Input: compared to their hosts, with a higher percentage of refugees in Addis Ababa completing primary (45 percent) and secondary (27 percent) education (Figure 2.7). Although more educated, even youth’s (age 15 to 24) educational attainment is low, with large differences by survey domains. Many youth refugees and hosts have not completed primary education (Figure 2.8). While the percentage of youth who completed primary education is close to 50 percent for hosts, it is only 35 percent of in-camp refugee youth. Moreover, there are large differences by location, with only 22 percent of Eritrean refugee youths in camps having completed primary school compared to 37 percent of in-camp Somali youth. On the other hand, refugee youth in Addis Ababa have similar levels of education compared to their hosts (Annex D, Table D.2). 14 In an emergency setting, it is recommend to provide refugees with access to educational programmes within the first 3 months of arrival in the hosting country. 15 Moreover, access to education services is often tied to having identification documents. Enabling refugees to receive identification documents is critical, not only for accessing education but also other services such as health or financial services. Sociodemographic Profile 13 16 In January

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Input: In a 2004 note to its Executive Com- mittee, UNHCR established the average at 17 years at the end of 2003 (Executive Committee of the High Commissioner ’ s Programme 2004). This number has been widely quoted by media, ac- tivists, humanitarian agencies, and development institutions (Milner 2014; United Nations 2016; UNHCR 2015). The rest of the paper is organized as follows. Section 1 gives some deﬁnitions and background information on the refugee population. In section 2, we provide some summary statistics from our main source of data, the UNHCR Population Statistics Database. Section 3 describes the method followed to construct duration statistics and presents a few stylized facts. The results of our anal- ysis are presented in section 4. Section 5 concludes. 1 Background: Deﬁnitions and Data Under the terms of the 1951 Convention Relating to the Status of Refugees – henceforth the Convention – later amended by the 1967 Protocol, a refugee is a person, who “ owing to a well-founded fear of being persecuted for reasons of race, religion, nationality, membership of a particular social group or political opinion, is outside the country of his nationality, and is unable to, or owing to such fear, is unwilling to avail himself of the protection of that country. ” Data on refugees and asylum seekers are collected by individual countries, international orga- 3

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Input: Page 27 of 51 Figure 18: Prevalence of Part-time employment among salaried employees. (Early 2000s / Mid-2010s) Source: Own calculations based on Household surveys. Figure 19: Prevalence of Temporary employment among salaried employees. (Early 2000s / Mid-2010s) Source: Own calculations based on Household surveys The older age profile of part-time employment in most of the analyzed countries of Eastern Europe and Asia is consistent with the age profile observed for total employment. In fact, the mean age of the labor force rose 4. 5 years on average in the countries included in the study. That is, the older age profile of NSE workers reflects the aging trend of the overall labor force. 0 % 2 % 4 % 6 % 8 % 10 % 12 % 14 % 16 % Russia Georgia Kyrgyz Republic Turkey Armenia Albania Moldova Starting point Ending point 0 % 5 % 10 % 15 % 20 % 25 % Georgia Kyrgyz Republic Turkey Armenia starting point ending point

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Input: m and SD are the mean and standard deviation value of the distribution corresponding the reference population (2006 WHO Child Growth Standards). Sociodemographic Profile 21 Disability Disability rates are similar for hosts and refugees. The proportion of individuals with a disability29 is comparable between refugees and hosts, except for Eritrean refugees. The percentage of persons with disabilities is higher among Eritrean refugees (8 percent) compared to hosts (5 percent). At the national level, and estimated 9 percent of the population lives with at least one disability, according to 2016 national survey results (UNICEF, 2018). Disability is more prevalent among elderly refugees and hosts who above age 60 compared to adults and children. Refugees and hosts mainly face disabilities related to seeing, walking, or climbing steps (Annex D, Figure D.13). 2.4 Living conditions Housing differs drastically between refugees and their hosts, with in-camp refugees living in UN or NGO shelters, and refugees in Addis Ababa residing in rented houses. Most Eritrean refugee households (61 percent) live in temporary30 shelters provided by the UN or NGOs, whereas 50 percent of Somali refugee households and 71 percent of South Sudanese refugee households live in UN or NGO-provided permanent31 shelters. In Addis Ababa, 97

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Input: 33 recommendations (Jewkes, 2000). Their efforts contributed to the Employment of Educators Act and new Department of Education guidelines, both of which were introduced in 2000. These regulations mandate dismissal of educators found guilty of sexual or physical assault, or of having a sexual relationship with a student. They also define penalties for failing to report abuse. It remains to be seen whether these measures will have the intended impact. After the act was passed, Human Rights Watch (2001) suggested that the South African government needed to do more to increase awareness of the law among school principals and to strengthen enforcement. Institutional reform Efforts to improve the institutional response to gender-based violence range from sensitization and training of staff, sexual harassment policies, curriculum reform, school-wide anti-violence awareness campaigns, counseling and referrals, and broader efforts to reduce discrimination against girls and improve school safety. Initiatives to increase female enrolment by improving girls ’ safety at and on the way to school As mentioned earlier, parental concerns about girls ’ safety in school appears to lower female school enrolment in settings such as South Asia, Africa and the Middle East. Usage context: primary mention, supporting mention, background mention.

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Input:
 Youth noted that the **continuation of armed conflict increases vulnerability to exclusion** . Both groups
agreed that addressing these issues requires tackling corruption, improving awareness, and ensuring equal
opportunities for all.
 **Absence of data** is also a relevant finding. Protection risks analysis on youth have not been produced in a
systematic manner in NWS, thus the identification of the particularity of the risks the population group
faces has not been documented, or even assessed. Concrete risks such as exploitation, forced labor, forced
recruitment have been addressed, to some extent, for children (until 18 years), but not for young people
(18-23).
 Findings also highlight the **need to have enhanced technical expertise** to assess, analyze and design
adequate responses for youth, that take into consideration the specific exposure to specific risks by young
men and young women, and doesn’t neglect these considerations in an equal manner.
 When asking youth if there are any mitigation strategies in place for these risks, results indicate that 47%
of youth in northwest Syria report the presence of mitigation strategies for protection risks, while 53% do
not. Among those who have access to mitigation strategies, the most common approaches include

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Input: reliance, economic integration, and access to education and health. By leveraging data from initiatives like SESRE and adopting a comprehensive approach that considers the needs of both refugees and host communities, Ethiopia can maximize the benefits from hosting refugees while minimizing associated costs. The Government of Ethiopia has committed to a significant shift in its refugee management policies and most recently in its pledges and commitments made at the 2023 Global Refugee Forum to improve the socio and economic opportunities for refugees through an agenda to transform camps to human settlements as well as for inclusion into national services for education, including secondary education as well as health (UNHCR, 2024). The recommendations below advance these commitments backed by the findings in this survey. Key policy recommendations stemming from this analysis are: Promote refugee self-reliance: ◆ Enable mobility for refugees to access areas with higher economic opportunities. ◆ Facilitate labor market access for refugees by easing restrictions and providing work permits. ◆ Integrate refugee children into national education system to improve their long-term prospects. ◆ Strengthen inclusive healthcare systems to address the health needs of refugees. Focus on place-based interventions: ◆ Invest in refugee hosting areas to benefit both refugees and

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Input:
Existing coastal flood maps covering Vietnam, most prominently the Global Tide and Surge Reanalysis (GTSR) data set (Muis et al. 2016), are expected to underestimate coastal flood risk in Vietnam.

It is based on a global digital elevation map with a resolution of 90 meters at the equator that has been corrected for several errors typically present in spaceborn elevation models (Yamazaki et al. 2017).

These curves have been generated by statistically postprocessing the results from storm surge modeling with a wide range of possible typhoons (Ministry of Agriculture and Rural Development, 2012).

Typhoon wind speeds used in this analysis were produced by a global model of cyclone winds calibrated
on over 2,500 past cyclones, terrain composure, and ocean depth. It contains the modelled maximum
wind speed at every location in Vietnam for typhoons occurring, on average, every 50, 100, and 1000
years (figure 2.2). The data is in raster format has a grid resolution of roughly 30 by 30 kilometers (UNDRR,
2015).

**Figure 2.2: Wind speeds over Vietnam in typhoons of varying severity**

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Input: images. All queries on rights and licenses should be addressed to World Bank Publications, The World Bank Group, 1818 H Street NW, Washington, DC 20433, USA; e-mail: pubrights@worldbank.org. Photos: © World Bank Abbreviations........................................................................................................................................................................................................................................................................................ i Acknowledgements....................................................................................................................................................................................................................................................................... ii Executive Summary......................................................................................................................................................................................................................................................................... vi 1. Introduction............................................................................................................................................................................................................................................................................... 1 1.1 How can we achieve better development outcomes for all?.................................................................................................................................................... 5 1.2 How does Socio-Economic Survey of Refugees in Ethiopia (SESRE) contribute to the debate on policies?....................................... 6 2. Sociodemographic Profile ........................................................................................................................................................................................................................................... 9 2.1 Demographic characteristics .............................................................................................................................................................................................................................. 9 2.2 Education .......................................................................................................................................................................................................................................................................... 12 2.3 Health and nutrition.................................................................................................................................................................................................................................................. 17 2.4 Living conditions.......................................................................................................................................................................................................................................................... 21 3. Jobs and Livelihoods ....................................................................................................................................................................................................................................................... 24 3.1 Labor market outcomes of in-camp refugees and their hosts................................................................................................................................................ 27 3.2 Labor market outcomes of OCP refugees and their hosts.......................................................................................................................................................... 34 3.3 Refugee youth................................................................................................................................................................................................................................................................ 37 4. Refugees’ Aspirations....................................................................................................................................................................................................................................................... 39 5. Welfare and Equity.............................................................................................................................................................................................................................................................. 42 5.1 Welfare dimensions.................................................................................................................................................................................................................................................... 42 5.1.1 Monetary poverty and inequality .............................................................................................................................................................................................. 42 5.1.2 Expenditure patterns ......................................................................................................................................................................................................................... 44 5.1.3 Multidimensional poverty ............................................................................................................................................................................................................. 46 5.1.4 Food security........................................................................................................................................................................................................................................... 47 5.1.5 Shocks and coping strategies....................................................................................................................................................................................................... 48 5.2 Determinants of welfare......................................................................................................................................................................................................................................... 49 5.3 Cost of basic needs for refugees ..................................................................................................................................................................................................................... 53 6. Markets and Opportunities ....................................................................................................................................................................................................................................... 56 6.1 Spatial disparities in refugees labor market access and outcomes...................................................................................................................................... 57 6.2 Effects of local

Socio-Economic Survey of Refugees in Ethiopia

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Input: In order to address these potential sample biases, the CAVR supplemented its documentation with reports produced by Amnesty International and Fokupers (a local NGO). The information contained in these reports was then included into the HRVD database. 9 Note that we do not analyse school completion in 2001 because most children that were of school age in 1999 were still in school in 2001. 10 The questions we used are ― Was [NAME] displaced outside E. Timor in 1999? ‖, and ― Was the [BUILDING] damaged in the violence of 1999? ‖. 14 % of the whole sample surveyed in 2001 report having been displaced, while 26 % report that their house was destroyed. Within our sample of school age children, these figures are 16 % and 25 %, respectively. We have made sure that buildings that are reported to having been destroyed were used for living purposes only. Usage context: background mention, primary mention, supporting mention.

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Input: Figure 5: Significant Historical Crises as a Share of Total Forced Displaced 1991 – 2015 Source: UNHCR Statistical Online Population Database, UNHCR Global Trends 2015 Note: Includes IDPs protected or assisted by UNHCR, asylum-seekers and refugees. Excludes IDPs not protected or assisted by UNHCR and Palestinian refugees under UNRWA ’ s mandate. Figure 6: Top 15 Countries of Origin end-2015 Source: IDMC Global Report on Internal Displacement 2016, UNHCR Global Trends 2015, UNRWA A small number of countries carry the burden of hosting the majority of refugees. Historically since 1991, 15 asylum countries, overwhelmingly in the developing world, have hosted more than 50 percent of refugees and asylum-seekers (see Figure 7). 44 By the end of 2015, while almost all countries in the world were hosting refugees, the burden was unevenly shared (see Figure 8). Only seven countries hosted more 44 Major host countries are identified based on the cumulative number of refugees and asylum-seekers over the period 1991-2015. Usage context: background mention, primary mention, supporting mention.

UNHCR Statistical Online Population Database

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Input: As summarized by Robinson (2017), “ fortunately, Afrobarometer respondents comprise stratified random samples at all levels, making population estimates based on them unbiased: thus, the major concern with using Afrobarometer sample data to construct demographic measures is unbiased measurement error. ” Based on a comparison of census-based and survey-based diversity indexes across five African countries, Robinson (2017, 224) found that a “ sample-based measure tends to underestimate the overall degree of diversity compared to census data ”. In theory, this should make it more difficult to observe the true relationship between ethnic diversity and some outcomes at the local level. Diversity indices are more likely to be measured with noise in highly diverse communities at the local level. We nonetheless argue that such a concern should not be overestimated, for three reasons. First, such noise cannot easily explain the contrast between the coefficients corresponding to the pre-revised and revised indices and the opposite results found for the revised refugee fractionalization and the revised polarization. This set of results can be explained by the fact that our identification comes from the annual changes in refugees flows. Second, the IV approach is likely to deal with the measurement errors if they are correlated with our main variables of interest. Our IV estimates therefore capture a local average treatment effect coming from the plausibly exogenous increase in annual refugee flows of particular ethnic groups. The similarity of the IV results to the OLS results supports this interpretation. Third, at the cost of introducing attenuation bias30, we also aggregate the number of conflict events at the regional level. Lines B and C of Table 7 confirm the negative and positive effects found for the revised fractionalization and polarization indexes, respectively, whether or not 30Another risk highlighted by Robinson (2017) is the fact that ethnic diversity may also capture different theoretical mechanisms at aggregated levels. 34

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Input: Having experienced the work task and therefore able to realistically value the work, we oﬀer individuals in the employment arm an additional [surprise] week of work at a series of wages following the incentivized Becker-DeGroot-Marschak (BDM) method. We inform participants that we have a limited amount of funds remaining and are therefore unable to pay everyone their previous wage. This strategy realistically motivates the reservation wage elicitation exercise and makes clear that there will be no further opportunities for work. We piloted this exercise extensively. To maximize comprehension, we employ a multiple price list strategy, embed repeated conﬁrmations, and conduct a trial run of the exercise for each respondent before the real exercise; this mimics the procedure employed in Burchardi et al. (2021) for which participants in another low-income country ﬁeld context exhibited high comprehension. For those individuals who express willingness to work at a wage of zero, we oﬀer an alternative option of answering a brief survey at the end of the week for a small, randomized fee; we then use the fraction of respondents who are willing to forego this paid option and instead work for free as an estimate of the proportion of respondents who have a negative reservation wage of at least the foregone magnitude. 16 Usage context: primary mention, supporting mention, background mention.

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Input: The MPI can be decomposed by any groups for which the data are representative and broken down by indicator to show the composition of multidimensional poverty, adding to the policy relevance of the analysis. To tackle individual-level and intrahousehold analyses, we build on the work of Alkire, Ul Haq and Alim (2019). The focus is on individual deprivations, and we call the persons with individual-level data in each indicator the eligible household members. For example, children aged 6-16 years might be eligible for deprivations in terms of school attendance, but not those older or younger. For individual-level indicators, we identify who and how many household members are deprived: their gender and their age, and what proportion of eligible household members are deprived. This is a powerful and potentially informative steppingstone for analysis. Consider two households, each of which has five eligible members with data on nutrition. The aggregation rule in this example is that if any household member is undernourished then the household is undernourished. So, both households are deprived in terms of

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Input: While camps have been recognized as posing serious challenges (Jacobsen and Crisp 1998), it is quite striking to observe that this organizational feature is not as spread in other regions of the world as in SSA. At best, only 28, 25 and 15 percent refugees are hosted in planned / managed camps in Asia, Americas, and the MENA region, respectively. Such figures are based on the most recent year available (2013) and may change significantly following the large inflows of Syrian refugees into Egypt, Lebanon, Iraq, Jordan and Turkey. Nonetheless, the differences are sufficiently striking to believe that this is a distinct feature of refugee hosting in SSA. 2 UNHCR defines a protracted refugee situation as “ one in which 25, 000 or more refugees of the same nationality have been in exile for five years or longer in a given asylum country ” (2012: 23). 3 The figures are based on refugees (including those in refugee ‐ like situation). Persons in refugee ‐ like situations include “ groups of persons who are outside their country or territory of origin and who face protection risks similar to refugees but for whom refugee status has, for practical or other reasons, not been ascertained ” (UNHCR 2014: 39). The number of refugees and people in refugee ‐ like situation for which demographic data is available does not necessarily equal the total number of refugees. However, for SSA, there is little difference between the two. We also restrict the number of refugees to those whose accommodation is known by the UNHCR (approximately 19 % in the world and 8 % for SSA). Usage context: primary mention, supporting mention, background mention.

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Input: 60 70 80 90 Poorest 2 3 4 Richest Poorest 2 3 4 Richest Poorest 2 3 4 Richest Poorest 2 3 4 Richest Female headed Married head Age of head (year) Percent Age (years) In Camp Refugees In Camp Hosts Addis Ababa Refugees Addis Ababa Hosts Figure 5.14: Demographic characteristics by quintile Source: World Bank Staff based on SESRE 2023. Note: Primary axis labels represent gender and marital status. 0 10 20 30 40 50 60 70 80 90 100 Eritrean Somali South Sudanese Hosts Refugees Percent Figure 5.15: Poverty headcount rate for in-camp refugees and their hosts, by domain Source: World Bank Staff based on SESRE 2023. Refugees’ Aspirations 51 level of the household head increases. This is only the case for Addis Ababa refugees and hosts (Figure 5.16). However, for in-camp refugees, there appears to be no response to expenditure on an additional level of education of the household head compared to other refugees. In-camp host community households are higher, on average, than for in-camp refugees, and returns to the education level of the household head for these households appears to be slowly increasing. Household welfare is linked to possession of certain assets or access to services.

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Input: The current study builds on the literature above by drawing on nationally representative, population-based surveys to look at how displacement experience is associated with different forms of IPV (lifetime, past-year and injury-causing IPV) in Colombia and Liberia. Additionally, independent data on the level and location of conflict was merged with individual level data in each country. These unique data sets provide insight into how both types of adversity- conflict and displacement- may impact a woman ’ s risk of IPV. The goal of this work is to highlight the link between IPV and forced displacement and conflict, and to explore the policy implications for state and peace building efforts. This understanding will help direct scarce funding appropriately to create more effective and targeted programs. Colombia Background Colombia has endured civil war, violent conflict, and displacement for over 60 years. Levels and intensity of violence have fluctuated throughout this period between a multitude of groups, including guerrilla groups such as the Revolutionary Armed Forces of Colombia (FARC), the National Liberation Army (ELN) and the Popular Liberation Army (EPL), the government, and paramilitary forces (Palacios, 2006). The historical root cause of the conflict rests in the unequal Usage context: supporting mention, primary mention, background mention.

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Input: The large number of interconnected conﬂicts in these provinces involving non-state armed groups and state actors create a continuous ebb and ﬂow of displacement in eastern DRC (Jacobs & Kyamusugulwa 2018). In June 2020, UNHCR estimated that over 4. 5 million persons were internally displaced in Ituri (1. 6M), North Kivu (1. 9M) and South Kivu (1M) provinces alone (UNHCR 2020). DRC hosts an additional 536, 000 refugees (UNHCR 2020) from neighboring countries with recent experiences of violence, especially Burundi, Uganda, CAR, and South Sudan. Figure 2 plots the trend in the new IDPs in the DRC between 2009 and 2020. 5 Most IDPs in DRC favor staying with host families as opposed to camp displacement (Haver 2008, Rohwerder 2013). In 2017, UNOCHA estimated that around 500, 000 IDPs were in camp- like settings, whereas 3. 3 million sought refuge in host communities (Jacobs & Kyamusugulwa 4The qualitative analysis covers only the Kivu provinces, but the quantitative analysis covers all three. 5Data provided by the Internal Displacement Monitoring Center DRC Page, accessed May 14, 2021. 6 Usage context: background mention, supporting mention, primary mention.

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Input:
total area of 122,437 sq. km. Rainfall data from more than 200 rainfall stations and

potential evapotranspiration data of around 30 evaporation stations have been used in the

is estimated by overlaying the inundation risk map with the population map for 2001 using

Ahmed, A.U., Alam, M. 1998.: Development of Climate Change Scenarios with General
Circulation Models in Vulnerability and Adaption to Climate Change for Bangladesh, S.
Huq, Z. Karim, M. Asaduzzaman and F. Mahtab (Eds.), Kluwer Academic Publishers,
Dordrecht, pp.13-20.

Bangladesh Bureau of Statistics (BBS), 2007. Population Census-2001: National Series,
Volume-1 Analytical Report. Dhaka, Bangladesh.

2050. The best available spatially-disaggregated maps and data for these assets have been

evapotranspiration data of around 30 evaporation stations

Rainfall data
spatially-disaggregated maps and data

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Input: 8 Conclusions We conducted a correspondence study using an online job platform in Malaysia. We tested for ethnic discrimination, gender discrimination and the value of signaling soft skills in the labor market. Unlike many correspondence studies, the data allow us to observe different stages in the hiring process. We observe if the employer rejects an application, visits the profile of a candidate, number of times the profile is visited, if they contact them and if they offer an interview. Uniquely, we observe competition in the labor market on both the demand and supply sides. We do not find evidence of gender discrimination in the hiring process. Malaysia ’ s observed differential wages and labor force participation rates by gender do not seem to be associated with discrimination or human capital accumulation. More research is needed to determine why women in the Malaysian labor market have lower employment rates and wages. We find that Indian and Malay sounding name profiles are discriminated against in comparison to Chinese-sounding name profiles. There is discrimination along all the hiring process variables we observe. Malay and Indian candidates are 8 and 9 percentage points less likely to receive an interview offer relative to a Chinese candidate. Discrimination for both ethnicities is also present in other outcomes. Usage context: background mention, primary mention, supporting mention.

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Input: The authors argue that Croats listened to Serbian radio for its consumption value but reacted negatively to national- istic messages intended for Serbian ears. Election results and street surveys are used to elicit preference for extremist nationalist parties among Croats who are able to listen to Serbian radio and those that do not. The authors ﬁnd that 3 to 4 percent of those 59See Yanagizawa-Drott (2014). 60See, for example, Enikolopov et al. (2011) and DellaVigna and Kaplan (2007) who ﬁnd large eﬀects on voting shares. 70 Usage context: primary mention, supporting mention, background mention.

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Input: 41 Note: Refugee data are from the UNHCR statistical population online dataset, accessed in September 2014. Refugee data from 2007 to 2013 include people in refugee ‐ like situations (see note, Figure 1). IDP data from 1990 to 2008 are aggregated based on Center for Systematic Peace (http: / / www. systemicpeace. org /). UNHCR assisted ‐ IDP are compiled based on several UNHCR (1995, 1996, 2007, 2008, 2009, 2010, 2011, 2012, 2013, and 2014) reports. UNHCR ‐ assisted IDPs are only IDPs who are protected / assisted by UNHCR. These are also not necessarily representative of the entire IDP population in a given country. Many of the world's IDP situations are not covered by UNHCR and are thus not reflected. Since some adjustments could take place over time, we always use the figures from the last available report.

UNHCR statistical population online dataset

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Input: Many detainees are facing ill ‐ treatment. Females are subjected to sexual harassment by security officers. According to UNHCR, there are 2. 7 million people of concern in Sudan (includes refugees, asylum ‐ seekers, IDPs, returned refugees, returned IDPs, stateless persons, and other concern), a lower number than 2015. About 37, 000 refugees returned to Sudan in 2016. At the same time, there were over 2 million IDPs, over 420, 000 refugees and over 16, 000 asylum ‐ seekers in other countries. Economic Opportunity Oil output in Sudan has been low due to civil war, poor infrastructure, and low productivity. Compared to South Sudan, Sudan also has fewer oil resources; nevertheless, it still has abundant resources72. Sudan ranks 186th of 190 states in the World Bank ’ s Doing Business 67 CIA Factbook, South Sudan, https: / / www. cia. gov / library / publications / the ‐ world ‐ factbook / geos / od. html 68 UNHCR, South Sudan http: / / reporting. unhcr. org / node / 2553 69 CIA Factbook, South Sudan, https: / / www. cia. gov / library / publications / the ‐ world ‐ factbook / geos / od. html 70 UNHCR, Sudan, http: / / reporting. unhcr. org / node / 2535 71 Human Rights Watch, https: / / www. hrw. org / world ‐ report / 2017 / country ‐ chapters / sudan 72 EIU Country Outlook, Sudan, June 19th 2017

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Input:  In Somalia, the Mogadishu Household Survey covered both residential areas and IDP camps, collecting data on expenditures, demographics and living conditions [survey completed; analysis forthcoming]. As part of the Somalia Knowledge for Operations and Political Economy (SKOPE) initiative, the Puntland Household Survey will also cover both residential and IDP populations [ongoing].  An IDP study in South Sudan [ongoing] aims to assess the economic needs of IDPs and host communities in urban areas, covering livelihoods, water and sanitation, infrastructure as well as intentions and conditions to return. Basic information about education, employment and general health variables will also be collected.  The Iraq Crisis Response Study [ongoing] will assess the impact of the Islamic State and oil price-related crises on IDPs and households left behind in IS controlled areas. Usage context: background mention, supporting mention, primary mention.

Mogadishu Household Survey
Puntland Household Survey
Iraq Crisis Response Study

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Input: 5 does not have migration or geographic identifiers. The SILC contains geographic identifying variables, (at the NUTS1 level) but still lacks migration variables. The data set this study uses is the Labor Force Survey (LFS) since there is an adequate availability of both migration and geographic variables. The LFS is representative at the NUTS2 level which corresponds to 26 regions in Turkey. One caveat is that income in the LFS refers to only wage income from employment, 9 and is an insufficient measure of income that should be used for welfare measurement. For example, important sources of income such as social assistance, asset liquidation, or remittances are missing. Therefore, income in the LFS is imputed with a few assumptions using information from the SILC. The NUTS1 spatial effects of the SILC are a good proxy for NUTS2 welfare dynamics in the LFS which increases the accuracy of the imputation model. However, since the original sample frame of the LFS does not account for the recent influx of foreign migrants in Turkey, the labor market characteristics of recent migrants might not be representative of the actual SUTP population. Therefore, results of the imputation could be interpreted as upper bound estimates for recent migrants. More details of survey techniques used to complete this exercise are available in the Annex. Usage context: primary mention, supporting mention, background mention.

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Input: 1.8 1.7 57 63 All cereals 76.9 - - 2,994 All pulses 8.3 - - 385 Aggregate ration/month 46.7 - Source: WFP and World Bank Staff based on SESRE 2023. Note: *Net of sold ration = quantity*share of ration sold (we asked the share of ration sold in SESRE) Table E.6: Aggregate food expenditures Value/year (per capita) Value/year (per adult) Food expenditure (all) [A] 11,414 13,898 Food expenditure (WFP items only) [B] 2,226 2,741 Food expenditure (WFP in-kind) [C] 4,968 6,165 Food expenditure (WFP in-kind + cash) [D] 7,653 9,440 Source: WFP and World Bank Staff based on SESRE 2023. Average food expenditures from SESRE (13,898 birr) are higher than valued in-kind food aid reported by WFP (6,165 birr). Valuing quantities of WFP food aid with prices from SESRE suggests that if food aid quantities were received/reported, refugees’ food expenditure would be 9,440 birr slightly above the values we get in SESRE of 13,898 birr, but still low compared to hosts at 28,324 birr. The level of disaggregation of food items matters. The more disaggregated, the higher the food aggregates. To summarize, food rations received are lower than admin data suggests, regardless of the data source. Possible explanations for lower

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Input:
evidence is consistent with studies that used cross-section surveys, panel data and cross-country

Some of the work with panel data has also gone further in an effort to establish a causality link

Oswald (2007) use information on lottery winnings in the British Household Panel Survey

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Input: Table 2: Ethnic composition of IDPs, refugees, returnees in the North Ethnicity IDPs in Bamako (%) Refugees Niger (%) Refugees Mauritania (%) Returnees (%) Total I + R + R (%) Ethnic composition of the North (%) Songhai 75 21- 71 43 45 Kel Tamasheq 12 56 69 12 38 32 Arab 3- 28 4 11 3 Peulh 4 21- 6 4 7 Other 6 11 3 7 4 12 Total (%) 100 100 100 100 100 100 Total (n) 100 81 100 220 501 1, 268, 009 Source: Listening to Displaced People Survey, 2014 and 2009 Population and Housing Census. The ethnic composition of IDPs and returnees is almost identical. This is a reflection of the fact that 94 % of returnees were displaced within Mali. Only 6 % returned from outside the country. The reason why few returned refugees are in the returnee sub-sample is explained by their place of residence prior to the crisis: only 5 % of the refugees in Mauritania and Niger lived in Timbuktu town before their displacement; 2 % lived in Gao town and 1 % in Kidal town. The remaining 92 % lived in 27 different towns and villages in northern Mali, locations not covered by the survey. Usage context: background mention, primary mention, supporting mention.

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Input: A survey was carried out in the health sector (health centers) with the support of the World Bank in 2005, but has not been yet validated. In the rural development sector, where the first expenditure tracking survey between the decentralized center and services was to be carried out in 2005 on PEFA funds, the survey is yet to be carried out. It is critical that adequate management measures are gradually put in place to stop the current waste of resources. These measures include, inter alia, the accounting improvement of material, improvement of the inventory and delivery control, and especially a transparent planning of the deliveries, including, the posting of the received deliveries, their comparison with the planned deliveries and their certification by users within each service. It would also be desirable that in each ministry, an action plan is prepared for the implementation of these measures, on the basis of existing ones, and with target indicators as regards improvement of the arrival of the expenditure at intended destination. The social ministries could usefully open the way in this field, on the basis of some projection already carried out. Without a quantitative and qualitative improvement of the arrival of the expenditure at their final recipient, the increase in the budgetary appropriations to the priority sectors will hardly be translated into substantial concrete results on the ground. 29 It is difficult to make accurate forecasts for the implementation of certain programs or developments in economic parameters such as inflation or interest rate. Some immediate needs that were not foreseen during budget execution may appear during budget execution.

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Input: 5 The rest of this paper is organized as follows. Section 2 offers some background to the paper, providing context for Syrian refugees and their QOL in Jordan. Section 3 introduces a multidimensional quality-of-life indicator. Section 4 explains the methodology used in this paper, describing the data, identification strategy, and analysis method. Section 5 presents results of the statistical analysis, while section 6 presents conclusions and policy implications. 2. Syrian Refugees in Jordan The war in the Syrian Arab Republic has turned into a decade-long crisis, and refugees from Syria form the largest share of international displaced persons. About 5. 5 million Syrians are registered as refugees in Turkey (65 %), Lebanon (16 %), Jordan (12 %), Iraq (4 %), and other countries (3 %). Many Syrian refugees settle in urban and peri-urban regions in these host countries (World Bank 2020). The number of refugees living in camps has declined since 2017. Many refugees seem to prefer living outside the crowded camps and to escape the precarious living conditions and enjoy the freedom to live with relatives and friends and to find work. Usage context: background mention, supporting mention, primary mention.

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Input: Vintar et al. (forthcoming), for example, provide an example of how to use these data to understand the differential labor impacts of COVID-19 on refugees and non- refugees (see also the report “ Answering the Call: Forcibly Displaced During the Pandemic ” i). UNCHR ’ s proGres database includes phone numbers for refugee family heads that can be utilized as a sampling frame. However, data privacy concerns need to be addressed if the phone survey is conducted by a firm. A possible solution is sending text messages to selected respondents asking for permission to share phone numbers with a contractor. Comparisons between FDPs and host populations are also an essential exercise to conduct in the context of FDP poverty measurement. These comparisons are important for FDPs, host countries and international organizations given that resentment against FDPs is often fueled by a perception that FDPs receive special assistance that is not available to locals. Several surveys have now been conducted in Jordan, Lebanon, Iraq and a few Sub-Saharan African countries to compare the well-being of FDPs and their hosts. These comparisons, while important, are complex because host populations have full access to the labor and consumer markets and government services that are often not available to FDPs, whereas FDPs rely on aid from the international community that is not available to local residents. It is difficult to compare health services in camps, for example, to those provided to the host population by the government, or other social protection services such as unemployment insurance or paid leave that do not exist for FDPs. Again, these are new and largely under-researched issues among poverty specialists. Usage context: background mention, primary mention, supporting mention.

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Input: Most male principal applicants are one of a married couple with children whereas most female principal applicants are single care ‐ givers, single persons or living in non ‐ traditional family groups. While on average female principal applicant households are no more likely to be poor than male principal applicant ones, poverty rates for some types of households are higher when these households have a female principal applicant. Households that have formed because of the unpredictable dynamics of forced displacement, such as sibling households, unaccompanied children, and 6 Identification of the head of the case (as family groupings are referred to in the UNHCR ProGres database) is determined by who best represents the family for case management purposes. It is not assumed that the household will be best represented by a man; a woman or even a child can be a head of a case, depending on standard operating procedures. 7 Even when traditional household survey data are gathered at the individual level, the information is often collected from a single respondent. The respondent is usually the self ‐ identified ‘ most knowledgeable ’ household member, which overwhelmingly corresponds to the ‘ head ’ of the household. In the case of a household survey that solicits information on ‘ headship ’, this information is gathered often through the question: “ Who is the head of this household? ” Usage context: supporting mention, background mention, primary mention.

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Input: The household head interviews also provided an opportunity to gather useful household-level information (including assets, housing characteristics, and household head characteristics) to be used as control variables in our analysis. The baseline survey was conducted before participants were informed of the outcome of the randomization, and the midline survey was conducted one year after the baseline survey, one month after completion of the first round of training and before the start of the second round. The results in this paper are based on a panel data set that includes data from the baseline and midline surveys as well as administrative and monitoring data from the program implementation team. Note that although the midline data collection occurred just one month after the completion of the intervention, the intervention itself includes 6 months of post-training follow-up; hence the midline survey captures outcomes of the first cohort 7 months after they exited the classroom-based training. This timing was necessary to prevent too long of a delay between cohorts; the second cohort of trainees started immediately after the midline survey was completed. Future analysis using endline data will examine the trends in outcomes of both groups after Round 1 completion, but will not involve comparison against a pure control group of non-participants. 3. 2. Sample and attrition Following the communications and outreach campaigns in each of the nine target communities, during which 2, 106 young women were originally recruited to be a part of the EPAG program, 8 a randomized 8 The original recruitment effort fell short of the target of enrolling 2500 participants. Hence, before the second round of training, another recruitment effort was launched and an additional 617 girls were enrolled. These girls are not included in the impact evaluation since they were not subject to the initial random assignment. 7 Usage context: background mention, primary mention, supporting mention.

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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

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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

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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

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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

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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

production data for 17 large-scale gold mines

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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

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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

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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

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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

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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

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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).

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

DHS data
household data from the GLSS
GLSS

surveys of men
household data from the GLSS

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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

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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)

Platform for Urban Management and Analysis

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