 5-11 (N=360) 28% 37% 56% 71% 71% 18% 11%\n\n### **Location of** **Received MHPSS**\n\nMHPSS services were most commonly accessed in community centres (38%), followed by online platforms (18%), reception hubs such as Blue Dots (14%), healthcare settings (13%), religious settings (11%), schools (8%), workplaces (4%), and through phone or hotlines (4%). Additionally, 11% indicated “other” locations. This distribution underscores the importance of diverse and accessible service locations to meet varied needs and preferences, leveraging both formal and informal support systems.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "# **From Stateless to Citizens: the journey** **of the Shona community in Kenya**\n\nPreliminary results from a socioeconomic study on the impact of citizenship on socioeconomic and living conditions.\n\n\" _Getting a national ID has really helped me. I can now move freely without fear of getting arrested. I have access to better job_\n\n_opportunities too because of the access the ID has been able to give me. My kids can now pursue their education comfortably because_\n\n_I know I can support them with access to more work opportunities._ \" - Azariah Samuel, 27-year-old father of two during a follow-up\n\nsocioeconomic study on the Shona community in Kenya. © UNHCR/Charity Nzomo.\n\n**[www.unhcr.org](http://www.unhcr.org/)** 1", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "confirmed the results found in international literature presented above. The most important result is that Ukrainian refugees who are fluent in Polish earn a net wage premium of about PLN 700 (+16% relative to refugee net median wage, PLN 1,000 gross wage) when compared to those with beginner language skills. This result is stable across different model specifications. Note that such an earnings gain would bring the median net wage of a Ukrainian refugee (estimated based on the SEIS UNHCR survey in chapter 2) from 80% to 98% of the median in the economy as a whole (or from 80% to 93% according to Ukrainian refugee’s median in the NBP’s 2024 survey), almost closing the gap to the economy as a whole in these terms. It is in fact higher than the PLN 500 median net wage premium of the pre-war Ukrainian migrants over Ukrainian refugees in the NBP (2024) survey, even though 68% of the former and only 28% of the latter said they had a high level of fluency in Polish.\n\n31", "output": {"entities": {"named_data": [{"text": "SEIS UNHCR survey"}, {"text": "NBP’s 2024 survey"}, {"text": "NBP (2024) survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "##### **September/ October 2023 report**\n\n###### Venezuela\n\n**ProCap Senior Protection Advisor**\n\n**have provided the WASH, Shelter,**\n\n**Logistics, Health, Education, Food**\n\n**Security, Nutrition Cluster as well as**\n\n**Venezuelan Humanitarian Fund (VHF)**\n\n**partners a Protection Mainstreaming**\n\n**in-person training.** The training com\nprised a theoretical component covering i)\n\nhumanitarian and protection principles, ii)\n\nfundamental protection concepts and the\n\nrisk equation, iii) the distinction between\n\nintegrated protection and protection\n\nmainstreaming and their definitions. The\n\nsecond part involved a practical exercise\n\nwhere participants selected an activity\n\nwithin their sector, analyzed the context,\n\nidentified three primary protection risks,\n\nand applied the protection equation.\n\nThis dynamic and participative exercise\n\nallowed participants to present their\n\nactivities and benefit from constructive\n\nfeedback. Overall, the positive feedback\n\ngiven by participants shows the need to\n\n**8**\n\nstrengthen humanitarian organizations'\n\nunderstanding on Protection Main\nstreaming to guarantee the Centrality of\n\nProtection is in place in the humanitarian\n\nresponse.\n\n**X. Training on Mixed Migration**\n\n**and Durable Solutions**\n\n**A full-day training session on Mixed**\n\n**Migration and Durable Solutions took**\n\n**place on October 19th. The session**\n\n**began with a review of basic protec-**\n\n**tion concepts, followed by an analysis**\n\n**of strategies to mitigate threats and**\n\n**vulnerabilities, and enhance capabil-**\n\n**ities through practical exercises with**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Instrumental variables regressions were performed with the Two Stage Least Squares technique. In the first stage, it adjusts for the non-random distribution of Ukrainian refugees across poviats, and in the second stage, it calculates the models. These results can be interpreted causally. The two previously mentioned instruments were used and yielded statistically significant results, as well as passed statistical tests on their appropriateness for instrumenting the employment share of Ukrainian refugees.\nOne instrument is the share of Ukrainian children in Polish schools, and the other is the distribution of Ukrainian citizens across Poland in 2019, as recorded in declarations", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "by Information Management (IM) per\nsonnel in the Protection Cluster and the\n\nAreas of Responsibility. The cluster's IM\n\nautomated data transformations to con\nsolidate information for the year 2023.\n\nThe pilot phase for the migration to 345W\n\nhas concluded, and final refinements are\n\nunderway. These refinements aim to\n\nestablish a more automated process for\n\nreporting, validation, and consolidation\n\nof partners' responses.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "World Day Against Trafficking in Persons\n\n2023. The document can be downloaded\n\n[here link.](https://www.globalprotectioncluster.org/publications/1586/reports/annual-report/boletin-anual-trata-de-personas-agosto-2022-agosto-2o23)\n\n**VII. Food Security and Liveli-**\n\n**hoods (FSL) and Trafficking in**\n\n**Persons (TiP)**\n\n**Under the Food Security and Live-**\n\n**lihoods (FSL) Cluster consultancy,**\n\n**research has been done to under-**\n\n**stand the connection between food**\n\n**insecurity, lack of livelihoods and**\n\n**the likelihood of being recruited into**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Ukraine Refugee Pulse, which is based on a survey carried out between October and December 2022, 40% of respondents have enough income to meet basic needs or are able to support the same lifestyle they had in Ukraine, while 60% say they do not have enough income or have to rely on savings and welfare. At the same time 62% reported staying in accommodation for which they pay themselves.\nMSNA Poland 2023 survey also shows that when asked whether they faced any challenges obtaining enough money to meet their needs, the refugees were nearly equally split (around 0.5% more reported no difficulties), with an additional 8% not knowing or refusing to answer. According to the National Bank of Poland survey carried out in November 2022, 28% of refugees said they spend less than half of their income on daily expenses, most spend between 50% and 80%, and 19% spend 80100% of their income.\n\n###### Currently between 225 and 350 thousand of refugees from Ukraine are working in Poland. The lower bound is the number from social security, while the higher bound is the product of employment rate from the surveys and working age population with PESEL numbers.", "output": {"entities": {"named_data": [{"text": "MSNA Poland 2023 survey"}, {"text": "Ukraine Refugee Pulse"}], "descriptive_data": [{"text": "National Bank of Poland survey"}], "vague_data": []}}}
{"input": "**it on a higher growth path.** According\nto the Deloitte D.Climate model, economic impact of Ukrainian refugees amounted to a higher real GDP by 1.5% in 2022, as they initially entered the labour market.\nWith more refugees finding employment, their impact grew to 2.3% GDP in 2023, and further to 2.7% GDP in 2024. This corresponds to GDP being higher by PLN 98.7 billion in 2024. In the long term, as the refugees acquire more country-specific skills and firms invest to restore their capital-to-labour ratio, the impact will grow to 3.2% GDP by 2030. Refugees contribute to the economy by increasing the labour supply as both workers and entrepreneurs, and by boosting demand as consumers.\nThe increase in GDP is not directly proportional to the increase in population or employment. [20] On the one hand, increase in productivity further boosts the economy, on the other net benefits are lowered both due to a decrease in the capital-to-labour ratio, as well as an increase in competition in the labour market. Moreover, the increase in demand in tight labour market conditions work in the direction of higher inflation and lower price competitiveness of Polish products which decrease its overall positive impact.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "physical health of the members of the\n\ncommunity was improved thanks to the\n\nwork of PUI, which translates in the need\n\nof the PC to keep supporting partners\n\nimplementing such relevant projects in\n\ncommunities of difficult access.\n\n[Full access to the story through this link.](https://www.globalprotectioncluster.org/publications/1658/reports/report/historias-de-impacto-cluster-de-proteccion-venezuela-septiembre)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The Polish government introduced a Special Act [26] that facilitated refugees’ inclusion. The work on the Act started when the activation of TPD was not certain, but later it was used for transposition of TPD. As a result, the Polish framework is very similar to the TPD, though the scope of the Act is wider than the TPD.\nHowever, it only covers those that arrived in Poland after 24th February 2022.\nThis legal framework gave access to the job market, health care and education.\nThe authorities allowed those fleeing Ukraine to access basic administrative systems like PESEL and “Trusted Profile”, and legalised residency for 18 months.\nThe government's solutions allow refugees to get a job, run a business or register as unemployed or seeking work.\nOn top of that, due to constitutional guarantee of access to education for everyone, refugee children were allowed to access schools and kindergartens.\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Chart 12.** Structure by occupational group of all employed persons and refugees from Ukraine\n\nAll employed persons Ukrainian refugees 40% 30% 20% 10% 0% 10% 20% 30% 40%\n\n**Source:** Deloitte own elaboration based on Statistics Poland and ZUS data.\n\n---\n[26] Act of March 12, 2022 on assistance to citizens of Ukraine in connection with the armed conflict on the territory of the country", "output": {"entities": {"named_data": [{"text": "Statistics Poland"}], "descriptive_data": [{"text": "ZUS data"}], "vague_data": []}}}
{"input": "As of 30 June 2023, only 1.6 per cent of Chad’s population is covered by the social protection framework,\nand the country spends 0.1 per cent of the Gross Domestic Product on social protection (excluding health\nand education expenses). After a lengthy process, the document for the new National Social Protection\nStrategy (SNPS) 2022-2026 has been finalized and is awaiting validation and signature by the transitional\ngovernment. The new SNPS spanning four years aims to gradually establish a comprehensive, effective\nand efficient social protection system that addresses financial needs, livelihood security, risk management,\nvulnerability reduction and access to basic social services for all individuals residing in Chad, including\nrefugees.\n\n**1.2** **Social cohesion**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Labor force participation [14] is almost on par with the host country weighted average for the region, with just 2 percentage points difference between the two. This is surprising, considering that the distribution of refugee household members is heavily skewed towards women and dependents.\n(73% of working age [15] individuals are female and the age dependency ratio stands at 63%, which is 10 percentage points above the regional weighted average). The most common activities reported by respondents who are out of the labor force are retirement (30%) and engagement in household responsibilities (31%). Across countries labor force participation looks uneven – it stands at a staggering 66% in Hungary (6 percentage points above the national indicator), and at just 36% in\n\n**REFUGEE HOUSEHOLD INCOME SOURCES ABOVE AND BELOW THE POVERTY LINE, %** **[1,2]**\n\nRegular employment Above the poverty line Below the poverty line Temporary work Self employment 35% Host country social protection payments 74% 12% Ukraine social protection pensions 34% Ukraine social protection other 9% 4% 6% 10% Other sources 3% 4% 7% Almost half of income of households below the poverty line depends on social protection\n\n---\n[15] In this context defined as individuals that are 15 or more years old", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "This contrasts with the government’s promotion of free land access which apply to all people involved\nin agriculture. The current arrangements have led to a seasonal migration of refugees from the camps\nto fields located in cantons up to 50 or 70 km away, where they establish temporary settlements. These\nsharecropping agreements offer the advantage of fostering close relationships between refugees,\nlandowners and entire villages, because refugees set up tents with their families throughout the growing\nseason. Furthermore, refugees often do not receive documents confirming their right to sustained access\nto the land used. Between 2020 and 2023, approximately 15,000 hectares of agricultural land have been\nmade available to refugees in Chad for exploitation purposes, under written or verbal agreements lasting\nfrom one to three years.\n\nIn the current Ministry of Social Affairs, there is still no housing assistance program for vulnerable Chadian\nnationals. Furthermore, the temporary support system for relocating populations affected by floods in the\ncapital, primarily backed by the humanitarian actors, does not extend its coverage to refugees.\n\n**3.4** **Financial and administrative services**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "main shareowner in the mine. Most of these 17 mines have foreign ownership, such as\n\nAustralian, Canadian, or South African, sometimes in partnership with Ghanaian firms or the\n\nGhanaian state. Most are open-pit mines, although a few consist of a combination of open-pit\n\nand underground operations.\n\n**Table 1 Gold Mines in Ghana**\n\n**Name** **Opening** **Closing year** **Company** **Country**\n\n**year**\n\nAhafo 2006 active Newmont Mining Corp. USA\nBibiani 1998 active Noble Mineral Resources Australia\nBogoso Prestea 1990 active Golden Star Resources USA\nChirano 2005 active Kinross Gold Canada\nDamang 1997 active Gold Fields Ghana Ltd. South Africa\nEdikan (Ayanfuri) 1994 active Perseus Mining Australia\nIduapriem 1992 active AngloGold Ashanti South Africa\nJeni (Bonte) 1998 2003 Akrokeri-Ashanti Canada\nKonongo 1990 active LionGold Corp. Singapore\nKwabeng 1990 1993 Akrokeri-Ashanti Canada\nNzema 2011 active Endeavour Canada\nObotan 1997 2001 PMI Gold Canada\nObuasi 1990 active AngloGold Ashanti South Africa\nPrestea Sankofa 1990 2001 Anglogold Ashanti South Africa\nTarkwa 1990 active Gold Fields Ghana Ltd. South Africa\nTeberebie 1990 2005 Anglogold Ashanti South Africa\nWassa 1999 active Golden Star Resources USA\n_Source:_ InterraRMG 2013.\n\n_Note:_ Active is production status as of December 2012, the last available data point.\n\n6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**The overall decline in total employment from 74 percent in 2019 to 70 percent in 2024 is indicative of the sum of**\n\n**these shocks.** Although men have re-entered the labor force at a faster rate, the community as a whole is still in\n\nthe process of economic recovery. The proportion of unemployed individuals has remained relatively low,\n\nsuggesting that many are still re-entering the labor market or seeking labor market opportunities. Only 13 percent\n\nof the Shona working wage-earners have some form of employment contract, demonstrating a high prevalence of\n\ninformal work arrangements.\n\n**The increase in the number of individuals out of the labor force, especially among women, underscores the**\n\n**difficulties of returning to the labor market and securing timely employment.** The pandemic's effects have pushed\n\n**[www.unhcr.org](http://www.unhcr.org/)** 6", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Data Sources: proGres v4 (PRIMES) hosts the data of refugees and asylum-seekers in 11 countries. In South Africa, the data are managed by the\ngovernment. In Angola, DRC, Zambia and Zimbabwe, some portions of the data are external. For IDP data, the source of DRC’s IDP figure is the OCHA;\nthe sources in Mozambique and Zimbabwe are the Displacement Tracking Matrix (DTM) of the IOM; and the source in the Republic of Congo is the\ngovernment, the Ministry of Social Affairs and Humanitarian Action (MASAH).", "output": {"entities": {"named_data": [{"text": "proGres v4 (PRIMES)"}, {"text": "Displacement Tracking Matrix (DTM)"}], "descriptive_data": [], "vague_data": [{"text": "IDP data"}]}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n### **Chronic illness and** **MHPSS**\n\nAmong individuals with chronic illnesses, 41% reported experiencing mental health and psychosocial problems in 2024 (44% of women, 36% of men), up from 33% in 2023 (36% of women, 28% of men). In contrast, only 16% of individuals without chronic illnesses reported such problems in 2024 (20% of women and 11% of men), compared to 13% in 2023 (15% of women and 9% of men). These findings reinforce the strong interplay between chronic health conditions and mental health challenges, emphasizing the need for integrated care models that holistically address both physical and mental health to provide effective and comprehensive support for those managing chronic illnesses.\n\n**26**\n\n**% OF INDIVIDUALS WHO REPORTED EXPERIENCING**\n\n**A MENTAL HEALTH OR PSYCHOSOCIAL PROBLEM BY**\n\n**CHRONIC ILLNESS STATUS AND COUNTRY**\n\nWith chronic illness Without chronic illness Regional Romania Hungary Lithuania Poland Bulgaria Latvia Slovakia Estonia Czechia Moldova (N=17,867)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Migrants dispersed to weaker labour markets experience poorer inclusion outcomes in subsequent years, and vice versa. These outcomes can pertain to employment, earnings, or human capital accumulation, and have been shown in Denmark (Foged, Hasager, and Peri, 2022; Azlor, Damm, and Schiltz-Nielsen, 2020), Germany (Aksoy, Giray, Poutvaara, and Schikora, 2020), Norway (Godøy, 2017), Sweden (Åslund, Östh, and Zenou, 2010; Åslund and Rooth, 2007), and Switzerland (Müller, Pannatier, and Viarengo, 2022), as well as the previously described crosscountry study. This could in principle stem from scarring on an individual level from weak initial opportunities, or persistently weak local labour market combined with imperfect geographic mobility. The effects are hard to disentangle, while Åslund and Rooth (2007) find some indication that both phenomena are at play, Godøy (2017) finds evidence only for persistently weak local labour markets.\n\n##### Migrants and refugees dispersed away from ethnic enclaves experience weaker labour market inclusion outcomes, and vice versa.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Given that the refugee population is up to three or four times larger than the local population in certain\nareas hosting refugees, mainly in Eastern Chad, there is an increased risk of tensions due to already limited\nresources. Nevertheless, on a broader scale and across the entire territory, refugees continue to peacefully\ncoexist with the local population, facilitated by strong ethnic and cultural bonds, along with shared common\ntraditions. Mixed committees, comprising both refugees and members of the host community, remain active\nin all refugee camps and sites. Their objective is to promote peaceful coexistence and proactively address\nconflicts. Women continue to play a crucial role in conveying messages of peace and social cohesion,\ncontributing significantly to dispute resolution efforts.\n\n**1.3** **Environmental management**\n\nThere has been no significant change in national environmental protection and resource management\npolicies. The existing policies continue to lack clarity concerning their application to refugees and/or host\ncommunities.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "prominent in refugee households in terms of poverty and employment. The same holds true for households that contain members with disabilities. It is somewhat encouraging that the share of refugee youth (age 15 to 24) not engaged in employment, education or training stands at just 14% (18% if distance learning is excluded), which is in line with host country national indicators.\n\n**Based on the above findings it is recommended**\n\n**that:**\n\n- Any transitions from subsidized accommodations\nare handled with extreme care. Almost 20% of all refugee households depend on this aid to stay out of poverty\n\n- Labor market inclusion efforts continue and\ninterventions target the removal of the most commonly reported barriers (local language proficiency, lack of decent work opportunities, a mismatch in skills).\n\n- A special focus is put on addressing the needs of\nfemale only led households or members with disabilities. Both groups are more likely to find themselves below the poverty line.\n\n# 50% 74% 14%\n\nof refugees from Ukraine find themselves of all refugee households income above\n\n**below the poverty line** [4] based on the poverty line **comes from regular work**\nreported income - this figure stands at 35% for households\n\n---\n[4] Defined as 50% of the median equivalized income in the host country", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "towards higher-paid occupational groups.\nThe share of Poles in the two lowest salary brackets (earning less than gross PLN 4,000 and PLN 4,000-6,000 in 2022) decreased by 0.4 and 1.8 percentage points, respectively, while the subsequent higher salary brackets increased by\n1.4 pp. (PLN 6,000-8,000), 0.6 pp.\n(PLN 8,000-10,000), and 0.3 pp. (above PLN 10,000) (see Chart 30).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland © UNHCR / Anna Liminowicz Dispersing refugees to weaker labour markets can also have negative social outcomes. Albarosa and Elsner (2022) report more anti-immigrant incidents during the European refugee crisis (2015/2016) in areas of Germany with high unemployment rates and shares of right-wing voters. Damm and Dustmann (2014) show that immigrant men dispersed to areas of Denmark with more convicted criminals, experience higher future crime conviction probabilities, but not overall neighbourhood crime rate.\n\nThe estimated employment rate of refugees from Ukraine in Poland is above 60% and was among the highest in the OECD [27] .\nAlthough there is uncertainty around employment rate in different countries due to uncertainty regarding refugee numbers while MSNA Poland 2023 gives a slightly lower figure of 61%. In comparison, the employment rate equalled 61% in the United", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "REGIONAL BUREAU FOR SOUTHERN AFRICA\n\n**DEMOCRATIC REPUBLIC OF THE CONGO REFUGEES SITUATION**\n\nAs of 3 0 September 2022\n\n**Author: UNHCR DIMA - RSA** Contact : rsarbdima@unhcr.org **Source:** UNHCR Primes, Government, UNHCR", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Poland 2023 assess that around 56% [23] of refugee arrivals had completed higher education. This means that Ukrainians with higher education were more likely to relocate to Poland or leave Ukraine in general, having the necessary means to achieve this. On average refugees with a bachelor’s degree or higher had an over 30% higher employment rate than peers without a degree, according to MSNA Poland 2023 survey.", "output": {"entities": {"named_data": [{"text": "MSNA Poland 2023 survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Table 12 shows that log annual wages are higher close to mines (column 1), and that most of\n\nthe increase is driven by the increase in wage rates for women (column 2). Women, however,\n\nhave lower wages before the mine, and a smaller share of women earn wages. Globally, it is\n\nconsidered that the historic expansion in service sector employment (which in this context\n\nincreased significantly within 10 km) has played a pivotal role in reducing the gender wage and\n\nhour gap (Ngai and Petrongolo, 2017).\n\n31", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "UNHCR \r first \r established \r an \r operational \r presence \r in \r South-­‐Eastern \r Myanmar \r in \r 2004\nwith \r the \r objective \r of \r assisting \r communities \r affected \r by \r armed \r conflict \r in \r Kayin \r and \r Mon\nStates \r and \r in \r Tanintaryi \r Region. \r Between \r 2004 \r and \r 2012, \r UNHCR, \r in \r partnership \r with\nlocal \r and \r international \r organizations, \r has \r delivered \r over \r 3,000 \r humanitarian \r projects \r to\nensure \r that \r displaced \r and \r host \r families \r in \r affected \r areas \r have \r access \r to \r proper\nsanitation, \r primary \r health \r care \r facilities, \r safe \r and \r clean \r water, \r livelihood \r activities \r and\nother \r training \r including \r technical \r support \r to \r community \r management \r capacities,\nparticularly \r in \r relation \r to \r small \r infrastructure \r management.\n\nUNHCR \r also \r undertakes \r protection \r assessment, \r legal \r awareness \r training, \r and \r provides\nassistance \r to \r extremely \r vulnerable \r individuals \r (including \r land \r mine \r victims \r and\nsurvivors \r of \r sexual \r and \r gender-­‐based \r violence). \r The \r extent \r and \r capacity \r of \r protection\nmonitoring \r and \r referral \r networks \r in \r the \r South-­‐East \r nonetheless \r remain \r extremely\nlimited.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "politicians that have been linked to mining activities in other countries such as Peru\n\n(Maldonado, 2017) and India (Asher and Novosad, 2018), such as clientelism, corruption and\n\nreelection of local politicians were not analyzed within the context of Ghana. We encourage\n\nfuture analysis along similar lines.\n\nA few caveats should be noted. As the gold mining industry in Ghana matures further, it will\n\nbe important to determine the long sustainability of these economic effects. This paper does not\n\ntease out the effect of mine closure on local socio-economic conditions, an aspect that warrants\n\nfuture focus. Moreover, lack of clearly estimated effects both in the individual level and district\n\nlevel analysis could stem from limited sample sizes. We encourage future analysis to use more\n\nrounds of data to ensure consistent results. Lastly, for the health and employment effects that\n\nwe observe, we cannot determine if they stem from changes in the market-based economy, from\n\ncorporate social responsibility policies or public spending. Future studies should try to carefully\n\ndisentangle the mechanisms at play.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# **2.** Situation of refugees from Ukraine on the labour market in Poland\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Chart 7.** Unemployment rate\n\n12% 10% 8% 6% 4% 2% 0%\n\n**Source:** Harmonized data, Eurostat, [Statistics | Eurostat (europa.eu)](https://ec.europa.eu/eurostat/databrowser/view/une_rt_m/default/table?lang=en)\n\n##### Refugees from Ukraine fit well into the needs of the Polish labour market.\n\nUkrainians arrived on a labour market that structurally needs more workers, as the domestic population is ageing rapidly, while the economy is growing. High levels of education, cultural proximity and previous connections to Poland helped refugees adapt to the labour market. Furthermore, Poland made an important and strategic policy decision by promptly opening the labour market and supporting their inclusion.\n\n16 17\n\n**Chart 6.** Working age population with Polish citizenship (20-64 years old)\n\n25 24 23 22 21 20", "output": {"entities": {"named_data": [{"text": "Harmonized data, Eurostat"}], "descriptive_data": [], "vague_data": [{"text": "Harmonized data"}]}}}
{"input": "UNHCR and partners provide case management assistance to support children who are\nunaccompanied or separated from traditional caregivers or who are suffering from violence,\nexploitation, and neglect. UNHCR works with partners, including government partners, to assist\nchildren with heightened protection needs by providing legal assistance, safety and security, and\npsychological and health interventions as needed. UNHCR works with YCWS, our implementing\npartner, to provide assistance to unaccompanied children (UAC) in a Semi-Independent Living Care\nArrangement (SILCA) through which UAC are accommodated in a rented room and their basic needs\nare covered. In response to the emergency situation in Aceh, UNHCR is undertaking Best Interest\nAssessments (BIA) for the large number of UAC, child spouses, and other children at risk to better\nunderstand their needs and determine a protection approach that best addresses those needs.\n\n### **Gender-Based Violence (GBV)**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "## **NAVIGATING HEALTH** **AND WELL-BEING** **CHALLENGES FOR** **REFUGEES FROM** **UKRAINE**\n\n#### An Inter-Agency Exploration of Data 2nd edition January 2025", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Average monthly gross earnings in enterprise sector in poviat of employment in 2022**\n\nNatives and other immigrants 36 Note that these percentages are only indicative, as Ukrainian refugee educational attainment is assumed on the basis of November 2022 NBP (2023) survey for 18+ age group and July-August 2023 UNHCR (2023) survey for 15+ age group, while the general population is taken from the 2022 Labour Force Survey for 15-74 (broadest available) age group, and earnings by educational attainment are taken from the GUS (2022) “Structure of wages and salaries by occupations in October 2020”.\n37 Note that the numbers of Ukrainian refugees and all workers numbers by poviats are taken from ZUS Statistical Portal on 30th September 2023 from the universe of workers registered for social security (this does not cover the informal sector and some jobs that do not require social security). Ukrainian refugees are identified by PESEL UKR. Salaries and wages are taken from Statistics Poland BDL GUS database for 2022, but cover only the enterprise sector (firms with 10 or more employees).\n38 Note that there is no publicly available administrative data on the sectoral distribution of Ukrainian refugees. We proxied their sectors by taking the difference in workers with Ukrainian citizenship registered for social security between H1 2023 and end of 2021 in A-Q 1-letter NACE sections. For the general population we used employment in the 15+ age group in Q2 2023 from the Eurostat Labour Force Survey. Earnings by NACE section have been taken from Statistics Poland Statistical Bulletin wages and salaries for the enterprise sector and public sector in Q2 2023.\n39 Note that Ukrainian refugees have been allocated to firm sizes based on the July-August 2023 UNHCR (2023) survey, while general workers from the GUS (2023) “Employment in the national economy in 2022”. Productivity of firms by size is based on gross value added per person employed in industry, construction, and market services sectors (broadest available) in 2021 from Eurostat Structural Business Statistics.", "output": {"entities": {"named_data": [{"text": "2022 Labour Force Survey"}, {"text": "Statistics Poland BDL GUS database for 2022"}, {"text": "Eurostat Labour Force Survey"}, {"text": "Eurostat Structural Business Statistics"}, {"text": "July-August 2023 UNHCR (2023) survey"}], "descriptive_data": [{"text": "November 2022 NBP (2023) survey"}], "vague_data": []}}}
{"input": "Population Data Analysis – September 2022\n\nOverview\n\nAs of the end of September 2022, Southern Africa hosts around **8.6 million persons of concern (PoCs) to UNHCR** .\nThis includes 1.1 million refugees and asylum-seekers and 6.9 million internally displaced persons (IDPs), as well as\nothers of concern, refugee returnees and IDP returnees. **The Democratic Republic of Congo (DRC) represents 77**\n\n**per cent of the regional data.**\n\nRefugees, Asylum-Seekers and Others of concern\n\nThe region hosts **785,000 refugees, 278,000**\n\n**asylum-seekers** **and** **36,000** **others** **of**\n\n**concern** . Among those 1.1 million PoCs, 74 per\ncent of them are from the countries outside of\nthe Southern Africa region. [1] The top five\ncountries of origin are Central African Republic\n(243,000), Rwanda (242,000), DRC (228,000),\nBurundi (84,000) and Ethiopia (61,000).\n\nInternally Displaced Persons\n(IDPs)\n\nIn Southern Africa, there are **6.9 million**\n\n**internally displaced persons (IDPs)** . Most of\nthem are conflict-induced, 6.4 million, but there\nare also natural disaster-induced IDPs, 0.5\nmillion. The data on IDPs are reported in DRC,\nCongo, Mozambique and Zimbabwe (see\nFigure 1).\n\nDurable Solutions\n\nFigure 1. Number of IDPs in RBSA by Cause as of 30 September 2022\n\n---\n[1] The Southern Africa region refers to the 16 countries covered by the Regional Bureau for Southern Africa of UNHCR including Angola,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "active*mine -0.086*** -0.055** 3.705 -0.058 -0.032 0.125**\n(0.025) (0.025) (2.898) (0.086) (0.032) (0.051)\n\nMean dep var 0.715 0.705 45.71 0.491 0.259 0.028\n\n_Note:_ The table uses GLSS data for Ghana for the survey years 1998, 2005, 2012. The sample is restricted to\nwomen and men aged 15–49. Robust standard errors clustered at the village or neighborhood level in parentheses\n(except if otherwise stated). All regressions control for year and district fixed effects, urban dummy, age, and years\nof education. Active is active status of mine in the survey year. The treatment distance is defined to 20 km. Rows\n2 drop sample between 20 to 40 km of a mine, and rows 3 drop sample that was surveyed two years before mine\nopening. *** p<0.01, **p<0.05, *p<0.1. FE = fixed effects.\n\n30", "output": {"entities": {"named_data": [{"text": "GLSS"}], "descriptive_data": [], "vague_data": []}}}
{"input": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE requirements and differences in location-specific regulations. On the other hand, individuals with experience in construction found it easier to secure employment in the same sector, with an unemployment rate at just 5%. Lower language requirements and fewer issues with skill recognition are likely to be the main reasons. This possibly explains why 53% of former construction sector employees from Ukraine were able to find work in the same sector.\n\n**REFUGEE EMPLOYMENT TRANSITION MAP FOR SELECTED SECTORS**\n\nPast sector of employment in Ukraine Current sector of employment in Host country Education and support service activities Construction\n\n**Accounting for those engaged in Ukrainian**\n\n**distance learning, the share of youth not in**\n\n**employment, education or training for refugees**\n\n**from Ukraine is comparable to that of host**\n\n**countries**\nIf distance learning, which follows the Ukrainian curriculum, is taken into account, the share of young Ukrainians (aged 15 to 24) who are not engaged in employment, education, or training (NEET) stands at 14% [16] across the region, which is fully in line with the Other No longer employed Construction Education Administrative and support service activities\n\n---\n[16] Likely to be a bit overstated, as the survey did not inquire about activities of 15-year-olds outside of school enrollment. Also,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "statistics for the women’s surveys across four different groups, close and far away, and before\n\nand during the mine’s production phase. Columns 1 and 3 show mean values of the population\n\nthat live far away from mines, before and during mining respectively. Columns 2 and 4, in\n\n14", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "the women’s surveys"}]}}}
{"input": "**ing grounds for the next months**\n\n**have been set.** Further, meetings have\n\nbeen held with the 6 subnational Pro\ntection Clusters in Zulia, Táchira, Apure,\n\nAmazonas, Barinas, and Bolivar. Coor\ndination with these coordinators will be\n\nstrengthened to assure decision taking\n\nis guaranteed also from the field, and\n\ntheir support in the implementation of\n\nthe extended OCHA Local Coordination", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE stigma limiting help-seeking behaviors among adult men. Conversely, for children aged 5–11, caregivers sought support for 76% of boys and 64% of girls.\nThese findings highlight the complex interplay of gender and societal norms in influencing helpseeking behaviours, warranting further investigation.\n\n**% OF INDIVIDUALS WHO TRIED TO ACCESS MENTAL**\n\n**HEALTH SUPPORT BY AGE AND GENDER**\n\nFemale Male work arrangements). These informal mechanisms, while less structured, complement formal services by fostering emotional connection and practical assistance through personal relationships and community networks.\n\n**TYPE OF MENTAL HEALTH AND PSYCHOSOCIAL SUPPORT**\n\n**RECEIVED BY GENDER**\n\nFemale Male Psychotherapy/counseling Support from family or friends Creative psychosocial activities Structured wellbeing intervention Spiritual support Psychiatry/medication management School-based services Workplace support Other Messaging materials Caregiver training (N=1,715) 5-11 12-17 18-34 35-59 60+ years old (N=4,052)\n\n### **Types of Support**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "##### 4. Ukrainian refugees’ skill-job mismatch\b 26 4.1 Over-qualification\b 27 4.2 Access to regulated professions\b 29 4.3 Language wage premium\b 31 4.4 Persons not previously in employment\b 34 4.5 Recommendations\b 35 Appendix: Modelling strategy\b 36 Glossary                                                      44 List of charts and tables\b 45 Literature\b 46\n\n02 Analysis of the impact of refugees from Ukraine on the economy of Poland", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "##### **September/ October 2023 report**\n\n###### Venezuela\n\n**Protection Cluster September/ October 2023 activity report**\n\nThis report has been prepared by the Protection Cluster in Venezuela\n\n_Cover photo: © UNHCR / Kimberly Sarkis (2023)_\n\nThe Protection Cluster is a broad-based participatory forum of protection partners which brings\ntogether United Nations agencies, human rights and development organisations and actors, as well\nas local and international non-governmental organisations. The Protection Cluster is led by UNHCR.\n\nAll our information products, including reports, maps and factsheets are available on the Venezuela\n\nProtection Cluster website:\n[https://ven.protectioncluster.org](https://ven.protectioncluster.org)\n\nContacts:\n\nProtection Cluster Coordinator, **Alice Contini**, continia@unhcr.org\n\nProtection Associate, **Patricia Bosco**, boscoleo@unhcr.org\nCounter-Trafficking in Crisis Specialist, **Norma Ferrer**, noferrer@iom.int\n\nProtection Assistant, **Kimberly Sarkis**, sarkisne@unhcr.org\nProtection Specialist, **Giuliana Inturrisi**, giuliana.inturrisi@drc.ngo\n\n**2**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "boosts the economic impact of Ukrainian refugees. To arrive at results that would be comparable to the previous report, economic impact has been additionally simulated in a scenario without the productivity shock. This brought the results down to 1.3% GDP in 2024, which is in line with the Deloitte (2024) most optimistic of the four outlined scenarios of 1.1% GDP in 2023 and 1.4% GDP in the long term. [21] The Ukrainian refugees and the economy turned out to have adapted better than expected last year. Moreover, the fact that the previously modelled mild adverse effects on the labour market have not materialized reflects a stronger increase in labour productivity than was assumed. As a result, the positive impact of Ukrainian refugees on the economy is greater than previously expected.\n\n**As Ukrainian refugees entered the**\n\n**labour market, the economy adapted,**\n\n**resulting in more specialization and**\n\n---\n[21] Full results of a modelling scenario with no shock to productivity are available in the Online Technical Appendix.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The recommendations drawn from this analysis focus on addressing the health and mental health and psychosocial needs and barriers identified in the SEIS, tailoring them to the specific data and context of each country. To enhance policy development, it will be crucial to improve monitoring of refugees’ health, including sexual and reproductive health and mental health, through inclusion of disaggregated refugee data into national data systems. This will require effective collaboration among health organizations, statistical offices, and partners. Addressing capacity issues in national health systems, such as workforce shortages and long wait times, can be supported through telemedicine and temporarily integrating Ukrainian healthcare workers. Refugees with chronic illnesses and disabilities require targeted interventions to meet their health and MHPSS needs, including through health financing mechanisms. Continued efforts are also required to address persistent access barriers through contextspecific strategies, including providing refugees with information on navigating health systems and preventive health services such as vaccination.", "output": {"entities": {"named_data": [{"text": "the SEIS"}], "descriptive_data": [], "vague_data": [{"text": "disaggregated refugee data"}]}}}
{"input": "Among the 5% who reported access constraints, the primary barrier to accessing SRH services was long waiting times, affecting 33%. Financial barriers also posed challenges, with 23% of women reporting difficulties covering transportation costs, 19% struggling with clinic fees, and 12% with hospital fees. Additionally, 21% lacked knowledge of where to access SRH care and 19% were unable to make appointments, reflecting both informational and administrative barriers to SRH services.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Activities \r – \r whether \r delivered \r by \r UNHCR \r or \r partners-­‐ \r should \r be \r conflict-­‐sensitive \r and\naddress \r key \r issues \r of \r concern \r of \r both \r returning \r refugees \r and \r IDPs \r and \r their\ncommunities. \r A \r community-­‐based \r programme \r that \r builds \r on \r existing \r systems \r and\nstructures \r and \r supports \r local \r development \r plans \r should \r be \r planned \r and \r implemented\nbased \r upon \r comprehensive \r needs \r assessments \r and \r consultations \r with \r the \r populations\nconcerned \r as \r well \r as \r government \r and \r non-­‐government \r actors.\n\nActivities \r and \r project \r delivery \r should \r be \r flexible \r and \r context-­‐specific \r so \r as \r to\naccommodate \r complexities \r and \r respond \r to \r any \r changes \r that \r may \r occur \r throughout \r the\nprocess. \r Activities \r range \r from \r food \r assistance \r to \r essential \r health \r care \r facilities \r and\nservices, \r primary \r and \r secondary \r education \r support, \r and \r community-­‐level \r infrastructure\nrehabilitation \r or \r construction \r and \r livelihoods. \r Livelihood \r opportunities \r will \r be \r a \r key\ncomponent \r in \r ensuring \r the \r sustainability \r of \r the \r reintegration \r process \r and \r cash \r and\nvoucher \r modalities \r to \r boost \r the \r local \r economy \r should \r be \r actively \r considered \r where\nthese \r are \r appropriate \r and \r effective \r ways \r of \r meeting \r identified \r needs.\n\nUNHCR \r will \r seek \r innovative \r solutions, \r in \r particular \r for \r self-­‐reliance, \r education, \r shelter,\nand \r domestic \r energy \r solutions. \r Poverty \r graduation \r models \r will \r be \r explored, \r combining\nrelief \r assistance \r with \r capacity \r building \r measures, \r to \r enable \r the \r poorest \r individuals \r and\nhouseholds \r to \r move \r out \r of \r poverty.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "### **Improved Protection Environment**\n\nWhile it is not a signatory to the Refugee Convention, Indonesia generally respects international and\ndomestic refugee law, particularly the principle of non-refoulement, and has demonstrated critical\nhumanitarian leadership in the region by consistently stepping forward to disembark boats carrying\nRohingya refugees. 2024 and 2025 present important opportunities to further advance the protection\nenvironment in the country, including the planned revision of a key domestic refugee law and the new\npolicies and priorities of recently elected national leaders.\n\nThe National Refugee Taskforce has initiated inter-ministry discussions on the revision of Presidential\nRegulation 125 of 2016. This Regulation provides the foundation for ensuring access to asylum and\nassigns UNHCR a key role in the management of asylum claims and solutions. UNHCR’s\nrecommendations for consideration in the revision have focused on the need for clarifying and\nexpanding the decree’s scope to ensure a strong refugee protection framework in Indonesia, including\nprotection safeguards that ensure entry to safe territory through channels other than the sea;\nincreasing joint activities with the Government, particularly in registration and documentation; and\nadvancing inclusion efforts in the country.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Kingdom, 56% in Sweden, 53% in Lithuania and 51% in the Czech Republic. The estimate for Poland was based on November 2022 National Bank of Poland survey data.\nThis relatively high value is supported by a UNHCR Assessment from 2nd November, in which survey results show that 72% of refugees are in the labour force, with 61% employed and 11% unemployed.\nThe most refugees are employed in manufacturing – 14%, accommodation and food service – 12%, and trade and repair – 6%. 89% of the survey respondents were women [29] .\n\n27 Deloitte elaboration based on the aggregation in OECD International Migration Outlook 2023 28 After the closing date for our report, NBP (2024) published new data, showing a slight drop in Ukrainian refugees employment rate to 62% that does not change our general conclusions.\n\n---\n[29] UNHCR Multi Sectorial Needs Assessment October 2023", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "November 2022 National Bank of Poland survey data"}], "vague_data": []}}}
{"input": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE Bulgaria (20 percentage points below the domestic figure). While differences in the typical household composition do explain some of the variation Bulgaria, for instance, has the largest share of retirees - the local context probably plays a more substantial role.\n\n**LABOR FORCE PARTICIPATION BY COUNTRY (AGE 15+), %** **[1]**\n\nHost country Ukraine refugees\n\n**UNEMPLOYMENT: REFUGEE POPLUATION VERSUS HOST**\n\n**COUNTRY, %** **[1]**\n\nHost country Ukraine refugees Bulgaria Czechia Hungary Moldova Poland Romania Slovakia Region\n\n1. Host country data based on indicators reported by the [ILO for 2022](https://ilostat.ilo.org/data/)\n\n**TOP EMPLOYMENT BARRIERS REPORTED BY UNEMPLOYED**\n\n**REFUGEES, % OF RESPONDENTS** **[1]**\n\nMoldova Bulgaria Romania Slovakia Poland Czechia Hungary Region\n\n1. Host country data based on indicators reported by the World Bank\n[(modeled ILO estimates for 2023)](https://data.worldbank.org/indicator/SL.TLF.CACT.ZS)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "indicators reported by the World Bank"}]}}}
{"input": "percent reported an increase, and 12 percent experienced a decrease since December 2020. This distribution\n\nsuggests that while citizenship has had a stabilizing effect for many households, it has not yet resulted in broad\nbased economic gains. However, the increase in income for nearly 4 out of every 10 households is a positive sign\n\nof economic progress and potential for further growth as the community continues to integrate more fully into the\n\nKenyan economy.\n\n**[www.unhcr.org](http://www.unhcr.org/)** 7", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The newly enacted asylum legislation does not include a specific legal provision governing access to financial\nservices nor access to administrative documents and certifications, including recognition of educational\nattainments received outside of the national system. However, within the context of local integration and\nself-reliance, Article 61 of the [2023 Decree](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf) outlines that the Government of Chad prioritizes actions for\nrefugees, among others, to access credits, microcredits and subsidies, as well as to obtain the recognition\nof documents issued by competent authorities.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**benefits.** Although the employment rate\nof Ukrainian refugees in Poland is already high when compared to other countries, there is still room for improvement.\nIncreasing the employment of refugees by 15 thousand people, which would close half of the gap between the employment rate of refugees and Poles, would yield at least PLN 1 billion of value added in the economy. This calculation is made under an assumption that those newly hired would be paid minimum wage and should be considered a lower-bound estimate, as it understates potential benefits. In part, the higher productivity of workers might boost the profits for employers, further enhanced by increased investment.\n\n#### **4.4 Persons not previously in employment**\n\n**Employment rates among Ukrainian**\n\n**refugees are exceptionally high, with**\n\n**only a minority requiring targeted**\n\n**assistance to enter the labour market,**\n\n**in particular those who were not**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "3% 2% 1% 0% 4000 10% 9% 8% 7% 6% 5% 4% 3% 2% 1% 0% 4000 Ukrainian refugee educational attainment implies from 18% (assuming refugees’ educational attainment from November 2022 survey) to 19% (July-August 2023) higher earnings than the general population. [36] Poviat-level geographical distribution of Ukrainian refugees is more concentrated in high productivity agglomerations, implying 7% higher earnings than for other workers registered for social security. [37] There is no publicly available hard data on the sectoral distribution of Ukrainian refugees, which we proxy by the growth in employees with Ukrainian citizenship registered for social security since the outbreak of the full-scale war in Ukraine (unfortunately this to some extent will be Ukrainian workers previously present in Poland who changed jobs) – this imperfect proxy implies 7% lower earnings than general workers. [38] Smaller firm sizes of employers of Ukrainian refugees imply their 8% lower productivity (and thus earnings) from the general population. [39] Most of all, occupational distribution of Ukrainian refugee workers from ZUS implies 21% lower earnings from the general population when measured by nine large occupational groups and 23% lower by detailed occupations. [40] 5000 6000 7000 8000 9000 10000 11000 12000\n\n---\n[40] Note that data on occupations of Ukrainian refugees is for persons with PESEL UKR registered for social security on 30th September 2023. It", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "November 2022 survey"}, {"text": "data on occupations of Ukrainian refugees"}], "vague_data": []}}}
{"input": "**The unemployment rate, however, is very high**\nIn contrast to labor force participation, the estimated unemployment rate of refugees from Ukraine is notably high when compared to that of host country nationals. At the regional level, the former stands at 14%, which starkly contrasts with the 3% weighted average for locals. In certain countries, such as Romania, the unemployment level exceeds 30%.\nAccording to unemployed respondents, challenges for securing employment include (1) local language proficiency (cited by over 50% of those surveyed), (2) lack of decent employment opportunities, (3) lack of opportunities matching the candidate’s skillset, (4) lack of age-appropriate opportunities, and (5) lack of childcare services. When queried about services that could enhance economic prospects of their families, the top two requests were for language training (33% of respondents) and job matching assistance (27% of respondents).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "constraints in accessing health services. Vaccine coverage increased notably in Moldova, Czechia and Bulgaria compared to 2023. In comparison, measles vaccination coverage within Ukraine reached 92% for the 1st dose of measles vaccine and 87% for second dose [8] (WHO, 2023).\n\nRegionally, only 54% of all children received the recommended second measles vaccine.\nVaccination coverage is below the 95% target required to interrupt community transmission of measles.\n\n**% OF CHILDREN RECEIVED AT LEAST ONE MEASLES**\n\n**VACCINE**\n\n2023 2024 Data need to be interpreted with caution as they rely on recall and were not verified against individual vaccination records.\n\nBulgaria Czechia Hungary Moldova Slovakia Poland Romania (2023 N=1,539, 2024 N=1,320) 8. [https://immunizationdata.who.int/dashboard/regions/european-region/UKR accessed on 06.11.2024](https://immunizationdata.who.int/dashboard/regions/european-region/UKR)\n\n**18**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n# **Contents**\n\nAcknowledgements\b 2 Summary of findings and recommendations\b 3 Background\b 4 Key findings\b 4 Methodology\b 13 Limitations\b 14\n\n# **Acknowledgements**\n\nWe extend our sincere appreciation to the numerous individuals and organizations whose contributions have been instrumental in the development of this report. The data analysis and writing was conducted by the interagency SEIS Livelihoods and Socio-Economic Inclusion Sector Analysis Group (SAG), led by Konstantin Fastovets (UNHCR). The team also consisted of David Mosler (ILO), Erin Neale (IOM), Arianna Pearlstein (UN Women), Yaroslav Smirnov (IOM), Elif Sucu (IOM), and Idil Yildiz (ILO).\n\nWe also express our gratitude to Jad Ghosn and the Regional Bureau for Europe (UNHCR) for their invaluable guidance and support in coordination, data preparation, and analysis.\n\n**Cover photograph:**\n\nAntonina (center) is at a CV support point, receiving assistance with preparing her resume.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Chart 7. Income of Ukrainian refugee households by source**\n\n**2%**\n\n**0.1%**\n\n**In 2024, Ukrainian refugee households**\n\n**increasingly sourced their income from**\n\n**Poland, rather than from Ukraine.** This\ncan be seen when comparing the MSNA survey conducted in July-August 2023 and SEIS in May-June 2024 (UNHCR, 2024, 2023).\n\nWhile some methodological differences apply, we can see that incomes earned in Poland grew from 81% in 2023 to 90% in 2024. Conversely, incomes from Ukraine declined from 18% to just 9%. This change demonstrates that Ukrainian refugees Work (regular, part-time, self-employment, remote, other, remote in Ukraine) Remittances from Ukraine Polish social benefits Ukrainian social benefits Other (capital, loans, other) Source: Deloitte own elaboration based on SEIS (May-June 2024) UNHCR (2024) survey.\n\nNote: Deloitte worked with disaggregated household-level data, ensuring comparability (converting all Ukrainian hryvnia incomes into Polish zloty based on daily exchange rates in the time of the interview, and 3-month into 1-month remittance incomes).\n\ncontinue to integrate economically.\nIt comes as no surprise, given that employment rates and wages of Ukrainian refugees in Poland increased during that time, which is the focus of the next chapter.", "output": {"entities": {"named_data": [{"text": "MSNA survey"}, {"text": "SEIS"}], "descriptive_data": [], "vague_data": [{"text": "disaggregated household-level data"}]}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n## **2.** Ukrainian refugees in the Polish labour market\n\n##### In the past year, as far as labour market integration is concerned, refugees from Ukraine improved in terms of employment and wages, yet they continue to be disproportionately skewed towards elementary occupations. They are also the group to see the fastest improvements, with the gap towards Polish citizens visibly closing across the entire wage distribution (2.1). The current refugee employment rates are only slightly lower than those for Polish citizens, and median net wages are at about four-fifths of the economy as a whole, which may nevertheless be overly optimistic when compared to gross or average wages (2.2).\n\n#### **2.1 Improving economic situation**\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Chart 9. Ukrainian refugee labour status** **[9]** **Chart 10. Ukrainian refugee median net wage** **[10]**\n\nWorking age (women 15-59, men 15-64) PLN, 18-64 age group 4,000 69%\n\n**Ukrainian refugees are more likely**\n\n**to be employed in elementary**\n\n**occupations than pre-war Ukrainian**\n\n**migrants, non-Ukrainian foreigners,**\n\n**and Polish citizens, but they are**\n\n**also the group to have improved**\n\n---\n[10] See the note on median wage estimation method in the Online Technical Appendix.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "from abroad (e.g. savings of refugees in Ukrainian banks) further strengthens that effect. In total, general government revenue increased by 2.0% in 2022, 2.75% in 2023, and 2.94% in 2024. In monetary terms this amounts to PLN 25.0 billion in 2022, PLN 39.1 billion in 2023, and PLN 47.0 billion in 2024 [22] . In the long term, refugees should increase annual general government revenue by around 2.7%.\n\n**Ultimately, Ukrainian refugees**\n\n**generate additional output and**\n\n**demand.** This results in an increase in real\nGDP, and is especially beneficial for public finance. Although the influx of refugees was costly at the start, the additional general government revenue they provided was more than enough to compensate for the expense [23] . Tight labour market helped absorb the increase in labour force, mitigating negative impacts of increased competition on the native workforce. Over time, increased productivity should benefit native workers, as it is the primary driver of long-term wage growth. [24]\n\n---\n[24] For a discussion on the stable long-term relationship between wages and labour productivity, see for example Meager & Speckesser (2011).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**refugees.** Although language skills\nimprove over time, still only 18% of refugees speak Polish fluently, usually those who arrived in Poland 29 months ago. On average, those at the beginner level have been in the country for only 18 months.\n\n**•** **Lack of work experience negatively**\n\n**affects the labour outcomes of older**\n\n**refugees.** Refugees who back in Ukraine\nmanaged the household or were not employed remain underemployed in Poland. The employment rate among the most enterprising refugees, who were self-employed back in Ukraine, is 91%. In contrast, those who did not work, study or train in Ukraine, have an employment rate in Poland of approximately 35%.\n\nlabour market, native workers increasingly shift to complementary, higher value and better paid tasks. This can be seen in the data, as Polish citizens are moving to better paid occupations. It constitutes a positive shock to productivity, which is what counterbalances labour market pressures.\n\n##### Macroeconomic impact\n\n**In 2024, Ukrainian refugees’ net**\n\n**impact amounted to 2.7% of the Polish**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The government of Chad has committed to providing refugees with access to quality education by integrating\nthem into the national education system. This integration allows all refugees and asylum-seekers to enrol in\nprimary, secondary, and higher education institutions, follow the Chadian curriculum, and obtain recognized\ndiplomas. The process of integrating refugees into the national education system has seen significant\nprogress since 27 November 2020, including the adoption of the ten-year refugee education strategy by\nthe government. In line with this, since 2018, the government has recognized and integrated 94 schools\nin camps and reception sites into the national system and opened seven examination centres in camps to\nensure that all students can take national exams under proper conditions.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "difference between close and far, and before and after mine opening, we have created a\n\ndifference-in-differences estimator.\n\nPanel B of figure 2 shows this strategy in a map, where the small blue circles show the treatment\n\nareas, and the 100-km-radius green circles show the geographic areas that constitute the control\n\ngroup. As is common in difference-in-differences analysis, the estimation relies on treatment\n\n11", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In these vulnerable conditions, any shock to the household economy -such as job loss, illness, or\nclimate related events- significantly impacts on refugees’ ability to cover the rent and utility costs\n(water, electricity), leaving them at heightened risk of eviction. [20] Climate related incidents are\nbecoming recurrent in the Brazilian context, such as floods and landslides in the south, as well as\ndroughts and wildfires in the center and the north of the country. [21] For instance, southern Brazil\nhas seen an increase of up to 30% in average rainfall over the last three decades [22] and, as of\nSeptember 2024, 59% of the Brazilian territory was affected by the most severe drought since\nnationwide measurements. [23]\n\n---\n[22] Presidência da Republica, « Southern Brazil has seen an increas of up to 30% in average annual rainfall over the last three decades »,", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**occupational downgrading.** The SEIS\nsurvey indicates that 34% of Ukrainian refugees currently employed in Poland work in the same sector as back in Ukraine, while 48% – in a different one. There is no data for 18% of workers – mostly made up of the youngest refugees who might not have worked back in Ukraine. Employment in one’s pre-displacement sector appears to boost the median net wage by about 6%, when compared to those who switch fields – a back-of-the-envelope calculation puts their median net earnings at 89% of the overall median. However, this likely overstates the true effect of staying in the same sector, since the higher-paid groups (for example, the majority of IT specialists) were more likely to remain in their original industry.\n\n**Highly skilled Ukrainian refugees**\n\n**are likely to suffer from significant**", "output": {"entities": {"named_data": [{"text": "SEIS\nsurvey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "While refugees and asylum-seekers have the right to reside in Chad, as enshrined in Article 21 of the law, and\nthere are no legislative restrictions on their choice of residence, multisectoral assistance is only provided\nby UNHCR and its partners in camps. Consequently, this assistance remains a decisive factor in refugees’\ndecision to stay in the camps. Refugees with the financial means to support themselves or engaged in\neconomic activities outside the camps are free to choose their place of residence in Chad.\n\n**3.2** **Right to work and rights at work**\n\nArticle 28 of the [Asylum law](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf) in the Republic of Chad grants refugees the most favourable treatment afforded\nunder similar circumstances to foreign nationals regarding the pursuit of gainful employment, whether\nsalaried, non-salaried and/or self-employed. The same provision pursues that refugees shall be exempted\nfrom certain restrictive measures imposed by the prevailing regulations on the employment of foreigners.\nAdditionally, Article 70 of the 2023 Decree stipulates that a refugee legally residing in Chad enjoys the same\nrights and standards of treatment as foreign nationals. Article 61 of the [2023 Decree specifically addressing](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf)\nlocal integration also guarantees the refugee right to access salaried or non-salaried employment to reach\nself-reliance.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "social insurance. Second, the statistical definition of an employed person is wider than just being registered with the Social Insurance Institution (Zakład Ubezpieczeń Społecznych, ZUS) on a certain day [3] . Third, some Ukrainians work in the shadow economy. The number of workers with Ukrainian citizenship and social insurance increased from only 33 thousand at the end of 2013 to 627 thousand at the end of 2021 – just before the refugee influx. Some of this increase reflects the transitioning of Ukrainians to more regular work arrangements and securing work permits. Following February 2022, the numbers further increased with the arrival of Ukrainian refugees. The data for mid-2024 shows 771 thousand workers with Ukrainian citizenship registered for social insurance, including 247 thousand refugees. Ukrainian refugees in Poland have been given PESEL UKR numbers\n\n- a version of an ID number assigned to\nevery Polish national – which made high quality data on their demographics easily available, though they may still be missing from most of the statistics compiled by the Polish statistical office.\n\n20% 19% Men Women 1% 1% 2% 3% 4% 7% 8% 4% 4% 9% 12% 7%\n\n#### **1.2 Households characteristics**\n\n**The structure of the Ukrainian**", "output": {"entities": {"named_data": [{"text": "PESEL UKR numbers"}], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n# Recommendations\n\nHost countries and communities have made commendable and continuous efforts to support refugees in accessing essential health and MHPSS services. While most respondents reported adequate access, barriers to services changed and increased for some refugees. These changes do not take the same form for all refugees, and intersectional factors related to gender, age, disability, and chronic illness continue to impact the experiences and needs of refugees from Ukraine in this regard. The recommendations below highlight key priorities and actions for governments and RRP partners to address these challenges and enhance refugees’ access to care in host countries.\n\nThese actions aim to support governments and local communities in strengthening health and MHPSS systems in areas impacted by refugee arrivals and advancing the integration of refugees into national systems. Achieving these goals will require long-term planning and sustained funding commitments.\n\n9. [Integraton of migrant and refugee data in health informaton systems in Europe: advancing evidence, policy and practce](https://doi.org/10.1016/j.lanepe.2023.100744)\n\n**28**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "treatment distance of 50 km, we no longer see a significant effect. In panel Ab, the results are\n\nreplicated using a spatial lag model, meaning that we allow for nonlinear effects with distance.\n\nIn reality, it seems like the electricity rate is much higher before a mine (dashed line) than with\n\nan active mine (the blue line). However, when the results are decomposed by migrant status in\n\npanel Ac of figure A1 (Annex) we find that migrants are driving the lower electricity rate. In\n\nfact, among nonmigrants, the electricity rate is higher 0–10 km from an active mine, although\n\nit is slightly lower 10–20 km away. [14]\n\n**6.3 Distributional effects on wealth and inequality**\n\nTable 9 presents the effects of mining on asset wealth and on asset wealth inequality. Wealth\n\ndata are available in the form of a wealth index, but only for the two last DHS surveys.\n\nFollowing Fenske (2015) and Flatø and Kotsadam (2014), we calculate inequality by means of\n\na Gini coefficient (recoding the wealth variable to be positive only, and using the command\n\n13 It is also possible that mining companies compete with households for electricity if supply cannot be increased\nin the short run.\n\n---\n[14] In panels Ba, Bb, and Bc of Appendix figure A1, we analyze access to radio. We learn that access to", "output": {"entities": {"named_data": [{"text": "DHS surveys"}], "descriptive_data": [], "vague_data": []}}}
{"input": "## Introduction\n\n##### Nearly two years after the beginning of the full-scale war in Ukraine, the positive impact of the refugees on the Polish economy becomes clearly visible.\n\nOn their arrival, the impact of refugees on the economy primarily manifested through higher consumption, that was financed mainly by increased governmental spending, civil society, international organisations, and savings brought from Ukraine. While these added to a significant initial increase in consumption, multiple sources of financing and a lack of aggregated data (particularly on general government expenses) make its magnitude uncertain. Although in the short term it stimulated the economy, drawing just on savings was not sustainable. Over time, however, refugees started to work as employees and entrepreneurs, adding not only to the demand, but also to the supply of the economy, contributing to its long-term growth. The focus of this report is this structural impact of refugees on the economy as consumers, employers, entrepreneurs, and taxpayers.\n\nThe beginning of the full-scale war in Ukraine resulted in a large inflow of refugees into Poland outlined in Chapter 1.\nThis cohort differs from the pre-2022 Ukrainian economic migrants, most notably in its demographic makeup which primarily comprises children and working age women.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n**SHARE OF POPULATION PAYING FOR RENTED HOUSING: HOSTS VS REFUGEES**\n\nShare of hosts living in rented housing (2023) Share of refugees fully paying for rent (2024) Share of refugees partially paying for rent (2024) 100% 80% 60% 40% 20% 0% Bulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia Region Source: Eurostat, survey data, SAG estimates\n\n**HOUSING COST AS A SHARE OF HOUSEHOLD DISPOSABLE INCOME**\n\nRefugees (2024) Hosts (2022) Bulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia Region Source: Eurostat, survey data, SAG estimates\n\n**REFUGEE POVERTY RATES WITH AND WITHOUT CORRECTION FOR EXCESSIVE HOUSING COSTS**\n\nRefugees (2024) Refugees with housing expense correction (2024) Hosts (2023) 65% 40% 52% 31% 46% 43% 37% Bulgaria Czechia Hungary Moldova Poland Romania Slovakia Estonia Latvia Lithuania Region Source: Eurostat, survey data, SAG estimates\n\n**6**", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "Eurostat, survey data"}], "vague_data": []}}}
{"input": "Skills-job mismatching also becomes evident when analyzing the current employment of refugees compared to their pre-war employment in Ukraine, as nearly 60% have transitioned to entirely different economic sectors.\nThis phenomenon is more pronounced among women, with 63% having shifted to roles outside their previous employment background, compared to 50% of men. One possible explanation for this discrepancy is the higher proportion of men employed in sectors like construction and IT prior to displacement. These fields often demand fewer country-specific qualifications, such as proficiency in the local language, thereby facilitating easier integration into similar roles in the host country.\n\n**DISTRIBUTION OF WORKING AGE POPULATION BY**\n\n**HIGHEST EDUCATION LEVEL ATTAINED**\n\nTechnical or Vocational Bachelor Master's Doctoral\n\n**WAGE PREMIUMS FOR EDUCATION LEVEL GAINS: HOSTS**\n\n**VERSUS REFUGEES, %**\n\nRefugee eduction wage premium (mean, 2024) Bachelor's or above Hosts (2023) Refugees (2024) Source: Survey data, ILO 1% Host education wage premium (median, 2022) Technical or vocational Note: Wage premiums computed with lower secondary education as the baseline Source: Survey data, Eurostat, SAG estimates", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "Survey data, ILO"}, {"text": "Survey data"}]}}}
{"input": "Employment continues to be closely associated with lower poverty rates, though ultimately, it’s the size of income that is generated by working household members that makes the biggest difference. Considering that the share of working-age refugees that are employed is nearing host population levels after rising further in 2024, attention should now turn to wages. Data on the latter, which was derived from household level indicators, demonstrates that refugees on average make two-thirds of what the local population does per hour of work. Low wage premiums for higher education levels and the fact that some 60% of current refugee employees have a background in an entirely different sector of the economy, suggest the presence of underemployment and skills mismatching. This assertion is corroborated by nearly 35% of employed refugees in the region reporting few available jobs with adequate pay, lack of positions that match their skills, or issues with getting their qualifications recognized. Moreover, almost the same percentage indicate lack of local language knowledge to be a problem, a well-acknowledged barrier to skilled employment.\n\n**Based on the above findings it is recommended that:**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "household level indicators"}]}}}
{"input": "##### **September/ October 2023 report**\n\n###### Venezuela\n\n**trafficking networks.** After bilateral\n\nmeeting between the Protection Cluster,\n\nthe WGTiP and the FSL Cluster, a focal\n\ngroup was organized on October 10th.\n\nA total of 7 participants from UN Agen\ncies, AoRs, and local NGOs participated.\n\nWG members actively participated by\n\nsharing field experiences and proposing\n\nrecommendations to address challenges\n\nraised during the discussion.\n\n**VIII. Monthly Meetings of the**\n\n**WGTiP**\n\n**The WGTiP convenes monthly to**\n\n**review its working plan and provide**\n\n**a platform for members to discuss**\n\n**trends and activities related to TiP. In**\n\n**the last meeting, the WG collectively**\n\n**decided to establish a Task Force to**\n\n**draft a guide on security for orga-**\n\n**nizations working with Victims of**\n\n**Trafficking (VoT).** Additionally, members\n\nhave developed standardized training\n\nand sensitization activities/workshops to\n\nimplement in communities on the topic of\n\nTiP. These trainings will be beneficial to\n\nother organizations addressing human\n\ntrafficking issues. In October’s monthly\n\nmeeting, the WG hosted the office of UN\n\nSpecial Rapporteur for Trafficking in Per\nsons. The meeting involved discussions\n\non potential collaboration with WG mem\nbers and how the UN Rapporteur's office\n\ncan support advocacy efforts.\n\nMember organizations also shared infor\nmation on available services for victims", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Note:_ Robust standard errors clustered at the DHS cluster level in parentheses. All regressions control for year and\ndistrict fixed effects, urban dummy, age, and years of education. Active is active status of mine in the survey year.\n\n*** p<0.01, **p<0.05, *p<0.1. Results for women’s partners also available upon request. OLS = ordinary least\nsquares. The women and men samples have different sampling frames and therefore we are not analyzing these\nresults jointly.\n\nTwo further caveats should be noted: (i) with many variables tested, such evidence should not\n\nbe given too much weight, (ii) number of sampled men in the treatment category is quite small.\n\nOut of 7,157 sampled med, only 484 men live close to active mines. A bigger treated sample\n\nwould provide more reliable results. [10]\n\n**5.2 Child health**\n\nWe explore effects on child health, such as size at birth, infant mortality, anthropometrics, and\n\nincidence of cough, diarrhea, and fever. Panel A and Panel B use different variable definitions\n\n---\n[10] Results for sampled women’s partners are similar.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "those people fell outside the definitions of population used by Statistics Poland (Główny Urząd Statystyczny, GUS, Poland’s statistical office). The National Bank of Poland estimated that between 2014 and 2018, there were approximately one to two million Ukrainian workers in Poland at a time (Strzelecki, Growiec and Wyszyński, 2022). According to the 2021 Polish National Census, one year before the outbreak of the full-scale war in Ukraine there were about one million Ukrainian citizens residing in Poland, almost all of them on a temporary basis.\n\nAfter the full-scale Russian invasion of Ukraine, Poland experienced a massive influx of refugees – with more than 27 million border crossings from Ukraine and more than 1.9 million applications for protection submitted by April 7, 2025 [1] . Not all of those people stayed in Poland. Many of them later returned to Ukraine or moved to other countries. By February 14, 2025, PESEL UKR [2] holders who remained in Poland stood at less than 1 million, while the border movement balance between Poland and Ukraine was slightly below 2 million.\n\n---\n[1] UNHCR data, https://data2.unhcr.org/en/situations/ukraine\n[2] PESEL UKR is a version of Polish national ID number for Ukrainian citizens in connection with the armed conflict in the territory of that country.", "output": {"entities": {"named_data": [{"text": "2021 Polish National Census"}], "descriptive_data": [{"text": "UNHCR data"}], "vague_data": [{"text": "UNHCR data"}]}}}
{"input": "The escalatation of war 2022 in Ukraine caused a large inflow of refugees into Poland. While some refugees from Ukraine have since returned to Ukraine or gone further to Germany or other countries, in October 2023 close to 957 thousand remained in Poland (identified by active PESEL UKR numbers). They consist primarily of children and working aged women. Despite the forced nature of displacement, war trauma, and caregiving responsibilities, refugees from Ukraine very quickly entered the labour market as employees and entrepreneurs. The precise number of refugees from Ukraine working in Poland remains uncertain, with our estimates ranging from 225 to 350 thousand. The lower bound is the number of social security registrations and understates the actual figure, as some jobs may not require social contributions or remain in the informal sector. The higher bound is the product of employment rates from surveys of refugees from Ukraine, and their working age population from the active PESEL UKR database. By JulyAugust 2023 Ukrainian refugee households supported themselves, with 80% of their incomes coming from work. [49]\n\n---\n[49] Deloitte calculations based on Multi-Sector Needs Assessment Poland 2023 survey data provided by UNHCR.", "output": {"entities": {"named_data": [{"text": "active PESEL UKR database"}, {"text": "PESEL UKR numbers"}], "descriptive_data": [{"text": "Multi-Sector Needs Assessment Poland 2023 survey data"}, {"text": "surveys of refugees from Ukraine"}], "vague_data": [{"text": "surveys of refugees from Ukraine"}]}}}
{"input": "**Figure 1 Ghana’s annual gold production and world price of gold**\n\nGhana is the second-largest gold producer in Africa after South Africa, with gold production\n\naveraging 77 tons per year (Gajigo, Mutambatsere, and Mdiaya 2012). In 2011, Ghana’s\n\nmineral sector accounted for about 14 percent of total tax revenues and 5.5 percent of the gross\n\ndomestic product (GDP) (Bermúdez-Lugo 2011), as well as 44 percent of Ghanian exports\n\n(Gajigo, Mutambatsere, and Mdiaya 2012). This makes the gold mining industry one of the\n\ncountry’s most important industries, and an essential industry to study.\n\nSimilar to gold mining in other African countries (see Gajigo, Mutambatsere, and Mdiaya", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In conclusion, the protection incidents evidenced in the analysis partially overview the situation in both countries\nwhere the data were collected. The number of protection incidents and victims is higher than what is represented\nin this report for September 2022. In DRC, the new protection monitoring platform still needs to be fully deployed\ncountrywide, and efforts are underway to have data that will reflect the real situation. In Mozambique, the data\nreported in this report concerns only one province, Cabo Delgado, where the protection monitoring is implemented.\nEfforts are also underway to have functioning protection monitoring in the rest of the affected provinces.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "REGIONAL BUREAU FOR SOUTHERN AFRICA\n\n###### **POPULATION OF CONCERN IN SOUTHERN AFRICA REGION**\n\n30 September 2022\n\n**PoCs IN SOUTHERN** **AFRICA REGION***\n\n**521,512** **REF**\n\n**41,283** **REF**\n\n**13,762** **ASY**\n\n**1,291** **ASY**\n\n**5,526,022** **IDP**\n\n**REF**\n\n**ASY**\n\n**OOC**\n\n**RET**\n\n**KEY FIGURES**\n\n## **8,572,919**\n\nTotal Population of concern\n\n###### **1,099,585**\n\nRefugees, asylum-seekers, other\nof concern & returnees**\n\n**785,119**\n\n**278,090**\n\n**36,165**\n\n**211**\n\n###### **7,473,334**\n\nConflict induced and Natural Disaster IDPs\n\nNatural Disaster IDPs\n\n**528,466**\n\n**7%**\n\n**6,419,356**\n\n**86%**\n\nIDPs RET\n\n**525,512**\n\n**7.0%**\n\ndo not imply official endorsement or acceptance by the United Nations\n\n**Author: UNHCR DIMA - RSA** Contact : rsarbdima@unhcr.org **Source:** UNHCR Primes, Government, IOM, OCHA, UNHCR\n\n**Author: UNHCR DIMA - RSA** Contact : rsarbdima@unhcr.org **Source: REF, ASY, OOC, RET** (UNHCR PRIMES, Government); **IDP DRC** (OCHA); IDP Zimbabwe & Mozambique (IOM); **IDP ROC** (Government, Ministry of Social Affairs and Humanitarian Action (MASAH).\n\n*PoCs = Persons of Concern   ** REF = Refugee; ASY = Asylum-seeker; OOC = Other person of concern; RET = Returnee. DRC = Democratic Republic of the Congo  ROC = Republic of the Congo Date of creation : 30 September\n2022\n\nFor more information visit: UNHCR Data Portal", "output": {"entities": {"named_data": [{"text": "UNHCR PRIMES"}], "descriptive_data": [], "vague_data": []}}}
{"input": "### **OPERATIONAL HIGHLIGHT**\n\n##### **September/ October 2023 report**\n\n###### Venezuela\n\n**Some key achievements**\n\n- Humanitarian Needs Overview (HNO)\n\nProcess\n\n- Coordination with other platforms,\n\nsubnational Clusters, ICCG, and Partners\n\n- Accountability for Affected Populations\n\n(AAP) WG\n\n- GPC Townhall\n\n- La Carnada Play\n\n- Annual TiP Bulletin 2022-2023\n\n- Food Security and Livelihoods (FSL) and\n\nTrafficking in Persons (TiP)\n\n- Monthly Meetings of the WGTiP\n\n- Protection Mainstreaming Training\n\n- Training on Mixed Migration and Durable\n\nSolutions\n\n- Reporting Transition to 345W\n\n- Focal Group Discussions with LGBTIQ+\n\nOrganizations for Thematic Protection\n\nAnalysis Update (PAU)\n\n- Mental Health and Psychosocial Support\n\n(MHPSS) Coaching and Training of Trainers\n\n(ToT)\n\n- Participation in the Gender ToT for\n\nGovernment Officials\n\n**4**\n\n**I. Humanitarian Program Cycle**\n\n**2024: Humanitarian Needs**\n\n**Overview (HNO) Process**\n\n**September was dedicated to identi-**\n\n**fying and define indicators and the**\n\n**local adjustment of severity scales**\n\n**for People in Need (PIN) and Needs**\n\n**Severity Calculation as part of the**\n\n**Humanitarian Needs Overview (HNO)**\n\n**process.** The indicators defined for the\n\nProtection Cluster (PC) Severity and PIN\n\ncalculation are Protection Risks, Protec\ntion Risks linked to trafficking in person,\n\nAccess to Documentation, Access to\n\nthe Justice System, Negative Coping\n\nMechanisms in Protection, Violent", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**than native workers.** There may be different reasons for this\nas perhaps immigrants have character traits that make them more inclined towards entrepreneurial activity (unclear in the case of refugees), or maybe it is a way to avoid occupational downgrading as immigrants find it difficult to prove their educational and professional credentials from home countries.\nNotwithstanding the reason, such effects are observed across the OECD countries (OECD, 2011). In a recent paper, Anelli, Basso, Ippedico, and Peri (2023) look at Italian data, finding that one standard deviation increase in emigration rate generates 4.8% decline of business formation in the municipality of origin.\nThe authors use existing migration networks to ensure causality of the results. Nevertheless, it is unclear whether immigrantcreated businesses are more successful from the native ones, but one could speculate that a higher rate of trying new business ideas spurs more successes.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "Italian data"}], "vague_data": []}}}
{"input": "Outcomes were relatively consistent across types of support. Those who accessed only formal support (e.g., psychotherapy or structured group interventions) reported improvement in 88% of cases (with 34% stating “yes” and 54% reporting “slight” improvement). Individuals relying on only informal support (e.g., help from friends, family, or employers) reported improvement in 91% of cases, with slightly fewer reporting “yes” (29%) and a higher percentage indicating “slight” improvement (62%). Meanwhile, those who accessed both formal and informal support were slightly more likely to state “yes” regarding improvement (40%), with 51% indicating “slight” improvement (for a total of 91% of cases reporting some improvement). Although differences are small, results imply that a combination of support types may be associated with enhanced perceived effectiveness. Further research is needed to explore this potential relationship.\n\nThese findings demonstrate that, overall, those who accessed support perceived this support to be beneficial. Results reinforce the importance of integrating both formal and informal support mechanisms to maximize positive outcomes, as well as tailoring interventions to demographic and country-specific needs to enhance the well-being of individuals receiving MHPSS services. The data also\n\n**23**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited (DTTL), its global network of member firms, and their related entities (collectively, the “Deloitte organization”). DTTL (also referred to as “Deloitte Global”) and each of its member firms and related entities are legally separate and independent entities, which cannot obligate or bind each other in respect of third parties. DTTL and each DTTL member firm and related entity is liable only for its own acts and omissions, and not those of each other. DTTL does not provide services to clients. Please see www.deloitte.com/about to learn more.\n\nDeloitte provides industry-leading audit and assurance, tax and legal, consulting, financial advisory, and risk advisory services to nearly 90% of the Fortune Global 500® and thousands of private companies. Our people deliver measurable and lasting results that help reinforce public trust in capital markets, enable clients to transform and thrive, and lead the way toward a stronger economy, a more equitable society, and a sustainable world. Building on its 175-plus year history, Deloitte spans more than 150 countries and territories. Learn how Deloitte’s approximately 457,000 people worldwide make an impact that matters at www.deloitte.com.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n**Republic of Moldova: the case for housing costs corrections in income-based poverty metrics**\n\nData from the Republic of Moldova highlights the limitations of poverty metrics that rely solely on disposable income, as they fail to account for vulnerability related to asset ownership. Based on income alone, the 2024 poverty rate suggests that Ukrainian refugees are able to attain a higher standard of living than their hosts, with only 10% living in poverty compared to 32% of Moldovans. This apparent disparity is largely driven by the sizeable financial support that Ukrainians received from humanitarian organizations in 2024, which amounted to 44% of their total household income. While the above comparison could suggest that the provided aid is excessive, such an interpretation overlooks an important factor – namely that only 5% of Moldovans incur rental expenses compare to 41% of refugees. In fact, including utilities, housing costs were estimated to consume 46% of refugees’ disposable income (inclusive of humanitarian aid), whereas they account for just 14% for Moldovan households. In essence, these findings indicate that refugees are using the entirety of their aid to cover accommodation needs. Adjusting disposable income at the household level to reflect these additional housing expenses raises the poverty rate for refugees to 43%, surpassing that of Moldovans.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n#### **2.2 Current occupational situation**\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland Administrative ZUS data can be used as a proxy for both average and _gross_ earnings percentages. On June 30, 2024, average bases for social contributions of Ukrainian refugees accounted for just 64% of those of Polish citizens. However, this is only relative to Polish citizens not all workers in the economy as a whole, and comes with other caveats of administrative instead of survey data sources – data given on a particular day instead of period average, the shadow economy unaccounted for, different contributions based on the type of contract, no data for farmers who belong to a separate social insurance scheme.\nAlso, the ZUS data, that is available, is much more limited that the SEIS survey data primarily used in this report.\n\n**Ukrainian refugees in Poland have**\n\n**clearly improved their economic**", "output": {"entities": {"named_data": [{"text": "SEIS survey data"}], "descriptive_data": [{"text": "Administrative ZUS data"}], "vague_data": []}}}
{"input": "**age.** The best population data available\nis the regularly updated active PESEL database. [4] According to the registry, 61.5% of the registered are women and 38.5% are men. The database also includes the age of PESEL UKR holders, which indicates that over half (57.4%), i.e. more than 560 thousand people, are of working age (18-65). While the male and female shares of people below 18 years of age (20% and 19%, respectively) and 66+ (1% and 3%) are similar, there is a large difference among productive-age individuals, with women 18-65 making up 40% and men only 18% of Ukrainian refugee population. This is largely due to the conscription of military aged men in Ukraine.\n\n66+ 56-65 46-55 36-45 26-35 18-25 <18\n\n---\n[4] Available in the repository maintained by the government https://dane.gov.pl/pl/dataset/2715 as well as UNHCR data portal https://app.powerbi.com/", "output": {"entities": {"named_data": [{"text": "active PESEL database"}], "descriptive_data": [{"text": "UNHCR data portal"}], "vague_data": []}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n**HOUSEHOLD INCOME DISTRIBUTION BY SOURCE AND POVERTY CATEGORY**\n\nEmployment Family support Social protection (host country) Old age pension (Ukraine) 12% 67% Social protection (Ukraine) 35% Humanitarian cash 8% 13% 23% 6% Other 5% 3% 3% 5% Below the poverty line Below the poverty line after housing cost correction Above the poverty line after housing cost correction Source: Survey data, SAG estimates 26% 88%\n\n**Higher employment earnings were the main driver behind the drop in poverty rates from**\n\n**2023**\n\nThe mean monthly equivalized household income [12] of Ukrainian refugees across the seven countries surveyed in both rounds increased by 38% from last year, to an equivalent of EUR 763. This increase was much higher than the 4% rise in the regional poverty threshold over the same time.\n\nApproximately 90% of the increase in refugee household income can be attributed to higher employment earnings, driven by a combination of rising employment rates and wage growth. A significantly smaller, though still notable, contribution came from increased financial support from families in Ukraine, although this finding may partially be an artifact of adjustments to the survey questionnaire [13] .", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "Survey data"}]}}}
{"input": "_UNHCR \r Discussion \r Paper \r –15 \r June \r 2013_\n\nengagement \r of \r key \r partners, \r including \r relevant \r development \r actors \r and \r the \r private\nsector \r since \r the \r early \r stage \r will \r be \r a \r crucial \r component \r of \r UNHCR’s \r strategy.\n\nCurrent \r co-­‐ordination \r fora \r include \r the \r South-­‐East \r Consultation \r Platform, \r led \r by \r UNHCR,\nconsisting \r of \r UN, \r NGO, \r donors, \r Government \r and \r other \r partners, \r including \r the \r Myanmar\nPeace \r Centre \r (MPC) [9] . \r This \r currently \r meets \r every \r 2-­‐3 \r months \r in \r Yangon. \r The \r objective \r of\nthe \r Platform \r is \r to \r maintain \r a \r common \r understanding \r of \r the \r operational \r environment\nand \r challenges \r in \r the \r South-­‐East \r and \r to \r forge \r strategic \r partnerships. \r UNHCR \r also \r chairs\nthe \r National \r Protection \r Working \r Group.\n\nMonthly \r inter-­‐agency \r co-­‐ordination \r meetings, \r chaired \r by \r UNHCR \r and \r attended \r by\nhumanitarian \r partners, \r are \r currently \r held \r in \r Mawlamyine \r (Mon \r State), \r Taungoo \r (Bago\nRegion), \r and \r Myeik \r and \r Dawei \r (Tanintharyi \r Region). \r Inter-­‐agency \r meetings \r also \r take\nplace \r in \r Loikaw \r (Kayah \r State), \r chaired \r on \r a \r rotational \r basis \r amongst \r agencies.\n\nIn \r January \r 2013, \r UNHCR \r also \r initiated \r cross-­‐border \r meetings \r between \r UNHCR\nMyanmar \r and \r UNHCR \r Thailand.\n\n---\n[9] The \r Myanmar \r Government \r draft \r Framework \r for \r Economic \r and \r Social \r Reform \r 2012-­‐2015 \r tasks \r the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**WEIGHTED AVERAGE MONTHLY EQUIVALIZED INCOME EVOLUTION, EUR**\n\n800 600 400 200 0 Equivalized income 2023 Employment Family Host country income support social protection Ukraine social protection (inc.\npensions) Humanitarian Other Equivalized cash income 2024 Note: Only includes data from the 7 countries surveyed in both rounds (Bulgaria, Czech Republic, Hungary, Republic of Moldova, Poland, Romania, and Slovakia) Source: Survey data, SAG estimates 12. Household disposable income adjusted for size, as per Eurostat’s methodology 13. The 2024 survey probed for income from family in Ukraine more explicitly\n\n**9**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "Survey data"}]}}}
{"input": "The established mechanisms in refugee camps and in N’Djamena to ensure substantial refugee participation\nat local levels remain functional. This includes elected committees representing refugees, along with separate\ncommittees for men, women and children/young individuals. Sectoral committees such as those for livelihoods,\nchild protection, education and healthcare are also still active. Additionally, inclusive and mixed committees\nof leaders or sectoral representatives in refugee hosting villages continue to facilitate interaction between\nmembers of both communities, addressing both general and specific issues. During the COVID-19 pandemic,\nwhen physical access to refugees became difficult due to government restrictions, alternative communication\nmethods (e.g. posters, banners, radio announcements, phone calls and SMS), and mobile protection teams,\nwere utilized by CNARR to stay in touch with refugee communities.\n\n**2.4** **Access to civil registration and documentation**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Similarly to the above results, an early analysis by Gromadzki and Lewandowski (2023) found no impact on the employment rate or unemployment rate. In a peerreviewed scientific article, they examined the impact of Ukrainian refugees on the labour market outcomes of Polish women from January to April 2022 (as most Ukrainian refugees are female). They found that the proportion of Ukrainian refugees in a given poviat had no statistically significant impact on the employment rate or unemployment rate of Polish women.\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Chart 29. Effect of a 1 pp. change in employment share of Ukrainian refugees on gross wage change**\nCross-section model of all 380 poviats in 2023. Results are statistically significant at a 0.01 level.\n\n200 150 100 50 0 OLS IV (pupils) IV (2019) IV (both)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "because of the nature of the data. Panel A uses three variables that reflect conditions around the\n\nyear of birth of the child. Note that women report their birth history, in what year the child was\n\nborn, and the baby’s health. She reports this information in the survey year, but retroactively,\n\nrecollecting the year of birth. Therefore, we deem that the birth year mining activity is more\n\nrelevant than the survey year mining activity for the outcomes in Panel A. In particular, we test\n\nif an active mine nearby in the birth year of the child influences the baby’s size at birth, infant\n\nmortality, and the number of antenatal visits. In Panel B we use the main specification of mining\n\nactivity in the survey year, as these variables are more reflective of current conditions in the\n\nsurvey year than past conditions around the time of the birth.\n\nPanel A of table 5 shows that infants in active mine communities are less likely to be born large,\n\nand that the mother had insignificantly fewer prenatal visits. However, infant mortality\n\ndecreases by 4 percentage points. Splitting the sample by gender, we note that this decrease is", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "# Abstract\n\nThe beginning of the full-scale war in Ukraine in February 2022 resulted in a large outflow of refugees, reaching more than 6 million globally.\n\nMuch of this exodus happened through the Polish border. As of October 2023, almost 1 million Ukrainian refugees were living in Poland. While in the past decade Poland experienced large labour migration from Ukraine, the refugee inflow had a different demographic composition.\nIt primarily included working age women (41%) and children (40%). These refugees from Ukraine did not plan to move, and many had special needs. Despite these difficulties, refugees began entering the labour market surprisingly quickly – attaining an employment rate of 28% in May 2022 and 65% in November 2022 (NBP, 2023). By July-August 2023 Ukrainian refugee households supported themselves, with 80% of their incomes coming from work. [1]\n\n---\n[1] Deloitte calculations based on Multi-Sector Needs Assessment Poland 2023 survey data provided by UNHCR.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "Multi-Sector Needs Assessment Poland 2023 survey data"}], "vague_data": []}}}
{"input": "Power BI Desktop Somalia’s Solutions Pathways The Department of Poverty Reduction and Durable Solutions of the Ministry of Planning, Investments, and Economic Development (MoPIED) in Somalia continues to play a leading role in overseeing and addressing solutions to internal displacement in the country.\nIn 2024, the department conducted a series of durable solutions pathways consultations across all federal member states and the Banadir Regional Administration (BRA), resulting in the National Solutions Pathways Action Plan. These consultations aimed to identify key approaches to facilitate the durable solutions pathways of one million Internally Displaced Persons (IDPs) from their displacement situations, in alignment with the National Durable Solutions Strategy, the National Development Plan and the United Nations Secretary-General’s Action Agenda on Internal Displacement, emphasising three interconnected goals: achieving durable solutions, ensuring protection and assistance, and preventing future displacement.\nBaseline Analysis This document presents key quantitative data under each of the six Solutions Pathways: 1) Government leadership, 2) Access to Basic Services, 3) Employment and Livelihood Opportunities, 4) Legal Documentation, HLP and Access to Justice, 5) Climate Change and Resilience. Pathway 6 refers to Data for Solutions, which is cross-cutting and covers MoPIED's Durable Solutions Progress (DSP) Survey, was supported by IOM Somalia in 2024. Data from this survey is presented under each of the six pathways in this document. Data collected by UNHCR related to protection and conflict sensitivity is also presented, highlighting key cross-cutting issues to consider in implementing the plan.", "output": {"entities": {"named_data": [{"text": "Durable Solutions Progress (DSP) Survey"}], "descriptive_data": [{"text": "Data collected by UNHCR"}], "vague_data": []}}}
{"input": "While \r UNHCR \r has \r been \r present \r and \r operational \r in \r South-­‐East \r Myanmar \r since \r 2004, \r the\nUNHCR \r framework \r for \r co-­‐operation \r with \r the \r Government \r of \r the \r Union \r of \r Myanmar \r in\nthe \r South-­‐East \r is \r defined \r by \r a \r draft \r Letter \r of \r Understanding \r (LOU) \r with \r its \r line \r Ministry,\nthe \r Ministry \r of \r Border \r Affairs \r (NaTaLa). \r The \r LOU \r articulates \r UNHCR \r and \r NaTaLa’s\nresponsibilities \r in \r regard \r to \r the \r implementation \r of \r programmes \r aimed \r at \r improving\nlivelihoods \r in \r communities \r affected \r by \r displacement, \r reducing \r the \r risk \r of \r further\ndisplacement, \r and \r specifically \r creating \r the \r appropriate \r conditions \r for \r return \r for \r IDPs\nand \r refugees. \r The \r current \r LOU, \r which \r includes \r Kayin, \r Mon, \r Kayah, \r Shan \r and \r Chin \r States,\nand \r Bago \r and \r Tanintharyi \r Regions, \r was \r signed \r on \r 10 \r June \r 2013.\n\nOnce \r the \r required \r safeguards \r are \r in \r place \r for \r the \r return \r of \r refugees \r and \r an \r organized\nprogramme \r is \r to \r be \r launched, \r a \r tripartite \r agreement \r between \r Myanmar, \r Thailand \r and\nUNCHR \r should \r form \r the \r main \r legal \r framework \r for \r the \r voluntary \r repatriation \r and\n\n6 \r Executive \r Committee \r Conclusion \r 29 \r of \r 1983 \r calls \r upon \r Governments \r to \r facilitate \r the \r work \r of \r UNHCR \r “in\ncreating \r conditions \r favourable \r to \r and \r promoting \r voluntary \r repatriation, \r which \r whenever \r appropriate \r and\nfeasible \r is \r the \r most \r desirable \r solution \r for \r refugee \r problems.” \r Also \r refer \r to \r Executive \r Committee \r Conclusions", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n### **Social cohesion and** **MHPSS**\n\nAn association between perceived hostility and mental health challenges remains evident across the region, with households experiencing hostility in their social environment more likely to report mental health and psychosocial problems (44%) compared to those not experiencing hostility (31%). Perceived hostility may increase vulnerability to distress, while distress may in turn influence individuals to perceive their environments as more hostile, creating a reinforcing cycle. This trend is consistent across countries, with notable between-country differences: Romania continues to report the highest percentage of problems both for households experiencing hostility (64%) and those not experiencing hostility (49%), while Czechia consistently reports the lowest percentages in both categories (24% and 20%, respectively). Significant differences also emerged between countries such as Hungary and Moldova, where the prevalence of mental health and psychosocial problems in households experiencing hostility is relatively high (63% and 56%, respectively), but the prevalence among those not experiencing hostility diverges dramatically (32% in Hungary versus 16% in Moldova). These findings highlight the importance of addressing perceived hostility and its impact on mental health, through targeted, country-specific MHPSS and social cohesion interventions.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "UNHCR \r ProGres \r data \r on \r the \r 83,044 \r registered \r refugees \r in \r Thailand \r indicates \r an\nestimated \r 84 \r per \r cent \r are \r ethnic \r Karen \r and \r 12 \r per \r cent \r are \r ethnic \r Karenni. \r The\nremaining \r 4 \r per \r cent \r are \r of \r Burman, \r Shan, \r and \r Mon \r descent, \r and \r other \r groups. \r The\nmajority \r of \r registered \r refugees \r come \r from \r Kayin \r State \r (65.3 \r per \r cent), \r followed \r by\nKayah \r (14.6 \r per \r cent), \r Tanintharyi \r (7.3 \r per \r cent), \r Bago \r (5.2 \r per \r cent) \r and \r Mon \r (5 \r per\ncent). \r (Annex: \r Myanmar \r Thailand \r Border \r – \r Refugee \r Overview, \r as \r of \r end \r of \r March \r 2013)", "output": {"entities": {"named_data": [{"text": "UNHCR \r ProGres \r data"}], "descriptive_data": [{"text": "UNHCR \r ProGres \r data"}, {"text": "UNHCR ProGres data"}], "vague_data": []}}}
{"input": "Securing \r durable \r solutions \r is \r fundamentally \r linked \r to \r the \r restoration \r of \r national\ncapacity \r to \r provide \r for \r the \r protection \r and \r welfare \r of \r formerly \r displaced \r communities,\nand \r UNHCR’s \r role \r should \r be \r designed \r to \r support \r such \r an \r outcome, \r through \r systematic\nengagement \r with \r key \r Government \r counterparts, \r civil \r society \r and \r other \r national\nstakeholders.\n\nNational \r authorities \r have \r primary \r responsibility \r to \r secure \r durable \r solutions \r for \r those\nwho \r have \r been \r formerly \r displaced, \r while \r UNHCR \r and \r other \r humanitarian \r and\ndevelopment \r actors \r have \r a \r complementary \r role.\n\nCo-­‐ordination \r and \r multi-­‐sector \r engagement \r is \r also \r critical \r to \r the \r sustainable\nreintegration \r of \r refugees \r and \r durable \r solutions \r for \r IDPs [8] . \r Therefore, \r mobilising \r the\n\n---\n[8] See \r UNHCR’s \r 2008 \r Policy \r on \r the \r Return \r and \r Reintegration \r of \r Refugees \r and \r IDPs, \r and \r the \r 2011 \r Secretary-­‐", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Table 13 Effects of gold production at the district level on employment**\n\nPanel A: Using production in the previous period\n(3) (4)\nnot agriworking culture\n\n(3) (4) (5) (6) (7) (1) (2)\nnot agri- service or profess- manual earns works all\nworking culture sales ional work cash year\n\ngold period 0.003 -0.009** 0.003* 0.004*** -0.002 -0.001 0.008**\ndistrict (0.004) (0.004) (0.002) (0.002) (0.004) (0.002) (0.003)\n\n(4)\nagriculture\n\n(5)\nservice or\nsales\n\n(6)\nprofessional\n\n(7)\nmanual\nwork\n\n(1)\nearns\ncash\n\nobservations 19,175 19,175 19,175 19,175 19,175 19,270 15,991\nR-squared 0.207 0.327 0.127 0.137 0.037 0.213 0.278\nPANEL B. Using production in the same year\n(3) (4) (5) (6) (7) (1) (2)\nnot agri- service profess- manual earns works\nworking culture or sales ional work cash all year\n\ngold year 0.012 -0.033 0.020 0.019* -0.018 -0.010 0.041***\ndistrict (0.022) (0.025) (0.013) (0.011) (0.015) (0.009) (0.008)\n\nobservations 19,175 19,175 19,175 19,175 19,175 19,270 15,991\nR-squared 0.207 0.327 0.128 0.137 0.037 0.213 0.278\n\n_Note:_ Robust standard errors clustered at the district level in parentheses. All regressions control for year and\ndistrict fixed effects, urban dummy, age, and years of education. *** p<0.01, **p<0.05, *p<0.1.\n\n**7.3 Investigating spillovers**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "During the 2019 Global Refugee Forum, the Government of Chad committed, among other things, to\nissuing biometric Refugee Identity Cards and Machine-Readable Refugee Convention Travel Documents\n(MRCTDs) to meet international standards. A study by the National Agency for Secure Documents (Agence\nNationale des Titres Sécurisés, ANATS), the only competent authority for issuing biometric identity and\ntravel documents, outlined a technical proposal released in March 2023 for the project’s implementation,\nbut financial resources are currently lacking to operationalize this pledge. As of 30 June 2023, no biometric\nidentity card neither CTD has been delivered by the competent national authorities (ANATS) to refugees.\n\nThe 2023 Decree specifies that CNARR and UNHCR collaboratively handle the reception and pre-registration\nof new arrivals at the international border, following the completion of police formalities. The pre-registration\nspecifically pertains to situations involving arrivals in groups. In practice, the entire registration of newly\narrived asylum-seekers remains jointly conducted by CNARR and UNHCR. This involves collecting all the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "migrants can thus in part be because a less-well-off part of the population chooses to migrate to\n\nmining areas, not that they are made worse off because of the mine activities.\n\nWe also explored a decomposition of the anthropometric results along the migration division,\n\nbut we found no important differences.\n\n**Figure 5 Diarrheal incidence among children under 5 by migration status**\n\n**Panel A Nonmigrants** **Panel B Migrants**\n\n24", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "9 These employment rates are very close to the ones from the Polish central bank surveys of Ukrainian refugees, which showed 62% in July 2023 and 68% in July 2024 (NBP, 2024). NBP (2024) age group was slightly different, describing adults as 18 years or older.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "Polish central bank surveys of Ukrainian refugees"}], "vague_data": []}}}
{"input": "only in conjunction with policies for local procurement. Moreover, some of the mining-related\n\npapers have focused on mining in an African context, exploring a range of outcomes, including\n\nHIV-transmission and sexual risk taking (Corno and de Walque 2012; Wilson 2012), women’s\n\nempowerment (Benshaul-Tolonen 2018), infant mortality (Benshaul-Tolonen, 2019) and labor\n\nmarket outcomes (Kotsadam and Tolonen 2016). Mining is also associated with more economic\n\nactivity measured by nightlights (Benshaul-Tolonen, 2019; Mamo et al, 2019).\n\nKotsadam and Tolonen (2016) use DHS data from Africa, and find that mine openings cause\n\nwomen to shift from agriculture to service production and that women become more likely to\n\nwork for cash and year-round as opposed to seasonally. Continuing this analysis, Benshaul\n\nTolonen (2018) explores the links between mining and female empowerment in eight gold\n\nproducing countries in East and West Africa, including Ghana. Women in gold mining\n\ncommunities have more diversified labor markets opportunities, better access to health care,\n\nand are less likely to accept domestic violence. In addition, infant mortality rates decrease with\n\nup to 50% in mining communities, from very high initial levels (Benshaul-Tolonen, 2019). In\n\na study that focuses exclusively on Ghana, Aragón and Rud (2013) explore the link between", "output": {"entities": {"named_data": [{"text": "DHS data from Africa"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Land ownership remains a complex issue in the absence of a codified land law, and the general regime\nof land ownership, encompassing both formal and traditional rights, has not undergone any changes in\nthe past three years. Customary and Islamic laws continue to govern access to and control of land and\nnatural resources in urban and rural areas. While these customary systems vary considerably across the\n\nR E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **R E P U B L I C O F C H A D** 9", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**qualification compared to Polish**\n\n**citizens.** While the proportion of\nindividuals with tertiary education among refugees is slightly higher than among Polish citizens (40% vs 38%), only 12% of refugees work as managers, professionals, and technicians (occupational groups usually requiring higher education) compared to 37% of Poles. Consequently, the wage premium for individuals with tertiary education is much lower among refugees than among Poles (22% vs 84%).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "mining companies in Ghana was 3 percent until 2010, which was the average rate for gold\n\nproduction in Africa (Gajigo, Mutambatsere, and Mdiaya 2012), but increased to 5 percent in\n\n2010 (Standing and Hilson 2013). Of this money, 80 percent goes to the general government\n\nbudget, 10 percent goes to the administration of mining oversight, and 10 percent supports\n\ndistrict administration (Garvin et al. 2009). Between 1993 and 1998, about US$17 million was\n\ndistributed to local mining communities (Aryee 2001). While considered a model of best\n\npractice, there is still a worry that the beneficial effects of allocations to the districts are\n\nundermined by elite capture and corruption at the district level (Standing and Hilson 2013). For\n\nour analysis, the scheme implies that it may be necessary to conduct a district-level analysis in\n\naddition to the more local-level analyses.\n\n12 currently active mines dominate the sector, and there are an additional five suspended mines\n\nthat have been in production in recent decades. Table 1 presents a full list of the mines, the year\n\nthey opened, and their status as of December 2012. Company name and country are for the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland Refugees from Ukraine are not yet utilising their full potential in the Polish labour market. In May 2022, 46% of arriving refugees declared that they had no knowledge of the Polish language (NBP, 2023). Over time, this percentage improved, with data from November 2022 showing a result of 21%, though this still represents a large group of people who do not know the local language [24], placing them at risk of limiting possible jobs to those below their educational level. Nearly 40% of Refugees from Ukraine insured at ZUS on 30th June 2023 in Poland were employed in elementary occupations [25], while for all employed persons in Q2 2023 this percentage was only 5%. Furthermore, the Deloitte Ukraine Refugee Pulse report indicates that 50% of respondents point to language barriers as an obstacle to accessing services to meet basic needs (Deloitte, 2023). Meanwhile, in the MSNA Poland 2023 survey, when asked about encountered barriers for accessing the labour market, 34% of respondents pointed to lack of language knowledge.", "output": {"entities": {"named_data": [{"text": "MSNA Poland 2023 survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "**migrants was challenging to quantify.**\nSince the onset of the armed conflict in eastern Ukraine in 2014, there was a consistent influx of Ukrainians into Poland.\nMany of them sought work as Ukraine’s economy declined and the currency devalued. Most of the migrants came as guest workers, a status brought in by a 2011 law enabling Ukrainians and five other nations to work in Poland for six months Source: Deloitte own elaboration based on Polish Border Guard Headquarter and PESEL data.\n\nPESEL-UKR data Total entries-exits of the Polish-Ukrainian border during a year without a work permit, based on an employer’s declaration. This was a circular migration, with Ukrainians coming to Poland for half of the year, then returning to Ukraine for another six months, and coming back to Poland. The data on employers’ declarations do not reveal the actual number of Ukrainian citizens who followed this system – a single person could hold several declarations, because with every change of employer or promotion at the same employer they had to ask for a new declaration. What is more, with stays shorter than one year,", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "PESEL-UKR data"}], "vague_data": []}}}
{"input": "Increased competition on the labour market could partially offset benefits from refugees. Although (due to a tight labour market) increase in labour force is almost entirely absorbed into working force, there should be slight increase in unemployment rate. Ultimately, it is estimated that it was higher by 0.14-0.25 pp. in 2022 and by 0.18-0.3 pp in 2023 which corresponds to respectively 24-42 thousand and 33-54 thousand additional people being unemployed [45] . In the long run, the unemployment rate should remain higher by 0.15-0.3 pp. Because of that, it is estimated that growth of real wages was slower in 2022 and 2023. It is estimated that due to the influx of refugees, real wages were lower in 2022 by 0.45-0.85% and in 2023 by 0.65-1.15%. Although in effect this is negative, it also means lower inflationary pressure from the labour market in the short term. Long-term real wages should be around 0.55-1.0% lower than in a scenario without refugees.\nThat said, the actual labour market effect is likely to be null as evidenced by econometric studies (Gromadzki and Lewandowski, 2023; Peri, 2014), which are elaborated on in Chapter 4. Gromadzki and Lewandowski (2023) in the early months of 2022 find no effect of Ukrainian refugees on earnings, employment, and unemployment rate of natives and other immigrants, except an actual slight positive impact on the wages of native women.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n# **1.** Inflow of refugees from Ukraine into Poland\n\n##### Even before the 2022 full-scale war in Ukraine the number of Ukrainians in Poland was substantial and growing, although their precise number is difficult to measure.\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Chart 1.** Ukrainian workers with social insurance.\n\nRate of change (right axis) Number (left axis)\n\n**Source:** Deloitte own elaboration based on ZUS data.\n\n1000 750 500 250 0 120% 100% 80% 60% 40% 20% 0%\n\n-20%", "output": {"entities": {"named_data": [{"text": "ZUS data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "**higher productivity.** In a simplistic\nsupply-demand framework, the influx of Ukrainian refugees would have had a negative impact on Polish workers employment or caused a decline in real wages. However, this has not occurred.\nFirst, Polish citizens employment rates have grown, and unemployment rates have fallen. Second, poviats in which the employment share of Ukrainian refugees has grown by 1 pp. saw 0.5 pp. higher employment rates among Polish citizens, and 0.3 pp. lower unemployment rates.\nThird, there is no evidence of lowered wages, in fact the limited available data indicates that a higher share of Ukrainian refugees in a poviat may have caused local wages to rise. Such findings are in line with academic literature, which documents a positive impact of migrants on native workers. With foreigners entering the 04 Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Addressing the remaining issues of**\n\n**refugee integration into the labour**\n\n**market would improve their situation**\n\n**and further benefit the Polish**\n\n**economy.** The key measures to improve\nrefugees' standing include advanced language courses for professionals, easing of occupational licensing, especially requirements based on citizenship, and active labour market policies to help specific groups enter the labour market.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "## **Works cited**\n\n[1] UNHCR, ‘Global Report 2023 - Executive Summary’, UNHCR, Geneva, Jun. 2024. Accessed: Jul. 13, 2024. [Online]. Available:\nhttps://reporting.unhcr.org/global-report-2023-executive-summary\n\n[2] UNHCR, ‘This is our home: stateless minorities and their search for citizenship’, 2017, [Online]. Available:\nhttps://www.unhcr.org/ibelong/wp-content/uploads/UNHCR_EN2_2017IBELONG_Report_ePub.pdf\n\n[3] D. S. Weissbrodt and C. Collins, ‘The Human Rights of Stateless Persons’, _hrq_, vol. 28, no. 1, pp. 245–276, Feb. 2006, doi:\n10.1353/hrq.2006.0013.\n\n[4] E. Abuya, ‘Out of the Shadows: towards ensuring the rights of stateless persons and persons at risk of statelessness in Kenya’, Kenya\nNational Commission on Human Rights (KNCHR) and UNHCR, Nairobi, Jul. 2010. [Online]. Available:\nhttps://www.unhcr.org/media/out-shadows-towards-ensuring-rights-stateless-persons-and-persons-risk-statelessness-kenya\n\n[5] B. Blitz and M. Lynch, ‘Statelessness and the Benefits of Citizenship: A Comparative Study.’, _Statelessness and Citizenship: A Comparative_\n_Study on the Benefits of Nationality_, Jan. 2011.\n\n[6] S. W. Goodman, ‘Citizenship Studies: Policy Causes and Consequences’, _Annu. Rev. Polit. Sci._, vol. 26, no. 1, pp. 135–152, Jun. 2023, doi:\n10.1146/annurev-polisci-051921-102729.\n\n[7] UNHCR, ‘High-Level Segment on Statelessness: Results and Highlights’. Accessed: Oct. 10, 2024. [Online]. Available:\nhttps://www.unhcr.org/ibelong/high-level-segment-on-statelessness-results-and-highlights/", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "REGIONAL BUREAU OF SOUTHERN AFRICA\n\nPROTECTION MONITORING DASHBOARD ON INCIDENTS IN DRC AND MOZAMBIQUE\n\nAs of 30 September 2022\n\nMAP SHOWING THE NUMBER OF REPORTED PROTECTION INCIDENTS PER\n\nProvince in Mozambique\n\n(MOZ) covered by\nprotection monitoring", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland An ageing population coupled with a growing economy causes labour shortages. Despite falling number of available workers, the Polish economy is growing steadily, as it modernises and converges to the level of development of old EU Member States. Despite the Covid-19 pandemic, real GDP growth averaged 3.7% during the last decade. As a result, due to steady demand for labour since 2019, the harmonised unemployment rate in Poland has not exceeded 4%, oscillating around 3% in recent years. According to Eurostat data, in September 2023, harmonized unemployment in Poland reached 2.8%, the same level as Malta. In the entire EU, only the Czech Republic reached a lower level: 2.7%.\nVacancies stood at record heights before", "output": {"entities": {"named_data": [{"text": "Eurostat data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE For households with a member with disability, health was the top priority with 56% of households reporting this as priority need compared to 30% of those without disability. Likewise, 45% of households with chronic illnesses identified healthcare access as their top priority, whereas households without chronically ill members ranked it fourth, with only 22% considering it a priority need. This indicates a modest decrease compared to 2023 when 58% of households with a member with disability and 48% of those with individuals with a chronic illness cited health as their top priority.\n\n### **Need to access** **health care**\n\nRegionally, 31% of individuals experienced health problems 30 days prior to the survey and needed to access health care. The reported experience of health problems was higher among under-fives (37%) and those over the age of 60 (60%), and it was higher among women above 18 years (36%) compared to men (31%). The discrepancies between women and men in terms of experiencing a health problem is particularly pronounced in Estonia, Latvia, and Lithuania, where the rates of experiencing a health problem are 10% higher among women compared to men.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "a 22 percent increase in service sector participation. However, this effect is only statistically\n\nsignificant at the 10 percent level, possibly due to the small sample size within that distance.\n\nThis is in contrast to the dummy for 0-20 km which is insignificant, pointing highly localized\n\neffects on service sector employment for women. Using distance bin of 30 km, we estimate\n\nzero treatment effect on the probability of service sector employment. Panel B of figure 4 shows\n\nthe results for cash-earning opportunities, and similarly, we estimate positive treatment effects\n\nwithin 20 km.\n\nIn panel C of Figure 4, infant mortality is re-estimated using different distance spans. The\n\ndecrease in child mortality decreases almost linearly with the increase in distance bins, an\n\nindication that the effects are only found close to a mine. The largest drop, and the only\n\nsignificantly negative drop, is found for the distance bin 0–20 km.\n\n**Figure 4 Varying the cutoff distance: Service sector employment, cash earnings, and infant**\n\n**mortality**\n\n**Panel A Service and sales** **Panel B Cash earnings            Panel C Infant mortality**\n\n20", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "to factors other than productivity growth, this is unlikely. Any negative impact could only arise if other workers left the labour force or reduced their working hours. No evidence of this is seen in recent Eurostat’s Labour Force Survey data for the Polish economy, where activity rates continued to grow, while the average number of usual weekly hours worked in full- and parttime employment remained fairly stable, particularly for women (who should be closer substitutes for Ukrainian refugees, most of whom are also women; see charts below).\n\nAnalysis of the impact of refugees from Ukraine on the economy of Poland", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "Eurostat’s Labour Force Survey data for the Polish economy"}], "vague_data": []}}}
{"input": "At 44, she arrived in Poland from Kyiv on March 9, 2022, with her 7-year-old daughter, Viktoria, and 5-year-old son, Timur. “I came to the job fair to find a position in my field of expertise. I’m not afraid of physical work, but as the sole provider for my family of three, I need a more stable and better-paying job,” she explains.\n\n© UNHCR/Anna Liminowicz\n\n**2**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "from Ukraine has increased from 61% to 69%, while their unemployment rate has halved from 15% to 8%. Second, median net wage of Ukrainian refugees grew from PLN 3,100 to PLN 4,000, i.e. by 29%. While half of this wage growth came from the overall high earnings growth in the country due to high inflation (gross wages in the general economy grew by 15% [8] ), it was still a major improvement. Gross wage gains appear lower, with ZUS social insurance contributions data for the period from June 30, 2023 and June 30, 2024 showing an increase of 18% (compared to 15% for Polish citizens). As of June 30, 2024, only 44% of ZUS-insured Ukrainian refugees had an employment contract (compared to 82% of Polish citizens). Many may opt for civil law contracts and self-employment to limit their social insurance contributions to the level of minimum wage.\n\n7 Together with refugees working remotely in Ukraine, their income from work would add up to 80% in the SEIS survey.\n\n8 From Q2 2023 to Q2 2024, https://stat.gov.pl/en/latest-statistical-news/communications-and-announcements/list-of-communiques-and-announcements/averagegross-wage-in-the-second-quarter-2024,281,43.html 14", "output": {"entities": {"named_data": [{"text": "SEIS survey"}], "descriptive_data": [{"text": "ZUS social insurance contributions data"}], "vague_data": []}}}
{"input": "Importantly, support with accommodation expenses reduces the calculated poverty rate of refugees from Ukraine to 32% (from 50%) if it is considered to be an indirect source of income [9] . This essentially means that rental aid, in whatever form it is provided, allows over a third of low-income [10] households to de facto live above the poverty line.\nIn Slovakia this effect is the most dramatic – subsidized housing allows an additional 46% of the refugee population to escape poverty.\n\n**DECREASE IN THE REFUGEE POVERTY RATE AS A RESULT**\n\n**OF ACCOMMODATION RENT SUPPORT, %** **[1,2,3]**\n\nNot adoping coping strategies Stress coping Crisis coping Emergency strategies strategies coping strategies Without accommodation rent support\n\n1. The statistic on emergency strategies may have been affected by\nthe survey wording on illegal work\n\n---\n[10] Those that are below the poverty line", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Analysis of the impact of refugees from Ukraine on the economy of Poland** **Analysis of the impact of refugees from Ukraine on the economy of Poland**\n\n# Table of contents\n\nAbstract 04 Non-technical summary 06 Introduction 11\n\n**1.** Inflow of refugees from Ukraine into Poland 12\n\n**2.** Situation of refugees from Ukraine on the labour market in Poland 16\n\n**3.** Economic impact modelling 30\n\n**4.** Unaccounted positive externalities 38\n\nConclusions 41 Appendix. Model Calibration 42 Bibliography 44 This publication has been produced in cooperation with UNHCR, the UN Refugee Agency.The content of this publication is the sole responsibility of Deloitte and may not reflect the views of UNHCR.\n\n02 03", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "22 Deloitte own calculations based on Informacja kwartalna o stanie fnansów publicznych - Ministerstwo Finansów - Portal Gov.pl for respective years. The general government income share in GDP in 2024 was calculated based on the data for Q1–Q3 and based on that total general government income was calculated using forecast for GDP from Wytyczne dotyczące wskaźników makroekonomicznych - Ministerstwo Finansów - Portal Gov.pl.\n\n23 Model treats general government sector as a whole, as such cost and income internal structure may differ creating institutions with financial loses while other may have disproportionate increase of income.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "4. Access to National Public Services\n\nhealth planning documents.\n\nThe 2019 agreement between the UN Refugee Agency (UNHCR) and the Ministry of Health, regarding the\nprogressive integration of camp health centres into the national health system, has facilitated the inclusion\nof all camp health centres in the national system, with the assignment of a healthcare worker to each of\nthese centres, who is included on the Government payroll. The remaining personnel are still supported\nby UNHCR through its partners. This support from UNHCR remains necessary because access to quality\nGovernment led healthcare is still limited due to a shortage of healthcare professionals, medication, health\ninfrastructure, and equipment, as well as high costs.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Certain employment barriers naturally become more pronounced when singling out certain demographics. Some 17% of adults living in households with young children (aged 0 to 11) report lack of childcare as a difficulty with peaks when the youngest child is between 3 and 4. Fifteen percent of those previously employed in the health sector and 14% in the education sector report skills recognition as a barrier.\n\nGenerally, analyzing employment in the host country through the lens of prior work experience offers valuable insights. Estimated unemployment is highest, at 33%, for those who were not employed in Ukraine prior to relocation. Among those who were employed, individuals working in administrative work faced the greatest challenge in transitioning, likely due to elevated local language\n\n**7**\n\nDo not know the local language Lack of decent employment opportunities Lack of employment opportunities for my skills Lack of employment opportunities for my age Lack of childcare services Lack of education/skills recognition Need to take care of others\n\n1. Multiple answers were possible\n\n52% 41% 27% 14% 11% 11% 10%", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "distance. We divide the plane into 10-km distance bins and estimate the model with a full set\n\nof distance bin dummies.\n\n𝑌��� - 𝛽� �� 𝛽�𝑚𝑖𝑛𝑒�� 𝛽�𝑎𝑐𝑡𝑖𝑣𝑒� ∙𝑚𝑖𝑛𝑒� ∝�� 𝑔� �𝜆𝑋� �𝜀���\n\n�𝑚𝑖𝑛𝑒�� 𝛽�𝑎𝑐𝑡𝑖𝑣𝑒� ∙𝑚𝑖𝑛𝑒� ∝�� 𝑔� �𝜆𝑋� �𝜀��� �2�\n\n-\n\nfor d ∈ {0–10, 10–20, …, 80–90}.\n\nThis method, in addition to varying the cutoff point in the baseline estimation strategy, allows\n\nus to identify in more detail the spatial structure of the data. Using this method, we can support\n\nour choice of baseline cutoff distance.\n\nTwo limitations to both individual level analysis are that (i) clusters are not repeatedly sampled,\n\nso cluster fixed effects cannot be included, (ii) the data is not representative below the regional\n\nlevel and no weighting can be undertaken to ensure representability.\n\n**4.2 District-level analysis**\n\nWhile the estimation strategy in (1) captures some spillovers beyond the 20 km, and strategy\n\n(2) maps the economic footprint of the mine up to 100 km, it does not capture district-level\n\n12", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE underscores the need to further explore how combinations of support types contribute to better outcomes and how service accessibility and quality can be optimized across different settings.\n\n**% OF INDIVIDUALS WHO RECEIVED INFORMAL VS FORMAL**\n\n**MENTAL HEALTH AND PSYCHOSOCIAL SUPPORT SERVICES**\n\n**AND REPORT IMPROVEMENT**\n\nYes Slight No No worsening Only formal Only informal Both None Other (N=1,662) 34% 29% 40% 33% 46% 54% 62% 51% 57% 11% 9%", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Table 11 Using GLSS: Employment on extensive and intensive margin and wages**\n\n(6)\nminer\n\n(5)\nservice\nand sales\n\n(4)\nagriculture\n\n(3)\nhours\nworked\nper week\n\n(1)\nworked\nlast year\n\n(2)\nwork 7\ndays\n\nPanel A: Women\n_1. baseline_\n\nactive*mine -0.067* -0.032 3.565 -0.075 0.074 0.025\n(0.040) (0.038) (3.140) (0.064) (0.054) (0.016)\n\n_2. drop 20-40 km_\n\nactive*mine -0.062 -0.039 3.849 -0.076 0.094* 0.026*\n(0.040) (0.039) (3.359) (0.064) (0.057) (0.015)\n\n_3. drop 2 years before_\n\nactive*mine -0.067* -0.031 3.565 -0.087 0.080 0.024\n(0.040) (0.038) (3.140) (0.065) (0.055) (0.016)\n\n_4. mine FE_\n\nactive*mine -0.067 -0.012 8.560* -0.084 0.104 0.025*\n(0.051) (0.048) (5.125) (0.075) (0.065) (0.015)\n\n_5. mine clustering_\n\nactive*mine -0.067* -0.032 3.565 -0.075 0.074 0.025\n(0.032) (0.036) (3.521) (0.081) (0.080) (0.022)\n\nMean dep var. 0.727 0.673 40.39 42.32 0.391 0.005\nPanel B: Men\n_1. baseline_ -0.086** -0.055 3.705 -0.058 -0.032 0.125***\nactive*mine (0.041) (0.039) (3.460) (0.066) (0.036) (0.043)\n\n_2. drop 20-40 km_\n\nactive*mine -0.094** -0.062 3.893 -0.064 -0.031 0.126***\n(0.042) (0.040) (3.842) (0.066) (0.038) (0.042)\n\n_3. drop 2 years before_\n\nactive*mine -0.094** -0.062 3.708 -0.071 -0.026 0.125***\n(0.041) (0.039) (3.459) (0.067) (0.036) (0.043)\n\n_4. mine FE_\n\nactive*mine -0.123** -0.094* 8.233 -0.068 -0.049 0.113**\n(0.057) (0.051) (5.425) (0.075) (0.044) (0.045)\n\n_5. mine clustering_", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**average or gross earnings.** The median\nnet earnings of Ukrainian refugees in Q2 2024 were PLN 4,000 in SEIS, and PLN 3,767 in NBP (2024) surveys. This is 84% and 79% of the national median, respectively. This estimate would be most likely lower, if data allowed us to look at average or gross earnings. First, a comparison of average instead of median earnings would show a larger gap between Ukrainian refugees and all workers in the economy, as the national average is inflated by top incomes, which are less often earned by Ukrainian refugees than", "output": {"entities": {"named_data": [{"text": "SEIS surveys"}, {"text": "NBP (2024) surveys"}], "descriptive_data": [], "vague_data": []}}}
{"input": "1. Host Communities\n\n### **RPRF Policy Dimensions**\n\n(as of 30 June 2023)\n\n### **1. Host Communities**\n\n**1.1** **Support for communities in refugee-hosting areas**\n\nThere has been little change since June 2020 in this domain and no specific national fiscal or budget policy\nis yet in place to provide additional financial transfers to areas most affected by the presence of refugees.\nFinancial contributions for these areas still rely on projects and programs funded by external donors.\n\nThe government’s priorities remain focused on: (i) Defence and security, peace, social cohesion and national\nreconciliation; (ii) Good governance and the rule of Law; and (iii) Return to constitutional order. In practice,\nregarding transfers from central to local level, the Government of Chad continues to allocate twenty\npercent of its budget to security, excluding other social sectors, amid ongoing challenges from conflicts in\nneighboring countries, and economic and climatic crises.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Refugees access Indonesia through the air and sea. Many refugees in Indonesia, particularly Rohingya\ntraveling by boats, are facilitated in their travel and arrive in the country with the assistance of agents.\nIn previous years, many Rohingya who arrived in Indonesia by sea – approximately 80% - departed\nsoon after arrival to Malaysia, where a large Rohingya community resides and more robust\nemployment opportunities, albeit informal opportunities, exist. UNHCR is extremely concerned about\ncredible reports that refugees in Indonesia – particularly Rohingya in Aceh and North Sumatra – are\nbeing victimized by traffickers during their journey to Indonesia or during onward movement after\narrival in the country.  Refugees have reported numerous protection incidents that took place during\ntheir movement to, through, and from Indonesia, including gender-based violence, physical abuse,\nexploitation, harassment, intimidation, forced movement, and extortion. UNHCR monitors the\nmovement of refugees to assess trends and identify protection risks, to engage with Indonesian\nauthorities to respond to reports of trafficking, and to counsel on the risks of onward movement.\n\n### **Ensuring Protection with Resource Limitations**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Preparedness \r activities \r will \r continue \r and \r will \r be \r strengthened, \r including \r assistance \r to\nspontaneous \r return. \r As \r patterns \r of \r spontaneous \r returns \r to \r specific \r locations \r emerge, \r in\nparticular \r with \r the \r return \r of \r entire \r households, \r UNHCR \r will \r enhance \r its \r assistance \r to\nreturnees \r and \r their \r communities \r though \r an \r integrated \r multi-­‐sector \r package \r of\ninterventions \r with \r the \r aim \r of \r building \r confidence \r without \r creating \r an \r artificial \r ‘pull’\nfactor. \r UNHCR \r will \r aim \r to \r play \r a \r leading \r role \r in \r bringing \r partners \r together \r to \r address\nthe \r identified \r needs, \r in \r the \r area \r of \r legal, \r physical \r and \r material \r safety, \r collectively \r and \r in\nan \r integrated \r manner.\n\n**10.3.** **Phase \r 3: \r Refugee \r repatriation \r and \r initial \r reintegration \r operations**\n\nPrevious \r phases \r activities \r will \r be \r further \r strengthened \r and \r operationalized \r with \r a\nfocus \r on \r providing \r immediate \r relief \r assistance \r to \r newly \r returned \r refugees \r while\nenhancing \r early \r recovery \r and \r development \r partnerships. \r Activities \r specific \r to \r this\nphase \r will \r include:\n\n- Provision \r of \r immediate \r relief \r assistance \r such \r as \r food, \r non-­‐food \r items \r and\nshelter \r in \r accordance \r with \r international \r standards \r and \r any \r nationally \r agreed\nhumanitarian \r standards. \r Particular \r support \r will \r be \r provided \r to \r the \r most\nvulnerable \r previously \r identified \r through \r a \r referral \r mechanism \r with \r the \r country\nof \r asylum.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "we use a cutoff distance of 20 km, we assume there is little economic footprint beyond that\n\ndistance. Of course, any such distance is arbitrarily chosen, which is why we try different\n\nspecifications to explore the spatial heterogeneity by varying this distance (using 10 km, 20 km,\n\nthrough 50 km) as well as a spatial lag structure (using 0 to 10 km, 10 to 20 km, through 40 to\n\n50 km distance bins). [4]\n\nSecond, we collapse the DHS mining data at the district level. [5] The number of districts has\n\nchanged over time in Ghana, because districts with high population growth have been split into\n\nsmaller districts. To avoid endogeneity concerns, we use the baseline number of districts that\n\nexisted at the start of our analysis period, which are 137. Eleven of these districts have industrial\n\nmining. Because some mines are close to district boundaries, we additionally test whether there\n\nis an effect in neighboring districts.\n\n**3.1 Resource data**\n\nThe Raw Materials Data are from InterraRMG (2013). The data set contains information on\n\npast or current industrial mines. All mines have information on annual production volumes,\n\nownership structure, and GPS coordinates on location. We complete this data with exact\n\n---\n[4] The distances are radii from mine center point, and form concentric circles around the mine.\n[5] The DHS and the GLSS data are representative at the regional level, and not at the district level. Since the", "output": {"entities": {"named_data": [{"text": "Raw Materials Data"}, {"text": "DHS mining data"}], "descriptive_data": [], "vague_data": [{"text": "GLSS data"}]}}}
{"input": "work. This indicates, possibly, that the economy becomes more reliant on cash as a mine starts\n\nproducing. It is possible that the difference from the main results presented in table 4 indicates\n\nthat agricultural workers are overrepresented among the bottom 40 percent in mining\n\ncommunities. However, given the issues associated with doing this analysis with repeated cross\n\nsection, we should be cautious in interpreting these results.\n\n**6.5 Heterogeneous results, sensitivity and intensity of mining**\n\nIn panel B (urban) of table A3 (Annex), we interact our treatment variables ( _active*mine_, _mine_,\n\n_active_ ) with an indicator variable for whether the locality is urban. This allows us to pick up\n\npotential differential effects across urban compared to rural localities. None of the treatment\n\neffects are statistically significantly different between rural and urban areas. [16] In panel C, we\n\nhave constructed a new treatment variable _#active*mines_ that counts the number of actively\n\nproducing mines within 20 km. Women are sampled within 20 km of one mine (593 women),\n\nwithin 20 km of two mines (137 women), and within 20 km of three mines (64 women). The\n\n---\n[16] Few of the other interaction coefficients are also statistically significant. The interaction between _urban*mine_", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "18-59 female and male 60+ female and male two 18-59 or 60+ females other households 18-59 female with one or more 60+ individuals two 18-59 females 18-59 female and male other households 0.3% 7.4%\n\n**10. Katowice** 11,591\n\nNote that poviat-level population does not include Ukrainian refugees, who were added to calculate their appropriate shares.\n\nSource: Deloitte own elaboration based on the PESEL database as of September 2024 and GUS population data as of mid-2024.\n\n#### **1.3 Households income sources**\n\nNote: Some groups that constituted less than 2% of households have been omitted.\n\nSource: Deloitte own elaboration based on SEIS (May-June 2024) UNHCR (2024) survey.\n\n**The majority of refugees settled in**\n\n**major cities, especially Warsaw and**\n\n**Wroclaw, and their vicinities.** Eight most\npopulous poviats in Poland [5] comprising 16% of the host population, are also the top eight poviats in terms of the number of Ukrainian refugees, 29% of whom reside there. This shows that Ukrainian refugees are more concentrated in the largest cities than the host population, as they migrated to the most attractive\n\n---\n[5] Seven cities and Poznański poviat.", "output": {"entities": {"named_data": [{"text": "PESEL database"}, {"text": "GUS population data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "geographic location data from MineAtlas (2013), where satellite imagery shows the actual mine\n\nboundaries, which allows us to identify and update the center point of each mine. The\n\nproduction data and ownership information are double-checked against the companies’ annual\n\nreports.\n\nFor Ghana, this exercise results in 17 industrial mines tracked over time. We have annual\n\nproduction levels from 1990 until 2012. As mentioned, Table 1 shows the mining companies\n\nactive in Ghana during recent decades, with opening and closing years (although some were\n\nclosed in between, and are not presented in the table). Figure 2 shows the geographic\n\ndistribution of these mines.\n\n**Figure 2 Gold mines and DHS clusters in Ghana**\n\n**Panel A Gold mines and 20 km buffer zones Panel B Gold mines, DHS clusters, and 100 km buffer zones**", "output": {"entities": {"named_data": [{"text": "MineAtlas (2013)"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n#### **Productivity shock rationale**\n\nAs Ukrainian refugees entered the labour market, the economy adapted in line with expectations based on scientific literature, resulting in greater specialisation and higher productivity. In a simplistic supply-demand framework akin to the “canonical model”, the influx of Ukrainian refugees should have caused some Polish workers to become unemployed or leave the labour force, or real wages to fall.\nEven in the Deloitte D.Climate model, Ukrainian refugees add 0.4 percentage points to the unemployment rate and lower real wages by 1.35% in 2024 when it is not counterbalanced by an additional positive productivity shock. However, this is not what we observe in empirical data. First, Polish citizens employment", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Ukrainian refugees who were outside the labour force before**\n\n**coming to Poland.** We have demonstrated that Ukrainian refugees\nwho managed the household or engaged in other non-workrelated tasks before arriving in Poland, are much more likely to be unemployed. ALMPs could be targeted at supporting this group and increasing its employment opportunities.\n\nincrease corresponds to wage increase, this intervention would add PLN 2.5 billion in value to the economy. This should be considered a lower-bound estimate, as it understates potential benefits. In part, the higher productivity of workers may boost employer profits, further enhanced by increased investment. As far as improved language skills are concerned, we do not anticipate a significant negative impact on wages due to increased competition.\nEnhancing language fluency is one way to address occupational downgrading. To avoid double counting, we estimated that around PLN 1 billion has been already included in the previously estimated gains from reduced downgrading.\n\n**A further increase in labour**\n\n**participation of refugees would**\n\n**yield significant macroeconomic**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "and might understate their presence.\nThe only hard data on these flows is the number of Ukrainian workers with social insurance, which nevertheless understates the numbers, as certain kinds of legal work often undertaken by temporary employees did not require it, and some Ukrainians worked in the shadow economy.\nThe number of workers with Ukrainian citizenship and social insurance increased from just 33 thousand at the end of 2013, to 500 thousand on 30th September 2019, and 627 thousand at the end of 2021. Some of this increase reflects the transitioning of Ukrainians to more regular work arrangements and securing of work permits. The yearly rate of the number of registrations peaked at 106% at the end of 2015, and even with the recent refugee inflow never reached such a high pace again. The most recent data from 30th September 2023 counts 753 thousand workers with Ukrainian citizenship registered for social security, including 225 thousand refugees.\n\n**Source:** Deloitte own elaboration based on ZUS data. Quarter 3 2023 shows the most recent\ndata available.\n\n13", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "country before the full-scale war began.\nThe document primarily includes residency rights and housing access, labour market access, social welfare and medical assistance, as well as access to education and legal guardianship for unaccompanied children and teenagers. Additionally, Ukrainian nationals that become admitted to EU territory are free to move across it for 90 days and are able to choose any EU country where they will make use of the temporary protection. The directive was initially introduced for one year – until 4th March 2023, however in September 2023 it was extended for a second time to remain active until 4th March 2025.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Power BI Desktop Government Leadership Ensuring a whole of governmental approach with oversight and involvement is crucial for successfully identifying and implementing solutions. Effective leadership and coordination at the national and local levels are necessary to ensure systematic inclusion of displacement-affected communities (DACs) across government priorities and planning processes, as well as successfully implementing durable solutions programs.\nPathway #1:", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Systematic \r engagement \r with \r key \r actors \r facilitating \r and \r supporting \r the \r peace \r process,\nsuch \r as \r MPC, \r is \r also \r required. \r This \r will \r ensure \r that \r issues \r affecting \r the \r rights \r and\nwelfare \r of \r IDPs \r and \r returning \r refugees \r are \r appropriately \r addressed \r in \r peace\nnegotiations \r and \r peace-­‐building \r programmes \r and \r initiatives \r such \r as \r the \r MPC-­‐led \r Joint\nPeace-­‐building \r Need \r Assessment \r (JPNA), \r and \r that \r displaced \r populations, \r including\nwomen, \r have \r the \r opportunity \r to \r participate \r in \r these \r processes.\n\nEfforts \r will \r also \r be \r required \r to \r ensure \r that \r durable \r solutions \r are \r mainstreamed \r in \r the\nimplementation \r of \r the \r UN \r Strategic \r Framework \r for \r Myanmar \r for \r 2013 \r to \r 2015, \r and\nnational \r development \r plans \r and \r programmes \r as \r means \r of \r catalysing \r interventions \r by\ndevelopment \r agencies. \r Relevant \r funding \r opportunities, \r such \r as \r the \r Peace \r Building \r Fund\n(PBF), \r should \r also \r be \r pursued.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Gender analyses revealed that 90% of women and 84% of men reported improvement. Respondents reported that, among children under 18, 85% demonstrated some form of improvement, 13% no improvement, and 2% worsening. Outcomes for children varied by age and gender, with 98% of adolescent girls (12-17 years) showing improvement compared to 78% of boys in the same age group, while among younger children (5-11 years), 83% of girls and 77% of boys showed improvement. Among adults, positive outcomes were relatively consistent 5-11 12-17 18-34 35-59 60+ years old (N=1,661)", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Poverty is associated with tangibly inferior living conditions, worse healthcare coverage,**\n\n**more frequently children being out of school, and having to skip meals**\n\nRefugee households with members living in poverty were found to more often not report feeling safe when walking alone in their neighborhood after dark (18% vs 10% for those not at risk), to significantly more frequently live in collective housing (27% vs 8%), and to feel under pressure to leave their accommodation (29% vs 11%).\n\nSimilarly, those with an income below the poverty line were substantially more likely to report lacking separate showers or toilets, having insufficient privacy, being unable to cook or store food in their dwelling.\n\nTwenty percent of respondents in the poverty group said they were unable to access needed medical services over the last 30 days and roughly the same percentage said they were forced to reduce essential health expenditures (including buying drugs) because of lack of funds. Almost half of those missing out on medical support cited unaffordable fees at their clinic or hospital as one of the main reasons.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_Note:_ Figure 4 shows the main treatment coefficients using the baseline estimation strategy (with DHS individuallevel data; see table 4 for more information), but with different distance cutoffs (10 km, 20 km, 30 km, 40 km, and\n50 km). *** p<0.01, **p<0.05, *p<0.1.\n\nThe results above suggest substantial heterogeneity in outcomes and highlights the importance\n\nto explore spatial heterogeneity in the results. In the following sections we explore plausible\n\nexplanations for these outcomes.\n\n**5.4 Difference-in-differences at the district level**\n\nThe results for female employment in the district-level analysis are shown in table 6.\n\nAgricultural work decreases for women in mining districts and manual work increases.\n\nFollowing from this, the likelihood that a woman is working year-round increases. [11] This is\n\nsimilar to what we saw in the individual-level regressions, but the results are now statistically\n\nsignificant.\n\n**Table 6 Effects of mine opening at the district level on female employment**\n\n(1) (2) (3) (4) (5) (6) (7)\n\nnot agri- service profess- manual earns works\n\nworking culture or sales ional work cash all year\n\nActive district 0.019 -0.085** 0.034 -0.018** 0.050** -0.021 0.054*\n(0.027) (0.042) (0.030) (0.008) (0.020) (0.049) (0.032)\n\n---\n[11] Working year-round is derived from a question if the woman works occasionally, all year or seasonally.", "output": {"entities": {"named_data": [{"text": "DHS individuallevel data"}], "descriptive_data": [{"text": "DHS individual-level data"}], "vague_data": [{"text": "DHS individual level data"}]}}}
{"input": "In the model, shocks were calibrated using data for 2022-2024. In the case of 2022, we adjusted the data to reflect refugee arrivals after February, fixing their share at roughly 2.6 percent of the population per PESEL registry figures. We then calibrated refugee employment to match the NBP’s 2022 survey (NBP, 2024), the UNHCR’s 2023 MSNA, and the 2024 SEIS survey - implying their employment share rose from 1.5 percent to 2.4 percent of total employment in Poland. To keep the regional labour supply balance, equivalent offsets were applied in the broader Eastern Europe aggregate. [35] Furthermore, it was assumed that refugees have higher spending needs and thus a lower saving rate than other earners in Poland for 2022 and 2023. Moreover, according to National Bank of Ukraine data, the consumption of Ukrainian refugees has been partially financed by savings in Ukrainian banks in 2022 and 2023, which was modelled as them having a negative saving rate, while being offset by lowering investment levels in Eastern Europe. [36] By 2024, it was assumed that their situation on the labour market had stabilised and that there had been no further changes in their savings.\n\n---\n[35] Aggregate region in the D.Climate model, that consists of Ukraine, Russia, Belarus, Moldova, Czechia, Slovakia, Hungary, Romania, and Bulgaria.\n[36] In other words, it was assumed that money that would be spent e.g. through credit action for investments in Eastern Europe were spent for consumption in Poland.", "output": {"entities": {"named_data": [{"text": "NBP’s 2022 survey"}, {"text": "2024 SEIS survey"}, {"text": "UNHCR’s 2023 MSNA"}], "descriptive_data": [{"text": "PESEL registry figures"}, {"text": "National Bank of Ukraine data"}], "vague_data": []}}}
{"input": "First, the employment rate of Polish citizens has been growing since the Ukrainian refugee influx, while the unemployment rate has been falling. This is particularly evident among women, who make up the majority of refugees. The employment rate for women aged 20-64 has grown consistently from 68.2% in Q2 2021 to 70.2% in Q2 2022, 71.7% in Q2 2023, and 72.2% in Q2 2024 (see Chart 26). The unemployment rate for women aged 20-64 has consistently fallen, from 3.5% in Q2 2021 to 3.0% in Q2 2022, 2.6% in both Q2 2023 and Q2 2024.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "unallocated), the gap in social contributions bases towards Polish citizens narrows.\nThe largest group (16%) is positioned between 90% and 100% of Polish citizens (median 93%). This is an improvement over two years, when the majority (13%) situated between only 80% and 90% (median 82%). [12]\n\n---\n[12] Unfortunately, the data is available in a format that is not suitable for econometric modelling and thus these are only comparisons between thousands of employee", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "In Brazil, refugees can choose between accessing the asylum system or applying for a residency\nas a complementary form of protection. Both options ensure freedom of movement, access to\nformal employment, education, healthcare, and social assistance. However, only those who apply\nfor asylum are explicitly safeguarded against refoulement, eligible to obtain travel documents,\ngranted expedite access to naturalization, and exempt from presenting documents from their\ncountry of origin in various civil procedures. These additional safeguards significantly ease their\nintegration into Brazilian society.\n\nDespite an overall favorable environment, the proportion of those living below the national\npoverty line is still considerable, especially if compared with host communities (40% vs 30%). [1]\nResearch conducted by UNHCR and other institutions indicates that refugees in Brazil experience\n\n_1_ _[https://unstats.un.org/sdgs/metadata/?Text=&Goal=10&Target=10.7](https://unstats.un.org/sdgs/metadata/?Text=&Goal=10&Target=10.7)_\n\nUNHCR / October, 2024 2", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "It is also important to highlight that there were slight differences in the questionnaire across countries. Not all questions were consistently included in all country-level surveys, and some answer options were individually adjusted.\n\nLastly, the survey was conducted during the summer months, coinciding with both host country and Ukraine school holidays. This period often sees many households temporarily visiting Ukraine, which impacted the accessibility of households and posed challenges in meeting targets, particularly in certain countries and geographic locations.\n\n**15**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "country-level surveys"}]}}}
{"input": "rates have grown, and unemployment rates have fallen. Second, poviats in which the employment share of Ukrainian refugees has grown by 1 percentage point, experienced higher by 0.5 percentage point Polish citizens employment rates, and 0.3 percentage point lower unemployment rates. Third, there is no evidence of lowered wages; in fact, the limited available data suggests that Ukrainian refugees may have caused higher wage growth in poviats to which they have moved. These are common findings in the scientific literature quoted in the previous section, that as immigrants enter the labour market, native workers tend to specialise in higher-value, complementary tasks.\nThis is evident in Polish workers moving to more attractive occupational groups. This constitutes a positive productivity shock, counterbalancing labour market pressures.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Regional protection monitoring harmonization outcomes\n\nIn line with the outcomes of the Regional IDP Stocktaking held on 25 February 2022, the Regional Bureau for\nSouthern Africa undertook an ambitious project to harmonize the protection monitoring activities conducted in the\nregion. The envisioned regional harmonization aims to enable an environment that increases persons we serve\nempowerment, inclusion, and protection while strengthening accountability and efficiency in humanitarian and\ndevelopment programs. The regional protection monitoring harmonization focuses to:\n\n§ **Set common definitions of the incident, minimum standards, and objectives of the protection**\n\n**monitoring.**\n§ **Standardize questionnaires to collect data but be flexible enough for field operations to add and amend**\n\n**questions depending on the context and needs.**\n§ **Develop reporting/product templates with a standard design and branding for UNHCR.**\n§ **Develop a narrative to explain externally why and how UNHCR does protection monitoring and identify**\n\n**common indicators for regional reporting.**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Source: Deloitte own elaboration based on SEIS survey, NBP (2024) survey. Monthly GUS median wage in the general economy has been recalculated to reflect the specific time periods of SEIS UNHCR and NBP (2024) surveys.\n\nSource: Deloitte own elaboration based on Eurostat Labour Force Survey data SEIS UNHCR survey conducted in May and June 2024. For Polish citizens reference period is Q2 2024.\n\nPolish citizens Ukrainian refugees\n\n**The wages of Ukrainian refugees are**\n\n**higher for men than women, but the**\n\n**gap is not wider than in the economy**\n\n**as a whole.** The median net wage of\nfemale Ukrainian refugees is 6% lower than in the male group (compared to 7% in the economy as a whole), however, the gap may be different due to the fact that there are fewer men in the Ukrainian refugee population.\n\n13 Children in Ukraine start school at 6 years of age, while in Poland at 7. School system lasts for 11 years in Ukraine and 12 years in Poland. After recent reform, Ukrainian children who started school in or after 2018 will receive 12 years of schooling.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE problems, and in each age group females reporting more problems than males, except among children under the age of 11, where boys reported slightly more problems than girls.\n\nThese overall upward trends underscore that, even in the third year of the Ukraine response, mental health and psychosocial needs remain a significant and growing challenge requiring sustained support, attention, and increased financing to ensure adequate care and resources are available.\n\n**% OF INDIVIDUALS WITH MENTAL HEALTH OR**\n\n**PSYCHOSOCIAL PROBLEMS BY AGE GROUP AND GENDER**\n\nFemale Male\n\n**% OF INDIVIDUALS WHO REPORT EXPERIENCING MENTAL**\n\n**HEALTH AND PSYCHOSOCIAL PROBLEMS AND TRIED TO**\n\n**ACCESS SUPPORT BY COUNTRY**\n\n46% 58% 57% 51% 50% 48% 45% 43% 35% 34% 32% Regional Hungary Latvia Lithuania Poland Czechia Estonia Bulgaria Moldova Romania Slovakia 5-11 12-17 18-34 35-59 60+ years old (N=17,972)\n\n### **Access to Mental** **Health and** **Psychosocial** **Support**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "The districts are small, and some mines are located in border regions. We thus expect there to\n\nbe spillovers across district borders. For example, a mine can change demand for labor,\n\nagricultural produce, and services across the district border, and induce reallocation of work\n\nacross districts. We explore neighbor spillovers by estimating the following equation:\n\n𝑌���  - 𝛽�𝑔𝑜𝑙𝑑_𝑝𝑟𝑜𝑑��  - 𝛽�𝑛𝑒𝑖𝑔ℎ𝑏𝑜𝑟_𝑔𝑜𝑙𝑑_𝑝𝑟𝑜𝑑��  - ∝�� 𝑔� �𝜆𝑋�� �𝜀���      �5�\n\nThat is, we add gold production for the mining districts to their neighbors, and _β2_ measures the\n\neffects of gold production in these districts, as well. That is, if _β2_ is statistically and\n\neconomically significant, it would imply that increased production in a neighboring district has\n\nspillover effects on the district in question.\n\nIn Annex table 4, we have added the gold production of the mining areas to their neighbors and\n\nwe estimate the spillover effects of mining production in a district on employment in adjacent\n\ndistricts. As before, panel A shows effects of increasing production in the previous period, and\n\n34", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "24 Due to possible differences in methodologies data from this surveys should not be directly compared 25 Elementary occupations include: Cleaners and helpers; Agricultural, forestry and fishery labourers; Labourers in mining, construction, manufacturing and transport; Food preparation assistants; Street and related sales and services workers; Refuse workers and other elementary workers.\n\n22 23", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Refugee receiving and hosting countries have shown generosity and kept borders open while adapting to a protracted stay of the refugees as the situation in Ukraine remains volatile and prospects for refugees returning home remain grim. Under the Temporary Protection Directive or other protection mechanisms implemented in most countries, refugees have access to health care benefits, but certain groups may be left out according to country-specific practices – for example, those who do not apply for temporary protection and those who temporarily return to Ukraine or move from one location to another and are deregistered [5] .\n\nHealth systems in refugee-receiving countries have made substantial efforts to meet the needs of Ukrainian refugees. However, challenges in host country health systems, such as health workforce shortages, long waiting lists, and language barriers affect access to care and may discourage healthseeking among refugees. Refugees’ movement within and out of countries present challenges for local health providers to register and provide required services. At the same time, there are", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "_5_ For the purpose of this analysis, the category that refers to “basic and essential services” regards denial of, or unequal access to basic\nservices, the category “family life” is linked to family separation or inability to exercise family unit, and “life incidents” are linked to\nenforced disappearance.\n_6_ [ACNUR (2023), Diagnosticos Participativos, https://www.acnur.org/portugues/wp-content/uploads/2023/12/Diagnosticos-](https://www.acnur.org/portugues/wp-content/uploads/2023/12/Diagnosticos-Participativos-2023-.pdf)\n[Participativos-2023-.pdf](https://www.acnur.org/portugues/wp-content/uploads/2023/12/Diagnosticos-Participativos-2023-.pdf) pp. 7; 9.\n_7_ Idem, p. 13\n_8_ [Cáritas-REACH (2022), Avaliação Baseada em Área (ABA) em Boa Vista, Roraima, https://caritas.org.br/storage/arquivo-de-](https://caritas.org.br/storage/arquivo-de-biblioteca/March2023/Ir3dz5ULhRAzNV4wqkwi.pdf)\n[biblioteca/March2023/Ir3dz5ULhRAzNV4wqkwi.pdf, p.14](https://caritas.org.br/storage/arquivo-de-biblioteca/March2023/Ir3dz5ULhRAzNV4wqkwi.pdf)\n_9_ [R4V (2024), Microsoft Power BI](https://app.powerbi.com/view?r=eyJrIjoiMWJhN2UzOWMtZWFlZC00MzZiLWI0OWQtNGZlMDIzN2Y3Zjg5IiwidCI6ImU1YzM3OTgxLTY2NjQtNDEzNC04YTBjLTY1NDNkMmFmODBiZSIsImMiOjh9&pageName=f271143c36cbd9a6b0ee)\n\n_10_ Idem.\n\nUNHCR / October, 2024 4", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**the younger age groups.** Ukrainian\nrefugee incomes from employment are highest in the 25–34 and 35–44 age groups. However, relative to the economy as a whole, the wages of Ukrainian refugees are the highest in the youngest age groups and decrease with age. This can be explained by three facts. First, wages in the youngest age groups are most compressed, because they diverge with time and accumulated professional experience. Second, younger persons have less experience and so lose least from migration. Third, younger persons often find it easier to learn the language of the host country.\n\n**The earnings of Ukrainian refugees**\n\n**differ across sectors in nominal**\n\n**terms and as a percentage of the**\n\n**economy as a whole – only education**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "8 A household is defined to fall below the poverty line if its members fall below the poverty line on individual basis (the equivalized income of all household members is the same) 9 Its magnitude can be computed as the difference between the median equivalized market rent in the region and the actual equivalized accommodation expense", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "12,294 individuals, of which 7,491 men live within 100 km of a mine. In addition, the DHS\n\ndata collect records of all children born within the five years prior to the surveying. Of the\n\n12,174 children born to the surveyed women within the last five years, 6,888 were born to\n\nwomen currently residing within 100 km of a mine. See Appendix table 1 for definition of\n\noutcome variables.\n\nWe complement the analysis with household data from the GLSS collected in the years—1998–\n\n99, 2004–05, and 2012–13. These data are a good complement to the DHS data, because they", "output": {"entities": {"named_data": [{"text": "household data from the GLSS"}, {"text": "DHS data"}, {"text": "DHS\n\ndata"}], "descriptive_data": [{"text": "household data from the GLSS"}], "vague_data": []}}}
{"input": "Furthermore, the Ministry of Education continues to collect data on refugee and asylum-seekers students for the\neducation management information system. The same applies with the Ministry of Health; data on refugee and\nasylum-seekers are included in the national health information system. The government is working on releasing\nbreakdowns of pupils by legal status (nationals and refugees). Additionally, the Government continues to work\nto include refugees in the national civil registry database. However, the technical and financial prerequisites\nfor this are not yet in place. Furthermore, UNHCR has long been advocating for refugees and asylum-seekers\nto be included in the future national population and household census, and there is now apparent agreement\nfrom the government on this principle.", "output": {"entities": {"named_data": [], "descriptive_data": [{"text": "national population and household census"}, {"text": "national civil registry database"}], "vague_data": [{"text": "education management information system"}, {"text": "national health information system"}, {"text": "national civil registry database"}]}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n**ACCOMMODATION QUALITY BY POVERTY GROUP**\n\nIncome above the poverty line Income below the poverty line\n\n**LIVING CONDITIONS BY POVERTY GROUP**\n\nIncome above the poverty line Income below the poverty line Living in collective housing Not reporting feeling safe walking in neighbourhood after dark Unable to store or cook food Insufficient Lacking privacy separate showers or toilets Feeling under pressure to leave accommodation Source: Survey data, SAG estimates\n\n**POVERTY EFFECTS ON HEALTHCARE ACCESS**\n\nIncome above the poverty line Income below the poverty line Source: Survey data, SAG estimates\n\n**FOOD COPING STRATEGY OVER LAST 7 DAYS BY POVERTY**\n\n**GROUP**\n\nIncome above the poverty line Income below the poverty line Had to reduce essential health expenditures in last 30 days (including drugs) Unable to obtain needed healthcare in the last 30 days Could not afford hospital or clinic fee in last 30 days Had to borrow money for food Note: Percentages of those that could not afford clinic fees are as share of those not able to access healthcare in the last 30 days Source: Survey data, SAG estimates", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": [{"text": "Survey data"}]}}}
{"input": "**Potential macroeconomic benefits**\n\n**from the further integration of**\n\n**refugees into the labour market**\n\n**are considerable.** Addressing even\nhalf of the existing gaps can generate significant macroeconomic gains of at least PLN 6 billion value added annually.\nSuch an increase in GDP would contribute more than PLN 2.5 billion to public sector revenue through taxes and social security contributions. These estimates are conservative, as they consider only the direct gains for workers. As the economy adjusts to a more skilled workforce, additional growth would result from increased company investments necessary to meet needs of more advanced workforce. While increased competition might reduce overall gains, deeper specialization can mitigate such effects, as suggested by the experience with refugee integration into the labour market.\n\n05\n\n**•** **Widespread occupational licensing**\n\n**is an obstacle to efficient use of**\n\n**refugees' human capital.** Only 3.6% of\nUkrainian refugees insured at ZUS work in regulated professions compared to 10.6% of Polish citizens. Many barriers on entry to a profession apply to foreign citizenship rather than skill or exam requirements. This is relevant in education, medical professions, and even fire service.\n\n**•** **Lack of fluent Polish negatively**\n\n**affects the labour situation of**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Observations 19,226 19,226 19,226 19,226 19,226 19,270 15,991\nR-squared 0.207 0.327 0.128 0.137 0.037 0.213 0.278\n\n_Note:_ Robust standard errors clustered at the district level in parentheses. All regressions control for year and\ndistrict fixed effects, urban dummy, age, and years of education. Active is active status of mine in the survey year.\n\n*** p<0.01, **p<0.05, *p<0.1.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland Importantly, most of the income of Ukrainian nationals living in Poland, both refugees and pre-2022 migrants, comes from their work. Our calculations based on the UNHCR MSNA Poland 2023 survey results show that 80% of refugee income comes from employment, with other sources on average playing a much lesser role. The income brackets presented in the survey show that 20% of households earn less than 3000 PLN, 41% earn between 3,000 and 6,000 PLN and 12% earn more than 6,000 PLN, while 27% of respondents preferred not to answer. Meanwhile, in the NBP (2023) survey conducted in November 2022 the net income of refugees oscillated between 2,000 and 3,000 PLN, while the net income of pre-2022 migrants was closer to between 3,000 and 4,000 PLN.\nIn the case of Ukrainians that were out of work, the monthly income was more varied, especially because there were fewer previous migrants in this situation.\nThe median income for non-employed prewar immigrants was around 2,500 PLN [32] .\nAmong refugees from Ukraine remaining out of work at the time of the survey, the median income equaled around 600 PLN.", "output": {"entities": {"named_data": [{"text": "UNHCR MSNA Poland 2023 survey"}, {"text": "NBP (2023) survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n**UKRAINE REFUGEE VS HOST GROSS MONTHLY WAGES, EUR/MONTH**\n\nMinimum wage (2024) Refugee mean wage (2023) Refugee mean wage (2024) Host mean wage (2024) 2,500 2,000 1,500 1,000 500 0 Bulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia Region Note: Mean wages have been estimated by dividing household employment income by the total number of working hours and then computing a weighted average across households with weights proportional to total working hours. As the survey asked for net income, weighted means were then converted to gross amounts for comparability based on host country tax rates.\n\nSource: Survey data, Eurostat, SAG estimates Similar to its impact on employment status, education seems to have a much less pronounced effect on wage premiums for refugees compared to hosts, also suggesting the presence of underemployment. While, according to Eurostat data and SAG estimates, a local with an advanced degree can expect to earn nearly 80% more than someone with only lower secondary education [18], the same wage gap [19] for Ukrainians stands as just 16% based on survey data.", "output": {"entities": {"named_data": [{"text": "Eurostat data"}], "descriptive_data": [], "vague_data": [{"text": "survey data"}]}}}
{"input": "We find that refugees from Ukraine who remain in Poland as workers, entrepreneurs, consumers, and taxpayers have a positive impact on economic output, which will increase in the long run. Results of our general equilibrium Deloitte D.Climate model show that refugees from Ukraine contributed 0.7-1.1% to the Gross Domestic Product in 2023. In the long-term this effect will grow to 0.9-1.35%. In our model, the long-term is defined as the period over which the economy fully adjusts to the shock of the initial refugee inflow; it does not include other aspects, e.g. refugee children growing-up and entering employment.\nThese results are consistent with previous, similar studies. However, they should be treated as lower-bound estimates, as we do not allow for the possibility of an increase in the labour force triggering a positive productivity shock (e.g., due to increased specialisation), because there is little data to credibly estimate its size.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "NAVIGATING HEALTH AND WELL-BEING CHALLENGES FOR REFUGEES FROM UKRAINE\n\n**% OF INDIVIDUALS WHO ACCESSED FORMAL AND**\n\n**INFORMAL SUPPORT BY COUNTRY**\n\nOnly formal Only informal Both None Other\n\n**% OF INDIVIDUALS WHO ACCESSED FORMAL AND**\n\n**INFORMAL SUPPORT BY AGE AND GENDER**\n\n**GENDER = FEMALE**\n\nOnly formal Only informal Both None Other Regional Bulgaria Czechia Estonia Hungary Latvia Lithuania Moldova Poland Romania Slovakia (N=1,716) 56% 34% 47% 37% 29% 33% 49% 59% 64% 44% 59% 14% 31% 23% 24% 28% 17% 17% 43% 58% 61% 52% 71% 34% 32% 38% 25% 26% 15% 29% 23% 12% 15% 17% 45% 26% 32% 30% 21% 23% 25% 21% 27% 13% 12% 13% 12% 60+ years old 35-59 18-34 12-17 5-11 (N=1,355)\n\n**GENDER = MALE**\n\nOnly formal Only informal Both None Other 44% 36% 10% 17% 21% 25% 9% 14% 11%", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n**Table 2. Deloitte D.Climate model results for Ukrainian refugees’ influx**\n\n**Current estimate** **Long-run estimate**\n2024 2030\n\n**Gross Domestic Product** +2.71% +3.21%\n\n**Unemployment rate** - -0.10 pp.\n\n**Real wages** 0.00% +0.24%\n\n**General government income** +2.94% +2.73%\n\nSource: Deloitte D.Climate estimates.\n\n**The positive shock to the marginal**\n\n**productivity of labour stabilized the**\n\n**current impact on the labour market**\n\n**and should turn positive in the long**\n\n**run.** In the model, additional influx of\nemployees increases labour market competition, creating an upward pressure on unemployment rate and downward pressure on real wages. This increase almost completely offsets the additional positive shock to the marginal productivity of labour. While the assumed increase in productivity stabilizes unemployment rate and real wage impacts in the 2022-2024, in the long-term, in 2030 the cumulative impact of Ukrainian refugees should lower the unemployment rate by 0.1 pp. and increase real wages by 0.24%.\n\n**Ukrainian refugees increase general**\n\n**government revenue as workers,**\n\n**entrepreneurs, and consumers.** First,\na larger number of employees increases the wage pool. Second, a larger population increases private consumption. Both streams are taxed. Also, an inflow of capital", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "THE ROLE OF HOUSING SUPPORT AND EMPLOYMENT FACILITATION IN ECONOMIC VULNERABILITY OF REFUGEES FROM UKRAINE It is important to note that while the poverty definition adopted in this assessment allows for comparisons across the countries covered (both regarding the refugee and local populations, though limitations need to be taken into account), it may not be directly comparable to other studies, as approaches tend to vary quite significantly. The setup of the questionnaire, the sampling methodology, the amount of non-response bias (and whether any corrections for it were done), the process adapted to equivalize income, and finally the location of the poverty line itself in the income range can have a substantial impact on the calculated indicators.\n\nRandom selection of settlements and convenience Bulgaria 1,054 2,255 Jul-Aug Global Metrics Ltd sampling for household selection.\n\nCzech Sample distribution by geographical strata and 1,218 2,648 June-Jul SocioFactor Republic convenience sampling for household selection.\n\nTárki Social Hungary 682 1,511 Jun-Aug Research Institute, IOM, UNHCR Random selection of districts and convenience sampling for household selection.\n\nSample distribution by geographical strata and Moldova 890 2,130 Aug-Sep REACH, UNHCR convenience sampling for household selection.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**PC partners.**\n\nThe morning session focused on explain\ning the concept of mixed migration and\n\nvarious migratory profiles, emphasiz\ning the distinctions between the causes\n\nand consequences of migration through\n\ngroup dynamics. In the latter part of the\n\nsession, the meaning of durable solu\ntions and the criteria for achieving them\n\nwere presented in relation to migratory\n\nprofiles and the Venezuelan context.\n\nFinally, together with IOM, a session on\n\nreturns and reintegration was included\n\nto discuss practical implementation\n\nof durable solutions. A total of 20 local\n\nand international organizations, part of\n\nthe PC, participated, and the feedback\n\nreceived was positive. Finally, to assure\n\nthat this information reaches colleagues\n\nin the field, an online session was orga\nnized on November 7th. Despite the\n\nchallenges posed by virtual sessions,\n\n28 people attended the session, showed\n\ninterest in the topic, and actively par\nticipated during the organized group\n\ndynamics.\n\n**XI. Reporting Transition to 345W**\n\n**During September and October, two**\n\n**training sessions were conducted**\n\n**with Protection Cluster Partners to**\n\n**facilitate the transition from the 5W**\n\n**system to the 345W reporting plat-**\n\n**form.** Adjustments were made in the\n\nplatform to reinforce quality controls, and\n\nAreas of Improvement were identified", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Despite \r the \r positive \r developments \r outlined \r above, \r considerable \r uncertainty \r remains\naround \r whether \r the \r cease-­‐fire \r agreements \r will \r lead \r to \r durable \r peace \r accords. \r There\nwere \r a \r number \r of \r clashes \r between \r armed \r groups \r and \r the \r Myanmar \r army \r reported \r in\n2012 \r in \r Shan, \r Kayah \r and \r Kayin. \r Trust \r in \r the \r Government \r is \r yet \r to \r be \r built \r in \r cease-­‐fire\nareas, \r after \r a \r long \r history \r of \r human \r rights \r abuses. \r Developments \r in \r relation \r to \r the\nconflict \r in \r Kachin \r will \r also \r play \r a \r role \r in \r influencing \r the \r prospects \r for \r peace \r elsewhere.\nPeace \r agreements \r will \r involve \r decisions \r on \r how \r best \r to \r share \r revenues \r from \r the \r natural\nresources \r in \r cease-­‐fire \r areas, \r how \r much \r to \r devolve \r political \r and \r economic \r authority \r to\nthe \r regional \r level, \r as \r well \r as \r how \r to \r maintain \r ethnic \r culture \r and \r language. \r Negotiations\nhave \r been \r and \r will \r continue \r to \r be \r extremely \r complex \r and \r the \r trajectory \r of \r the \r process\ntherefore \r remains \r uncertain.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Refugees’ impact on the economy manifests in a multi-layered fashion. An influx of refugees means first and foremost an increase in population. As such, they enter the economy boosting the labour market as new workers, increase demand as new consumers, and stimulate business by creating market niches catering to their needs and as potential new business owners. However, their characteristics differ from the local population (in terms of gender, age, education, skills etc.) meaning their impact as both workers as well as consumers would not be proportional to increases in population. Refugees also differ in their characteristics with other migrants. Although their economic impact in the literature is modelled similarly to the impact of other migrant groups, they also differ from them due to life circumstances.\nWhile immigration systems generally rely on 30", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "On 27 June 2023, Chad’s National Transitional Council (CNT) officially adopted the proposed new\nConstitution. This Constitution aims to restore constitutional order and conclude the transition initiated\nafter the passing of former President Idriss Déby on 19 April 2021. Drawing from the 1996 Constitution,\nthe document incorporates recommendations from the national dialogue. Notably, the reinstatement\nof institutions such as the Senate, the High Court of Justice and the Supreme Court occurs, preserving\nthe decentralized unitary state. Half of the cross-cutting recommendations from the Sovereign National\nInclusive Dialogue (DNIS) concentrate on fostering social cohesion. The primary focus of the Post-DNIS\nTransition Specifications’ initial strategic axis revolves around Defence, Security, Peace, Social Cohesion\nand National Reconciliation. Consequently, the Ministry of National Reconciliation and Social Cohesion has\nbeen established.\n\n[As part of the RESILAC project funded by the European Union (EU) and the French Development Agency](https://www.urd.org/fr/publication/rapports-de-capitalisation-du-projet-resilac-2020-2022/)\n[(AFD), the capitalization report on the implementation of social cohesion activities in the Lake Chad basin](https://www.urd.org/fr/publication/rapports-de-capitalisation-du-projet-resilac-2020-2022/)\n[(2022)](https://www.urd.org/fr/publication/rapports-de-capitalisation-du-projet-resilac-2020-2022/) recommended strengthening social cohesion at various levels (community members, groups,\ninstitutions) and adopting a cross-cutting approach coupled with economic recovery and institutional\nsupport activities.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "including physical and sexual abuse and neglect; children are kept from school due to difficulties\npaying for incidental school expenses; refugees have limited opportunities to productively engage in\nIndonesia by developing and utilizing skills and capacities in an employment setting, impacting both\nthe quality of their experience in the host country and opportunities to access a third country solution\nthrough labor mobility; barriers to accessing the workplace limit opportunities to meaningfully\ninteract with Indonesians, impacting social cohesion between refugees and their hosts; refugees are\nunable to make positive contributions to the Indonesian economy while residing in the country; etc.\n\n### **Smuggling and Trafficking**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "There \r are \r no \r mine \r maps \r currently \r available \r and \r the \r extent \r of \r the \r threat \r is \r impossible \r to\naccurately \r assess. \r However, \r it \r is \r suspected \r that \r Myanmar \r is \r one \r of \r the \r most \r highly\nlandmine-­‐contaminated \r countries \r in \r the \r world, \r with \r these \r devices \r continuing \r to \r claim\nseveral \r hundred \r civilian \r victims \r each \r year. \r Myanmar \r has \r not \r acceded \r to \r the \r Mine \r Ban\nTreaty \r but \r has \r recently \r set \r up \r a \r Myanmar \r Mine \r Action \r Centre, \r under \r the \r Myanmar\nPeace \r Centre \r (MPC) [4] to \r co-­‐ordinate \r and \r oversee \r the \r implementation \r of \r a \r national\n\n3 _Changing \r Realities, \r Poverty \r and \r Displacement \r In \r South \r East \r Burma/Myanmar_, \r The \r Border \r Consortium, \r 31\nOctober \r 2012, http://www.tbbc.org/resources).\n\n---\n[4] The \r Myanmar \r Peace \r Centre \r (MPC) \r was \r established \r in \r October \r 2012 \r by \r a \r Presidential \r Decree \r to \r serve \r as", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**Unaccounted positive externalities**\nAll our theoretical economic modelling results are conservative lower bound estimates, as econometric studies from other countries have found immigration to have additionally a positive impact on labour productivity that cannot be accounted for using the available data.\nAccording to these econometric studies, immigration can not only raise economic output (i.e., more workers equal more production), but more importantly labour productivity (i.e., more value added per worker). Such results are unfortunately too aggregated to disentangle the constituent effects (Chapter 4).", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "immigration in a sample of 18 developed OECD countries during the 1980-2010 period. Authors find that increase of immigrant share in the adult population by 1 percentage point raises labour productivity and GDP per capita in the longterm by about 2%. They also examine impacts for the population in top 10% and bottom 90% of income distribution of tertiary and non-tertiary educated immigrants. Effects are similarly 2-3%, apart from the impact of tertiary educated immigrants on population in the top 10%, which are about 6%. These are not just correlations, but causal estimates, as authors carefully address potential problems of reverse causality (i.e., that immigrants may migrate to countries with better growth prospects, instead of improving them). They want to estimate the impact of immigrant shares on GDP per capita, but these could be correlated (biasing the result) as GDP per capita is a pull factor for immigrants. To resolve this, they first create an “instrument” for immigrant shares by estimating a model that predicts them based on country-of-origin push factors and bilateral migration costs determined by geography and culture. In effect they can now control for reverse causality.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Smooth inclusion of refugees on labour market thus far was enabled by proper policies. In response to the war escalation in Ukraine and the influx of refugees into the EU, prompt actions were taken both at EU and national level.\n\nRefugees from Ukraine in the European Union are covered by the Temporary Protection Directive TPD, which was activated on 4th March 2022 (European Council, 2022). The regulation aims to support EU Member States’ asylum schemes and to ensure harmonised rights for the incoming Ukrainian refugees throughout the EU. It also includes citizens who fled Ukraine not long before 24th February and those who were outside the", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Lower income households are, on the other hand, much more dependent on social protection benefits. These comprise almost half of all earnings.\nTwo thirds of the income provided by social protection is generated by the host country, with the remainder mostly coming from pensions paid by Ukraine (13% of all adults below the poverty line are of pension age as opposed to 5% above it).\n\n**The overall employment rate of refugees from**\n\n**Ukraine is almost in line with host country**\n\n**nationals**\nAcross the region, employment stands out as the largest source of income for refugee households by far (64% of all earnings). In some countries – such as Hungary and Poland this share is even larger (at 74% and 68%, respectively). Moldova appears to be an outlier, with employment representing only 32% of respondent household income, but this figure may have been affected by sampling limitations.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "- Refugees \r and \r IDPs \r are \r provided \r with \r accurate \r and \r up-­‐to-­‐date \r information \r that \r is\nobjectively \r presented \r and \r consistent \r with \r humanitarian \r protection \r and \r human\nrights \r principles \r and \r a \r wide \r range \r of \r representatives \r are \r allowed \r to \r visit \r places\nof \r origin \r or \r intended \r return.\n\n- All \r stakeholders \r at \r all \r level \r have \r a \r clear \r understanding \r and \r commitment \r to \r the\nprinciples \r and \r standards \r underpinning \r durable \r solutions.\n\n- The \r Government \r includes \r local \r integration/reintegration \r needs \r of \r IDPs \r and\nreturning \r refugees \r in \r its \r long \r term \r development \r plans.\n\n- Sufficient \r resources \r are \r available \r to \r increase \r UNHCR \r and \r partners’ \r operational\ncapacity \r in \r the \r immediate \r to \r longer \r term. \r Investments \r are \r made \r by \r development\nactors \r in \r long-­‐term \r reconstruction \r and \r development \r projects. \r Many \r places \r of\norigin \r of \r refugees \r are \r isolated \r and \r have \r received \r little \r investment \r in\ninfrastructures \r or \r in \r the \r creation \r of \r livelihood \r opportunities \r that \r can \r support \r the\nsustainability \r of \r the \r return \r process.\n\n11", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "**even greater disparity in financial wellbeing**\n\nAt the regional level, the weighted average share of the host population living in rented housing was calculated at 13% based on Eurostat data. This figure is dwarfed by 60% of refugee households fully paying rent for their accommodation and 21% partially paying, as per the SEIS survey. Likewise, accommodation expenses as a share of disposable income were estimated at 17% for hosts, including mortgages, compared to 32% for refugees. This essentially implies that refugees, on average, have a much smaller share of their disposable income remaining for other needs. To estimate the magnitude of this effect, poverty rates were recalculated after subtracting the portion of housing expenses that exceed the national average directly from disposable income. This calculation almost doubled the poverty rate, bringing it to 40%.\n\n11. Defined as someone feeling so upset, anxious, worried, agitated, or depressed that it affects daily functioning\n\n**5**", "output": {"entities": {"named_data": [{"text": "SEIS survey"}], "descriptive_data": [{"text": "Eurostat data"}], "vague_data": []}}}
{"input": "the general population. UNHCR (2025b), using a different method than the one in this report, estimated average instead of median net wages based on the SEIS data. The average net wage of a Ukrainian refugee they arrived at was PLN 4,214, only slightly higher than calculated above. This would yield 72% of the national average net wage. [15] Average is not used here, because median is more relevant for discussing economic impact, as it is not disrupted by bottom or top earnings. Furthermore, there are no outside estimates to compare it to. Second, as discussed previously, there are much fewer Ukrainian refugees with employment contracts than Poles, and this lowers their social contributions and thus gross earnings. Unfortunately, there is no such data available, as both SEIS and NBP (2024) measure only net earnings.\n\n**Chart 13. Polish citizens and Ukrainian refugees’ employment rates by age group**\n\nMale Female\n\n**Chart 14. Ukrainian refugee median net wage estimates in Q2 2024**\n\nMonthly net wage (PLN) Percengate of all workers total economy average 84% UNHCR NBP UNHCR NBP 15 May - 24 June 2024 6 May - 5 July 2024 15 May - 24 June 2024 6 May - 5 July 2024", "output": {"entities": {"named_data": [{"text": "SEIS data"}], "descriptive_data": [], "vague_data": []}}}
{"input": "[In addition to the constitutional guarantee of freedom of movement, Article 21 of the Asylum Law](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf) confirms\nthat refugees and asylum-seekers in possession of their identification documents enjoy the right to circulate\nand to reside in Chad in the same conditions as nationals. Furthermore, Article 73 of the [2023 Decree](https://www.ecoi.net/en/file/local/2091861/645b938a4.pdf)\noutlines that the refugee identity card allows the free movement of refugees in the conditions specified\nby the law. Additionally, Article 61 of the 2023 Decree specifically addressing local integration of refugees\nrecognizes, as part of the perquisite to achieve self-reliance, among others, the freedom of movement and\nthe right to settle in places favourable to their self-reliance.\n\nHowever, regarding asylum-seekers, it is important to note that Article 20 of the 2020 Law, incorporating\nthe principle of non-penalization for illegal entry, specifies in its second paragraph that the movement of\nasylum-seekers is restricted only if necessary and as long as their refugee status is not determined or until\nthey have been admitted to another host country.\n\nRefugees and asylum seekers continue to have access to a free travel permit issued by CNARR (saufconduits). This document specifies the intended destination and the duration of absence from the camp.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "requests.\n\n### **Solutions - Resettlement**\n\nUNHCR Indonesia continues to identify and submit refugees for resettlement consideration. In 2024,\n950 resettlement spaces have been made available for refugees in Indonesia. UNHCR seeks to ensure\nthe most vulnerable refugees are prioritized for resettlement consideration, assessing heightened\nspecific needs and protection concerns, as well as length of stay in the country, when identifying cases\nfor submission.\n\n### **Solutions - Complementary Pathways**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "to the MSNA Poland 2023 survey, 20% of Ukrainian refugee households earn less than 3 000 PLN, 41% earn between 3 000 and 6 000 PLN, and 12% earn more than 6 000 PLN, while 27% of respondents preferred not to answer. That said, the standard of living of Ukrainian refugees may be significantly lower than that of native residents, even at similar incomes, due to their lack of housing, which in Poland is usually occupant-owned.\n\n**Inflow of Ukrainian refugees into**", "output": {"entities": {"named_data": [{"text": "MSNA Poland 2023 survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "- Governments, development and humanitarian actors take into account poverty levels when designing their\nsupport programs for Ukrainian refugees. The quality of day to day life, safety, and level of access to key services are directly tied to household income.\n\n- Poverty measures account for differences in housing costs between refugees and host populations.\n\n- A special focus is placed on supporting refugee employment at their skill level, including transition from\ncurrent low-level jobs. The difference between refugee and local population wages could be an important metric to monitor on an ongoing basis", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland\n\n## Executive summary\n\n##### Progress in market integration\n\n**Ukrainian refugees have been**\n\n**increasingly successful in terms of**\n\n**labour market integration.** The large\ninflux of refugees since February 2022, has further increased and changed the demographics of the already significant Ukrainian migrant population in Poland.\nRefugees from Ukraine are primarily women and children, with over 67% of female-headed households. Poland was quick to open its labour market to refugees from Ukraine, who – despite difficulties\n\n- surprisingly promptly began their\neconomic integration and soon supported themselves primarily from employment.\nIn the past year, refugees’ employment rate grew from 61% to 69%, with the median net wage rising from PLN 3,100 to PLN 4,000 and narrowing the gap to the median net wage in the entire economy.\n\n**As Ukrainian refugees entered the**\n\n**labour market, the economy adapted,**\n\n**resulting in more specialization and**", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}
{"input": "HIGH EMPLOYMENT RATES, BUT LOW WAGES: A POVERTY ASSESSMENT OF UKRAINIAN REFUGEES IN NEIGHBORING COUNTRIES\n\n# **Summary of findings and** **recommendations**\n\nThe 2024 round of the SEIS survey indicates that while the financial vulnerability of refugees from Ukraine residing in neighboring countries - specifically those included in the [Regional Refugee Response Plan - has](https://www.unhcr.org/europe/publications/regional-refugee-response-plan-2025-2026) declined over the past year [1], one in five still live with an income below the poverty line [2] . When factoring in the disproportionately high accommodation costs refugees face, largely due to the region’s high homeownership rates among locals, the poverty rate [3] rises to 40%, more than three times that of host communities [4] .", "output": {"entities": {"named_data": [{"text": "the 2024 round of the SEIS survey"}], "descriptive_data": [], "vague_data": []}}}
{"input": "Analysis of the impact of refugees from Ukraine on the economy of Poland The above results do not distinguish between Ukrainian refugees improving the labour market outcomes in the poviats they arrived in and Ukrainian refugees disproportionately moving to the poviats with better performance, which continued to perform better in subsequent quarters. This distinction is mostly academic, as causality is always uncertain in social sciences, as effects can run both ways. However, instrumental variable regressions have been performed to ascertain causal effects. This approach is widely used in studies focused on the impact of migration on socio-economic outcomes. This econometric technique additionally uses variables that correlate well with Ukrainian refugees’ employment shares, but do not directly cause changes to the Polish citizens' employment rate or to the unemployment rate. Two variables have been used: the first was the share of Ukrainian children in Polish schools, and the second was the pre-war distribution of Ukrainian citizens based on notifications of entrusting work to a foreigner. Unfortunately, panel fixed effects regressions with quarterly dummies showed statistically insignificant results for either instruments or both. In addition, regressions using only the instrumental variable for the distribution of pre-war Ukrainian citizens reveal only a modest link to the employment share of Ukrainian refugees.", "output": {"entities": {"named_data": [], "descriptive_data": [], "vague_data": []}}}