ai4data/datause-dataset-rechunked huggingface dataset:
refugee populations are better documented and ascertained so that they can benefit from a wider range of integrated services. Interoperability with other databases will also enhance responsiveness in the event of a natural disaster. 39. **In addition to reinforcing the social registry, the sub-component will support enhancing the operational capacity** **of existing social counters (** _**guichets sociaux**_ **) in urban areas and regions.** These social counters will be upgraded to reach a greater number of individuals, enabling the registration of additional households, as well as the regular updating of data. The enhanced social counters will be equipped to handle grievances, ensuring timely and effective responses. These centers will also serve as key points for connecting refugees with essential services, facilitating their inclusion in national programs for social protection and economic empowerment. The centers will evolve into fully integrated one-stop service hubs, serving as entry points for basic services, beneficiary monitoring and grievances management. By implementing these measures, the project aims to create a robust and dynamic social registry that will not only address current needs but also adapt to future challenges. **Component 2: Access to Socio-Economic Infrastructure and Development of Economic Opportunities (** _**total IDA**_ _**US$14 Million equivalent, including WHR
(1.805) (0.039) (0.054) (0.029) (0.021) (0.029) (0.021) Active 0.007 0.001 0.050** 0.034** -0.032 0.054** -0.023 (1.012) (0.026) (0.024) (0.017) (0.021) (0.026) (0.022) Observations 9,790 9,790 12,226 12,216 12,227 12,227 12,227 R-squared 0.128 0.180 0.453 0.148 0.208 0.171 0.095 mean of dep var 0.407 14.84 0.565 0.652 0.151 0.732 11.6 _Note:_ Robust standard errors clustered at the DHS cluster level in parentheses. All regressions control for year and district fixed effects, urban dummy, age, and years of education. Active is active status of mine in the survey year. *** p<0.01, **p<0.05, *p<0.1. OLS = ordinary least squares. Overall, we estimated in table 8 that a household’s access to electricity decreased when a mine became active. This finding is surprising if we assume that electricity infrastructure is seldom destroyed, so that with time, access has generally been increasing. [13] Figure A1 (Annex) further decomposes the effect, and panel Aa of the figure confirms that the coefficient for electricity access is negative using the treatment distance 20 km. However, with a treatment distance of 10 km, the effect is marginally positive and insignificant. If we use a treatment distance of 50 km, we no longer see a significant effect. In panel Ab, the
exposure and awareness of flood risk in England and Wales. Disasters. Vol. 36(3), pp.477-494 Freire, Sergio; MacManus, Kytt; Pesaresi, Martino; Doxsey-Whitfield, Erin; Mills, Jane (2016): Development of new open and free multi-temporal global population grids at 250 m resolution. Geospatial Data in a Changing World; Association of Geographic Information Laboratories in Europe (AGILE). AGILE 2016. Daniel, V. E., R. J. G. M. Florax, and P. Rietveld. 2009. “Flooding Risk and Housing Values: An Economic Assessment of Environmental Hazard.” Ecological Economics 69 (2): 355–65. Durand-Lasserve, A., H. Selod, and M. Durand-Lasserve. 2013. “A Systemic Analysis of Land Markets and Land Institutions in West African Cities: Rules and Practices—The Case of Bamako, Mali.” Policy Research Working Paper 6687, World Bank, Washington, DC. [Hallegatte, S., A. Vogt-Schilb, J. Rozenberg, M. Bangalore, C. Beaudet (2020). "From Poverty to Disaster](https://ideas.repec.org/a/spr/ediscc/v4y2020i1d10.1007_s41885-020-00060-5.html) [and Back: a Review of the Literature," Economics of Disasters and Climate Change, Springer, vol.](https://ideas.repec.org/a/spr/ediscc/v4y2020i1d10.1007_s41885-020-00060-5.html) 4(1), pages 223-247 Hallegatte, S., C. Green, R. Nicholls, J. Corfee-Morlot (2013). Future flood losses in major coastal cities. Nature Climate Change. Vol. 3, 802–806 25
The modeling of all coastal wetlands by McFadden et al. (2007) suggests that global wetland losses are 32% and 44% by the 2080s for a 50 cm and 1 m rise in sea level between 1990 and 2100 accounting for human impacts, such as dike construction or wetland nourishment. The estimates presented by McFadden at al. (2007) are not delineated by types of wetlands or by regions of the world. As for McFadden et al. (2007), the estimates of Nicholls (2004) and Nicholls et al. (1999) are also not disaggregated by types of wetlands. Furthermore, while Nicholls (2004) asserts the largest loss of coastal wetlands to be expected around the Atlantic coast of Central and North America, the small Caribbean islands, and most particularly the Mediterranean and the Baltic, the paper does not present estimates of lost wetlands by regions of the world. It should also be noted that neither of these analyses present estimates of the economic values, which may be associated to these lost wetland areas around the world. The valuation studies by Tol (2007) and Anthoff et al. (2010) are also based on wetland losses derived from the Global Vulnerability Analysis (Hoozemans et al. 1993). Wetland value
needed.** The project will provide targeted support to strengthen M&E capacity within MASS and ADDS. Where feasible, the project will finance consultants to assist MASS and ADDS in developing a detailed M&E and reporting system plan. In addition, consultants will provide on-the-job training for M&E specialists across MASS, ADDS, and other implementing agencies, as well as any other support required to establish and maintain an effective M&E system. 64. **The MASS and ADDS have demonstrated capacity to undertake beneficiary assessments (BA) and technical** **audits (TA) to inform implementation and obtain stakeholder and beneficiary feedback as good practice** . Two BAs and TAs are anticipated to determine feedback and inform the pre and post MTR implementation. The BAs will provide feedback on satisfaction levels among key beneficiaries, identify challenges in implementation and make recommendations for improvements. The TAs which have been undertaken to ascertain delivery of cash transfers, will now cover a broader range of interventions including the financial services and SBCCs. **C. Disbursement Arrangements** 65. **Given the high-risk environment, the report-based disbursement will not be applicable.** Therefore, upon project effectiveness, transaction-based disbursements will be used. An initial advance up to the ceiling of the Designated Account (DA) will be made
(Eds.) _Climate Change 2007: The Physical_ _Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the_ _Intergovernmental Panel on Climate Change_ [Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Krabill, W, Hanna E., Huybrechts, P., Abdalati, W., Cappelen, J., Csatho, B., Frederick, E., Manizade, S., Martin, C., Sonntag, J., Swift, R., Thomas, R., and J. Yunge. 2004. Greenland ice sheet: increased coastal thinning. _Geophysical Research Letters_, 31: L24402 Larson, J.S., Adamus, P.R. and E.J. Clairain Jr. 1989. _Functional Assessment of Freshwater_ _Wetlands: A Manual and Training Outline_ . Glaud, Switzerland: WWF Publication 89-6: 62pp. Lehner, B. and P. Döll. 2004. Development and validation of a global database of lakes, reservoirs and wetlands. _Journal of Hydrology_, 296(1-4), 1-22 Maslanik, J. A., C. Fowler, J. Stroeve, S. Drobot, J. Zwally, D. Yi, and W. Emery, 2007: A younger, thinner Arctic ice cover: Increased potential for rapid, extensive sea-ice loss _Geophysical_ _Research Letters_ **34** : L24501 McFadden, L., Spencer,T. and R.J. Nicholls, 2007. Broad-scale modelling of coastal wetlands: What is required? _Hydrobiologia_, 577, 5-15. McLeod. K.L., Lubchenco, J., Palumbi, S.R. and A.A. Rosenberg. 2005. _Scientific Consensus_ _Statement on Marine Ecosystem-Based Management. The Communication Partnership for_ _Science
Strzepek K & McCluskey A, 2006. District level hydroclimatic time series and scenario analysis to assess the impacts of climate change on regional water resources and agriculture in Africa. CEEPA Discussion Paper No 13, Centre for Environmental Economics and Policy in Africa, University of Pretoria. USGS (US Geological Survey), 2004. Global 30 Arc Second Elevation Data, USGS National Mapping Division, EROS Data Centre. (These data files are downloadable from http://edcdaac.usgs.gov/gtopo30/gtopo30.asp) Weng F & Grody N, 1998. Physical retrieval of land surface temperature using the Special Sensor Microwave Imager. _Journal of Geophysical Research_ 103: 8839–8848. World Bank, 2003. Africa rainfall and temperature evaluation system (ARTES). World Bank, Washington DC. 12
its zone of maximum wind speed. We employ a standard IMD storm classification based on maximum wind speed intervals in kt: (Cyclonic Storm (CS) [34-47 kt]; Severe Cyclonic Storm (SCS) [48-63]; Very Severe Cyclonic Storm (VSCS) [64-119] and Super Cyclonic Storm (SuCS) [120+]. We have excluded all storms rated as tropical depressions because their maximum wind speeds are below 34 kt. The third distinctive feature of our exercise is use of the constructed database to explore temporal and spatial patterns in cyclone impacts that can provide the context for future household level research on adaptation by coastal communities. Our analysis is aggregative in this paper, but the source database can provide high-spatial-resolution cyclone incidence and impact measures for households and communities in both coastal and interior locations. We should introduce a cautionary note at the outset. During the past 140 years, technical support for cyclone tracking has evolved from land-based telegraphy in the 19th century, through 3
and age of the 2023 data for victims is not yet available. However, according to the Child Protection Sub-cluster, the Child Protection Working Group of the Diffa region recorded 18 child victims of ED in 2022, the majority of whom (74%) are girls who went to look for firewood. 5 Departments of: Torodi, Say,Téra, Tillabéry, Gotheye, Bankilaré et, Ouallam (région de Tillabéry) et Diffa, Bosso, Mainé et N'Guingmi (region de Diffa) 6 According to protection monitoring data (P21) 1st semester 2023. 7 [Food security situation, june 2023](https://drive.google.com/file/d/1FVzLNdVSeHdrZ0iNx0YUf2LNiWuO5gBS/view?usp=sharing)
replace deteriorating reservoirs, extend the water distribution network, or enhance water storage and management. This would lead to increased risks of water shortages and contamination, endangering the health of the refugees. Substandard waste and sanitary management would also pose significant health hazards to the camp residents. Access to quality obstetric care and services as well as essential medicines will also be compromised. 1 _UN agencies use different points of reference for the population living in the Tindouf refugee camps. For example, UNHCR uses the number 90,000 to refer to the_ _‘most vulnerable refugees’ although recognizing that assistance needs are much higher. The Sahrawi Response Plan launched in November by the UN resident_ _coordinator in Algeria uses the higher 173,600 figure to ensure humanitarian assistance is comprehensive._ ### **EGYPT** **Health** As medical needs continue to rise among new arrivals from Sudan, public health services are overwhelmed, and many individuals face high out-of-pocket costs. Underfunding means UNHCR will not be able to support some 16,100 refugee patients, including those chronic diseases who depend on monthly medications. Without this support, many lives are at risk. **Education** Currently, around 54 per cent of all school-aged arriving from Sudan are out of school. Education grants
These flood risk categories are defined in line with an approximation of the risk to the lives of affected people. Up to 0.15 meter inundation depth, no significant risk to life is expected. Up to 0.5 meter, some risk to life must be expected, especially for vulnerable groups such as children and the disabled. Up to 1.5 meters, a significant share of the affected population could face risk to life, especially if flood waters have a current. Above 1.5 meters, most affected people could face substantial risk to life without rescue measures. Through this process, each 90 by 90 meter cell of a country will be assigned one of the five risk categories (e.g. a pixel that has an estimated inundation depth of 5 cm is classified as low risk, while a pixel with depth 4.3 meters is classified as very high risk). This is repeated for the world’s landmass of 510 million square kilometers, which implies the processing of 63 billion pixels. **3.** **Assign flood risk categories to population headcounts at the pixel level and aggregate to the** **administrative unit:** As the flood hazard and population density maps are converted into the same spatial resolution, each population map cell
discount rates have also been provided as a measure of the sensitivity of the analysis. 46 This corresponds to the average village population in similar areas according to the International Organization for Migration (IOM). This information can be accessed at Village Assessment Survey County Profiles. [https://iomsouthsudan.org/tracking/sites/default/publicfiles/documents/Lakes.pdf](https://iomsouthsudan.org/tracking/sites/default/publicfiles/documents/Lakes.pdf) _._ 47 Burden of Road Injuries in Sub-Saharan African _,_ [htp://pubdocs.worldbank.org/en/356861434469785833/Road-Safety-Burden-of-Injuries-in-Africa.pdf](http://pubdocs.worldbank.org/en/356861434469785833/Road-Safety-Burden-of-Injuries-in-Africa.pdf) _._ Page 26
_Figure 14. Economic value at risk, computed as exposure headcount multiplied by subnational income_ _per capita. Note: no subnational income data are available for several countries, including China._ **Exposure headcounts by income groups.** To address the bias that high-income areas have higher flood exposure in monetary terms, we consider flood exposure headcount disaggregated by national income classifications. The results, presented in Figure 15, show that 710 million people (or 48 percent) of the world’s flood exposed population live in lower- or lower middle-income countries. About 159 million (11 percent) of flood exposed people live in high-income countries. Considering that the flood exposed population in high-income countries is more likely to benefit from flood protection systems, social post-disaster assistance, and other risk management support, these figures highlight that monetary exposure estimates (including GDP) offer a distorted account of the distribution of global flood risks. 0 500 1,000 1,500 Millions _Figure 15. Number of people exposed to significant flood risk, disaggregated by national income level_ _classification_ 18
of the GoR’s strategy – together with support from humanitarian and development partners – research shows that the impact of refugees in Rwanda on basic services, the environment and livelihood can be mitigated. Indeed, the refugee presence is generally associated with improved local economic conditions and access to services, without creating major social tensions. [2] 2. **The government’s strategic goal for refugee management is to promote self-reliance, however, major gaps** **remain in achieving this aim.** Data from the 2022 national census (which included a refugee module for the first time) and from the first round of a World Bank-led survey on refugee self-reliance showed that refugees generally enjoy good access to basic services such as education, health and water, but remain well short of self-reliance with respect to employment and income. [3] High poverty rates, lack of economic opportunity and limited access to finance in the refugee-hosting districts (RHDs) constrain employment and income-generating prospects for refugees and host communities alike. Building on the success of the ongoing Phase I of the World Bank-financed Socio-economic Inclusion of Refugees and Host Communities in Rwanda Project (P164130) (known in Kinyarwanda as “Jya Mbere” or “move forward”), Phase II will support self-reliance for refugees
**The World Bank** Costa Rica Results in Education (CORE) (P181174) **D. Results Chain** **Assumptions** **Figure 3: Results Chain** i. Political and Governmental Support: The government of Costa Rica will continue to prioritize education. ii. Stability of the Project Implementation Unit: The Project Implementation Unit will remain stable, with consistent leadership and staffing levels, and will be able to effectively coordinate with the IDB, internal and external stakeholders. iii. Community and Stakeholder Engagement: There will be buy-in from key stakeholders, including educators, students, parents, and the community at large, for the education technology reforms. **E. Rationale for Bank Involvement and Role of Partners** 39. **The Bank has a long-standing partnership with the Government of Costa Rica on education and can leverage** **global experience in the implementation of education sector reforms.** This Project builds on and complements prior Bank support to Costa Rica on education, including the Costa Rica Higher Education Improvement Project (P123146, Loan 8194CR) and on governance under the Costa Rica Fiscal Management Improvement Project (P172352, Loan 9075-CR). 40. **Collaboration with development partners will be key for the preparation and implementation of this Project.** The Project is designed in parallel to an IDB financed project. Both projects are self-standing and
an economically viable area. Results from various studies such as the 23 Zambia 2022 Census of Population and Housing, Central Statistical Office Zambia, 2023. 24 One Meheba Local Area Plan, Planning Survey and Issues Report, GRZ, 2023. 25 One Meheba Local Area Plan, Planning Survey and Issues Report, GRZ, 2023. 26 “Many girls choose not to attend classes at certain times due to the lack of appropriate washing and hygiene facilities,” School headmaster, Kalumbila District, February 2024. Page 16
strong spillover effects. The lack of visible spillover effects casts doubt on the theory that repurchases are being driven by increased trust in the insurance company or learning about insurance payouts. Notably, this result stands in contrast to recent results that do document spillover effects of insurance payouts (Cole, Stein, and Tobacman 2014; Karlan et al. 2014). Direct Effects of Payouts on Wealth and Liquidity The previous two sections discount the possibility that trust, learning, or weather effects are driving the result that receiving an insurance payout is correlated with purchasing insurance the following year. This points to the actual reception of money from the insurance company as being the driving force behind greater take-up. The most natural explanation for this phenomenon would be that receiving an insurance payout could directly affect choices the next year due to its effects on wealth and liquidity. For instance, if insurance is a normal good, then increased wealth would result in greater insurance demand. [18] Although the BASIX data set does not offer the opportunity to test the direct effects of a cash payment separately from an insurance payout, there are a number of reasons why it is unlikely that wealth or liquidity
data on slum location to examine the distribution of exposure across poor and non-poor locations. While prior studies have examined flood risk in Vietnam, this paper provides two main contributions. First, we develop new high-resolution flood hazard datasets, which incorporate both riverine and coastal flooding and consider climate change. [1] When examining flood exposure, it is important to get as local as possible as impacts can vary widely across space - for instance, impacts can be different from one city block to the next (Patankar 2015). This 1 Prior use hazard data at a 1 km resolution and are restricted to a single district or city within Vietnam (Chinh et al. 2017; Apel et al. 2016). We develop new high-resolution flood hazard datasets on a 90 m × 90 m grid.
not owned, significant and quantitatively large investment disincentives persist and cause productivity losses of considerable magnitude. This makes it important to explore other ways of bringing investment levels on such land closer to the social optimum. To explore this, our survey asked households who occupied land under usufruct about their willingness to pay to acquire full ownership rights. Results, as reported in table 7, suggest that 40% of 2,804 owners were willing to pay for about 37% of the 4,478 occupied parcels overall or 43% of the 1,519 parcels under freehold or _mailo_ . The median willingness to pay, US$ 215/acre for customary and US$ 269 per acre for _mailo_ or freehold land is surprisingly large, both if compared to owners’ median self-assessed value of US$ 403/acre. It is also high in view of the fact that, at least in the case of _mailo_ or freehold, the economic value of landlords’ residual claims to a perpetual ground rent of about US$ 0.6 annually is minuscule. Although part of the stated willingness to pay could have its origin in non-economic values of land ownership, the fact that a large number of households are willing to spend large amounts of 19 As
United Nations Development Programme (UNDP) Needs Assessment, [27] UNHCR Socioeconomic Survey, [28] the UNHCR Gap Analysis, [29] and the outcome of a stakeholder consultation process revealed that rehabilitation of settlement roads is the priority development need across all communities. The project will improve the 38 km of rural road from the Meheba junction on the T5 Solwezi-Mwinilunga Road to the Mwafwe River located at the southern border of the settlement. Construction will be done to a climate-resilient standard, to withstand damage from flash flooding, including, for example, adopting a robust drainage and camber design and ensuring their periodic maintenance. The approach is in line with Zambia’s Climate Adaptation Plan which seeks to promote the application of climate-smart codes for roads development nationally. It will also provide a bridge over the Mwafwe River to facilitate access to communities in the Matebo Ward to the immediate south of the settlement [30] and improve their resilience to climate change impacts such as flash floods. An assessment will ensure that the bridge is engineered to withstand flooding and erosion risk. Rural road improvement will also contribute significantly to creating links—increasing the opportunity to access goods and services located in nearby Solwezi and other markets,
Economics of Disasters and Climate Change paper contributes to the growing literature in economics on the assessment of local and disaggregated disaster impacts (e.g. Del Valle et al. 2018 using wind speed), and is the first to our knowledge examining flood risk at this scale in a developing country. Second, we analyze how flood exposure differs based on socioeconomic dimensions, in this case poverty, at the country and city-level. In both cases, we examine how flood exposure and poverty differs spatially across the country (at the district level) but also within HCMC (by identifying slums). The combination of these two datasets on hazard and poverty - typically kept separate in the literature – is another main contribution of this paper. The consideration of socioeconomic characteristics and the focus on the poor is an important one as not all segments of the population are equally exposed and vulnerable to floods. In some cases, people living in risky places may be richer than the average population: for instance, urban residents are on average wealthier than those living in rural areas (World Bank 2009). At a more local scale and especially within cities, land and housing markets often push poorer people to settle