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:**

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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

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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]

flood hazard maps
spatial socioeconomic data
high-resolution flood hazard data

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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

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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

surveys of users of project-financed infrastructure

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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

World Bank’s Global Monitoring Database
Living Standards Measurement Survey

household surveys
Bank household surveys

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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

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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

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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

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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

WCMC wetlands map
‘Lagoon’ from ArcWorld
ArcWorld

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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

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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

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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

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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

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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

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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

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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.

flood protection databases
flood hazard maps

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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

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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

Fathom global flood maps
Global Tide and Surge Reanalysis (GTSR)

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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

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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

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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

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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

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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

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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

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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

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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

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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,

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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

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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~~

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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

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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

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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

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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

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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

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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

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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,**

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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

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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

historical daily grid of rainfall
data from BASIX

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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

Internationally comparable Programme for International Student Assessment

PISA index for economic, social and cultural status

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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

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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

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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

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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

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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

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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

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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) =

crop data, including production quantities, amount sold, and sale receipts from crops

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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

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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

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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

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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

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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

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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

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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

flood exposure maps
population flood exposure estimates
population exposure maps

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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

high-resolution flood and population data

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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.

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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

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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

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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

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