ai4data/datause-dataset-rechunked huggingface dataset:
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
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
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) =
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
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
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
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
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
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
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
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
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.
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
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
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
should direct short- and long-term assistance to both the displaced and host communities. This can help reduce real and perceived inequalities and prevent host communities from forming negative attitudes about newly arriving displaced persons. Phase II of Jya Mbere continues the area-based approach of Phase I, providing multi-sectoral support to respond to the impacts of forced displacement, covering refugees and host communities. The mid-term survey for Phase I indicated positive results from this approach for social relations between refugees and local residents, mirroring results from independent impact evaluations of the Development Response to Displacement Impacts Project (DRDIP) in Ethiopia (P152822) and Kenya (P161067). 47. **By creating new challenges and new opportunities, the presence of refugees transforms the environment** **in which host communities are pursuing their own development efforts.** This requires an approach that supports hosting areas rather than focusing on refugees alone. Investments are needed to mitigate the downside of hosting refugees – overcrowded basic services, environmental degradation, competition over natural resources and, sometimes, over employment opportunities – while taking advantage of the benefits their presence may generate through their human capital, financial resources and the humanitarian and development assistance they can Page 13
place for the proposed project implementation). 51. **The PIU to be established at the MEP is expected to undertake the FM aspects of the proposed Project.** These encompass the following main tasks: (i) budget formulation and monitoring; (ii) cash flow management (including processing payments and submitting loan withdrawal applications to the Bank); (iii) maintenance of accounting records, including an inventory of fixed assets for the Project, (iv) administration of adequate information systems; (v) preparation of in-year and year-end financial reports; and (vi) contracting the external audit. The FM arrangements for the project will rely on country systems for budgeting, accounting and treasury, which are considered adequate [30] will be used as the project’s FM arrangements. Loan proceeds will be disbursed to an account in the Central Bank of Costa Rica named General Fund. Unaudited semi-annual financial statements will be submitted 45 days after the end of each calendar semester. Annual financial statements which will be audited under terms of reference and by an external firm, both acceptable to the World Bank, will be produced for the project. Basic arrangements to ensure control, recording, and reporting are further described in Annex 1. 52. **Procurement** . Procurement for the Project will be
take-up the following year. There is some evidence for this happening in developed markets; for example, Kunreuther, Sanderson, and Vetschera (1985) note that purchases of flood and earthquake insurance in the United States spike after a recent event, even if people were not insurance customers before. There are a number of theories that could explain this behavior. First, recent experiences with rainfall could change subjects’ beliefs about the probability of a rainfall shock the following year (this is proposed as “recency bias”in Karlan et al. [2014]). If there is actual autocorrelation of rainfall events or if the subject has limited knowledge about the effects of rainfall shocks, people may update their beliefs about shocks and therefore have more desire for insurance the following year. Alternatively, recently experiencing a rainfall shock could make shocks more salient, increasing the chance they will buy insurance the following year. Also, rainfall shocks may affect the wealth of the farmers. If farmers become poorer because of bad rainfall, CRRA utility would suggest that they would be even more risk averse the next year as a second shock would cause greater disutility. I start by examining whether there is actual autocorrelation in the rainfall data. To
will include enhancing its operational framework, providing staff training on risk management and financial advisory services, and equipping CPEC with digital tools, building on multi-year technical assistance from the World Bank and other donors, to leverage CPECs proven capabilities and streamline advisory services to the C4N beneficiaries as well as those that will benefit from the FISs. **Sub-component 1.3: Strengthening the Social Registry (total IDA US$2 Million equivalent, including WHR US$0.3** **Million)** 38. **This sub-component will finance the scale-up of the SR among all Djiboutians, refugees and host communities,** **toward full coverage which will be a critical foundation for coordinating support across ministries and development** **partners.** The social registry will play a crucial role in coordinating existing funding and mobilizing additional resources to 22 Malaeb, B.; Duplantier, A., Maarraoui, G., Fluet, E. (2023). Towards a More Equitable Development: Constraints and Opportunities of Women in Djibouti. The World Bank, Washington Page 11
and concludes the paper. **2. Georeferenced Database Construction** We combine data from BMD, IMD and IBTrACS to document all recorded cyclonic storms in the Indian Ocean region from 1877 to 2016. We construct a panel database; the component for each storm includes a unique identification number; year and month of occurrence [1] ; maximum wind speed (kt); radial distance (km) from storm center to zone of maximum wind speed; IMD storm classification derived from wind speed; time indices for successive observation points [2] ; and latitude/longitude for each point. We use ArcGIS to construct individual storm-track polylines by interpolation from time indexed latitude/longitude observations for each storm. Then we determine maximum-impact 1 The first month for storms that occur in two months. 2 Incommensurate day/time tracking in the three databases (BMD, IMD, IBTrACS) could be addressed in a more complete exercise. For our purposes, identifying successive observations by cardinal units [1,2,3, ...] is sufficient for constructing GIS polylines that trace individual storm tracks. 4