ai4data/datause-dataset-rechunked huggingface dataset:
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
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
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
_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
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
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
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
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
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
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
**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).
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
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
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
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
**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
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
**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
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
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