ai4data/datause-dataset-rechunked huggingface dataset:
Road data from the transport sector review were used to construct a road condition index for each of the 89 communes in the project area. The index combines pavement condition scores, bridge load ratings, and seasonal accessibility ratings into a composite infrastructure access score. Communes ranked in the bottom tertile of the index were given priority consideration for infrastructure investments under Component 2, subject to confirmation through community consultation that road rehabilitation was among the top three priorities identified by community members.
The remote sensing inputs comprise  weather data, such as rain and temperature, as well as soil and terrain data. These sources  are then used by GeoSFM to model basins across Indonesia and the stream flow in each of  these.

from ENLACE, a census-based standardized test that primary and secondary school

of the Mexican labor force survey (ENOE) applied to individuals aged 18 to 20 years old
Page 13 of 51 Figure 8: Temporary employment by gender. (Mid-1990s / Mid-2010s) Source: Own calculations based on Household surveys 4. 1. 2 Profile of Non-Standard Employment The next objective of this work is to investigate possible changes in the profile of non-standard employment, usually associated with lower productivity and greater vulnerability. The analysis of the employment profile was made based on access to social security benefits, education level, labor income and the task content performed by the workers. From the point of view of social security, we find that NSE shows a higher prevalence of informality compared with SE. For instance, the average prevalence of informality for our set of countries among NSE in the ending point of the study is 40 % while the prevalence among SE is 20 %. In this sense, a rise in the prevalence of NSE could be associated to a big set of workers without access to social security benefits. From a dynamic perspective, there is no a common trend across countries regarding the prevalence of informality among NSE workers (Figure 9). Indeed, several countries (Uruguay, Brazil, Chile, and Peru) registered a small decrease in the prevalence of informality among NSE but there is another set of countries for which the opposite is observed (Mexico, El Salvador, Bolivia and Argentina).
7 educational institutions, suspensions on in-person meetings and a dusk-to-dawn curfew. The lockdown was subsequently lifted in May 2021. Refugees living in Kenya were subject to the same containment measures as nationals, although refugee camps were in addition closed off from the outside in the very beginning of the pandemic. When the nation-wide lockdown was stepwise lifted in the fall of 2020, permissions to enter the camp for outsiders continued to be strongly limited to protect the refugees living in the densely populated camp settings. Figure 1: COVID-19 cases and RRPS timeline in Kenya Source: Ritchie, et al (2020). Data downloaded on June 14, 2021, here. 3. Data and methodology 3. 1 Survey design The Kenya COVID-19 Rapid-Response Phone Survey (RRPS) is structured as a five-waves bi- monthly panel survey that targets nationals, refugees, and the Shona community. 9 The first wave of interviews was administered in May-June 2020 and the last available wave in April- June 2021. The questionnaires capture extensive demographic and socioeconomic data with modules on employment, income, coping strategies, food security, access to education and health services, child labor, subjective well-being, knowledge of COVID-19, changes in behavior in response to the pandemic, and perceptions of the government ’ s response.
10 Last, specific adjustments are made in the case of Germany and the Republic of Korea. For Germany, bilateral data are available only by nationality. However, these data fail to take adequate account of the large number of ethnic Germans who arrived from other countries between 1944 and 1950 (mainly expellees) and those who arrived after1950 (mainly resettlers). Material from the German 2005 micro-census was therefore used to supplement the data for Germany (see appendix 3). In the case of Korea, data by nationality are readily available for each census round. However, these data fail to account for the large numbers of migrants from the People ‘ s Democratic Republic of Korea living in the Republic of Korea. Since the United Nations Trends in International Migrant Stock details the total migrant stock in the Republic of Korea by the country of birth definition and because citizenship is rarely granted to people from outside, it is simply assumed that the nationality data were comparable to the foreign-born definition. The nationality total was then subtracted from the UN total and the remaining migrants were assigned to the People ‘ s Democratic Republic of Korea.
over 15,000 refugees relocated from the Tigray camps to Alemwach, and an additional 7,000 refugees were resettled in November 2022 following the cessation of hostilities (UNHCR, 2022). Before the conflict, 64 percent of all Eritrean refugees were hosted in camps in Tigray and 36 percent in camps in Afar (UNHCR, 2020b). Refugees going to either Tigray or Afar are distinct culturally and linguistically. Eritrean refugees in Afar are Muslim and speak Afar, as do the Ethiopian hosts in Afar. Many Eritrean refugees in Tigray—and thus the ones who moved to Amhara during the conflict—are Orthodox Christians and speak Tigrinya. The SESRE sample, therefore, includes in-camp Eritrean refugees in two regions: Afar (216 households) and Amhara (216 households). This means that Eritrean refugees in Amhara, representing half of the Eritrean refugee sample, were displaced from Tigray only a few months before the SESRE was implemented, thus have had less time to integrate into the surrounding community and labor market. Among Eritreans in Afar and Amhara, the share working is 43 percent and 9 percent, respectively. Among workers, Eritreans in Amhara are three times as likely to work for NGOs or RRS, and very few work outside the camp. Box 3.1: Eritrean
In terms of statistically insignificant effects, Block et al. (2004) examine the effect of Indonesia's drought and financial crisis of 1997-98 using time-age-cohort decomposition analyses employing high-frequency nutrition data.

With regards to social shocks, in Rwanda, Akresh et al. (2011) find that an additional month of exposure to civil war lowers child HAZ by 0.11 SD. Using qualitative data, the authors argue that this effect is due to increased theft of livestock or crops and exposure to water- and vector-borne diseases, with internal displacement driving this exposure to disease.

7 Measurement error in consumption data could be behind this.

We use weather data taken from the _Terrestrial Air Temperature and Precipitation Version 4.01_ compiled by

We use recent global sub-national aggregated output data (Kummu, Taka and Guillaume 2018a) derived from
Figure 1 ‐ Number of Forcibly Displaced Persons (1951 ‐ 2015) Source: Constructed from UNHCR population data (http: / / popstats. unhcr. org / en / time_series). Note: 2015 data are mid ‐ year and lower than end of year data. 5 http: / / www. unhcr. org / en ‐ us / figures ‐ at ‐ a ‐ glance. html. 0 10000000 20000000 30000000 40000000 50000000 60000000 70000000 1951 1953 1955 1957 1959 1961 1963 1965 1967 1969 1971 1973 1975 1977 1979 1981 1983 1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015
Our evaluation explicitly investigated these spillovers by including household-level indicators such as food security and attitudes of the household head toward gender norms. Our results show strong impacts on economic outcomes, including large and statistically significant increases in employment and earnings of EPAG participants. We show mixed results on empowerment- related outcomes, and very little evidence of spillovers on non-participants. Self-assessed measures of self-confidence show huge gains, as does ownership and control over monetary resources such as savings. The remainder of the paper is organized as follows: Section 2 describes the EPAG project including some of its innovative design features and implementation details. Section 3 reviews the methodology of the evaluation and Section 4 presents results on the three groups of outcomes discussed above: economic, empowerment, and spillovers. Section 5 includes a short discussion of cost-effectiveness. Section 6 presents a series of robustness checks and Section 7 concludes with a discussion of next steps and policy implications. 2. The EPAG Project The EPAG project is part of a larger Adolescent Girls Initiative (AGI) administered by the World Bank with support from the Nike Foundation and the Governments of Australia, the United Kingdom, Norway, Denmark, and Sweden. Launched in Washington DC in October 2008, the AGI was spearheaded by President Ellen Johnson Sirleaf, who signed on to undertake the initiative ’ s first pilot project in Liberia. The Liberian pilot was launched in March 2010 and has served as a role model to seven subsequent pilot projects in Rwanda, South Sudan, Nepal, Afghanistan, Haiti, Jordan, and Lao PDR. Under the global AGI, young women and adolescent girls are given a package of skills training and complementary services in order to facilitate their successful transition to employment. In the case of EPAG, the intervention consisted of a six month phase of classroom-based training, followed by a six 4
This paper ’ s scope of analysis includes the country as a whole using a nationally representative survey. While regional case studies may reveal salient stresses on public services and job displacement, nationally, there is no significant impact. Over the period of 2009 to 2013, the poverty rates of host community households have stayed relatively stable near the Syrian border; despite the high poverty rates experienced among the recent migrants. By country of origin, the displacement of Syrians is one of the largest in recent history. As a result of the civil war that began in 2011, Syrians started to leave their homes and look for safety in neighboring countries across the region. By November 2015, about 4. 3 million Syrians were seeking refuge in primarily Turkey, Lebanon, Jordan, Iraq, and the Arab Republic of Egypt. 3 The only other time in the last half century that the world experienced a larger group of refugees from a single country is the case of Afghan refugees during the 1980s to 1990s. Refugee displacements of this size are rare. Consequently, they are not well studied and their impacts are not well understood. Moreover, the case of Afghan refugees in Pakistan is different, since they were stigmatized to a larger extent, which limited their movement in Pakistan.
are located. Seven Zones host refugees; this study calls them hosting Zones. North Gondar Zone hosts Eritreans in Alemwach camp. Awsi (Zone 1) hosts Eritreans in Asayita camp. Liben Zone hosts Somali refugees in Bokolmanyo, Buramino, Hilaweyn, Kobe, and Melkadida camp. Fafan Zone hosts Somali refugees in Aw-barre, Kebribeyah, and Sheder camp. Agnuak Zone hosts refugees from South Sudan in Pinyudo 1 and 2, Jewi and Okugo camp. Itang Special Zone hosts refugees from South Sudan in Tierkidi, Kule, and Nguenyyiel. Assesa hosts refugees from South Sudan in Bambasi, Sherkole, and Tsore. Probability of being employed 1 .8 .6 .4 Female 50 60 70 80 90 100 Male Labor force participation rate .2 Figure 6.6: Local labor supply effect of refugee’s odds of employment Source: World Bank Staff based on SESRE 2023. Note: Predicted marginal probabilities of being employed based on the labor force participation rate of the local market, tabulated by employment experience. Probability of being employed .8 .6 .4 Female 2 6 10 14 18 4 8 12 16 20 Male Unemployment rate (5%) .2 Figure 6.7: Local unemployment level matters to obtain jobs Note: Predicted marginal probabilities of being employed based on the unemployment rate of the
LEDA, which computes the minimum linguistic distance between two ethnic groups and, therefore, provides the closest linguistic neighbor for each given ethnic group (see Figure A. 1). This function computes a variable called distance, which measures the linguistic distance between two ethnic groups. Mathematically, these distances are calculated as DL1L2 = 1 −  2d (ω (L1,..., O) ∩ ω (L2,..., O)) d (ω (L1,..., O)) + d (ω (L2,..., O))  δ, (A. 1) where d (ω (L1,..., O) is the length of the path from the first language to the tree ’ s origin and d (ω (L1,..., O) ∩ ω (L2,..., O) is the length of the intersection of the paths from the first and second language to the origin. δ is an exponent to discount distances further away from the root of the tree; it is typically set to 0. 5. Figure A. 1: Linking Ethnic Data from Africa Source: M ¨ uller-Crepon et al., 2020.
Impacts on the labor market are unclear; initial research suggests that there has been a supply shock to informal labor markets. This has had a large-scale impact on the employment of natives in the informal sector. At the same time, research suggests there has been a boost to formal employment for the Turks, but this has been uneven: the low educated and women experience net displacement from the labor market and, together with those in the informal sector, declining earning opportunities.  The “ Socio-economic Assessment of the Impact of Syrians under Temporary Protection (SuTPs) on Turkish Hosting Communities ” [ongoing], to be undertaken in partnership with the Government of Turkey, will include a nationally representative household survey with SuTP and local Turkish households including camp and non-camp environments. The questionnaire will cover welfare (assets, income, expenditure), municipal services, labor and employment, education, social networks and quality of life. F. Options to improve forced displacement statistics Significant efforts are needed to enhance the reliability, comparability, quality and scope of the global data on forced displacement. In particular, more robust estimates are needed of the scale (stocks, flows and locations) and typology (demographics, location and accommodation) of forced displacement crises. This requires substantial improvements in the rigor of data collection and compilation methodologies including: (a) Harmonization of definitions and methodologies used in the collection and analysis of statistical data on forced displacement — covering stocks and flows of refugees, asylum- seekers and IDPs — to ensure comparability across regions and countries;
10 The SETAM platform has only one electronic trading platform that is run by the system administrator, creating a conflict of interest through the possibility of accessing auction data and using these to interfere in the auction process.

Auction data for our analysis come from two sources. Information on 31,483 auctions of public land for

Specifically, we use data from longitudinal and cross-country comparable national phone surveys implemented between March 2021 and January 2023. These multi-topic phone surveys were conceived in order to track the effects of the COVID-19 pandemic in the absence of in-person data collection (Himelein et al. 2020). Our experimentation with survey design choices draws on five of these surveys in Sub-Saharan Africa that were supported by the Living Standards Measurement Study (LSMS) team at the World Bank and implemented by the respective National Statistical Offices.

These surveys are re-contact surveys, drawing their samples from the latest nationally representative, in-person LSMS-ISA household survey conducted in each country before the pandemic. As part of the LSMS-ISA surveys, phone contact numbers of all household members (where available) as well as from a reference contact such as a neighbor were collected (Gourlay et al. 2021). The list of households with a phone contact, or a random subset of it, constituted the sample to be contacted for the phone surveys and covered between 73% (Malawi) and 99% (Nigeria) of households included in the in-person LSMS-ISA survey.
team of the Poverty and Equity Global Practice at the World Bank led by Christina Wieser (Senior Economist, World Bank), including Wondimagegn Mesfin Tesfaye (Economist, World Bank), Fikirte Girmachew (Consultant, World Bank), Jeremey Aaron Lebow (Young Professional, World Bank), and Manex Bule Yonis (Economist, World Bank), under the adept guidance of Pierella Paci (Practice Manager, World Bank). The report is an output of a collaboration effort between the World Bank, the Ethiopian Statistical Service (ESS), the Ethiopia Refugees and Returnees Service (RRS), and UNHCR with generous financial support from the World Bank and UNHCR Joint Data Center on Forced Displacement (JDC). Our appreciation extends to the UNHCR and RRS colleagues for their unwavering support. We offer our special thanks to Mulualem Desta (Deputy Director General, RRS) and Ashenafi Demeke (Education Team leader, RRS) for their critical guidance and support throughout the survey design, implementation, and report development phases. Moreover, we would like to thank colleagues from RRS who provided invaluable comments on the various draft stages of this report: Bruhtesfa Mulugeta, Zewdu Bedada, Daniel Adefires, Anteneh Mekasha, Anteneh Gorfu, Yewulsew Nigussie, Fantaw Kabtamu, Biruk Kebede, Dr. Goitom Ademnur, Dr. Tagay Kelil, Daniel Darcha. Additionally, we acknowledge the Household Expenditure and
_Thailand_ . As for Thailand, it is the third largest country, fourth most populous and boasts the
second largest GDP of our countries. In terms of disasters, Thailand is mostly at risk to floods
and typhoons, but earthquakes happen occasionally, with the largest recorded being a 6.1
magnitude earthquake that occurred in May 2014. The lower risk compared to our other
countries is also mentioned by INFORM in their country profile of Thailand (INFORM 2019).


_Vietnam_ . The final country is Vietnam, which is the smallest, but has the third highest
population just below 100 million people. In terms of GDP, Vietnam rank fourth among our
five countries. When it comes to disaster risk, they are on par with Thailand in that INFORM
ranks them low and exposed primarily to floods and typhoons (INFORM 2019).

National Disaster Management Agency, B. N. P. B. 2016. "DiBi database (Data and Information
on Disaster in Indonesia)." http://dibi.bnpb.go.id/.


Rahman, Md. Mizanur, Dhyan Singh Arya, Narendra Kumar Goel, and Ashis Kumar Mitra. 2011.
"Rainfall statistics evaluation of ECMWF model and TRMM data over Bangladesh for
flood related studies." _Meteorological_ _Applications_ (Wiley) 19: 501-512.
doi:10.1002/met.293.

The underlying data are based on 2015 and combines census data with satellite images from DigitalGlobe. The population is allocated according to subdivision censuses once settlements have been identified from the satellite images.

(2018) used the underlying NPP-VIIRS DNB Daily Data to analyze selected natural disasters. They found that the images were useful for detecting damages and power outages, but that cloud coverage was a major limitation in the assessment.

The first dataset combines information on flood extent and flood depth from pluvial and fluvial flooding into one flood map. It was developed by the company Fathom, formerly known as SSBN. The map covers all of Vietnam at a resolution of about 90 by 90 meters.
The Disaster and Emergency Management Presidency of Turkey (AFAD) provides information on the number of Syrian refugees. The numbers used in this paper are taken from Erdogan (2014), who draws on information from AFAD and the Ministry of Interior and reports the number of refugees by NUTS 2 subregion. To construct our instrument we use the Syrian Labor Force Survey for 2010 (the year before the beginning of the war). Finally, Google Maps was used to derive the travel distance between each governorate in Syria and the most populous city in each NUTS 2 subregion in Turkey. 14 Most recently, in January 2016, labor market access for Syrian refugees in Turkey was eased considerably. Importantly, they now can benefit from vocational training under the Turkish Employment Agency, employers will be able have to Syrians comprise up to 10 percent of their staff, and seasonal workers are exempted from the work permit, see http: / / www. resmigazete. gov. tr / eskiler / 2016 / 01 / 20160115-23. pdf. It is of course too early to evaluate the impact of these legislative changes. 15 Hurriyet Daily News (February 2015) http: / / www. hurriyetdailynews. com / turkey-urges-worlds-help-on- syrian-refugees-as-spending-reaches-6-billion. aspx? pageID = 238 & nID = 78951 & NewsCatID = 359. 16 Starting with 2014 there was a change in the design of the Household Labour Force Survey to ensure full compliance with European Union standards. This has caused some difficulty in making comparisons across years. However, our identification strategy does not use aggregate variation across years for identification and should hence be unaffected by the changes to the design of the survey.
Geographic Information Systems (GIS) and geospatial analysis can be used to map, monitor and analyze data on forced displacement. Triangulation of this information with socio-economic and other indicators can provide a rich source of data and enable insights into underlying patterns and trends over time. (e) Use of big data (mobile phone data, news scraping, social media). IDMC is pursuing big data approaches to capturing displacement data in real time in order to report on displacement situations as they are happening and to provide updates on how they are evolving (IDMC 2015). These data are not necessarily representative but can be used in conjunction with other methods to triangulate trends. For example, the Swedish NGO, Flowminder, has pioneered the use of de-identified data from mobile operators to track population displacement caused by natural disasters such as earthquakes in Haiti in 2010 and Nepal in 2015, and these techniques may also have applications in conflict-induced displacement crises. 100 (f) High-resolution satellite imagery and unmanned drones. High resolutions satellite imagery can be used to map physical structures in refugee and IDP camps including changes to the number and type of these over time, support the remote detection of displaced populations in hard to reach or insecure settings; and conduct rapid assessments during or immediately after a mass displacement (Harvard Humanitarian Initiative 2014).
some but not all of the high trust in Somali camps relative to other domains. 7.2 Social interactions Social and community integration is fundamental to refugees’ ability to improve their livelihoods, support systems, and economic integration. Having friends in the host country is a valuable resource for refugees; Ethiopian friends can provide valuable information, employer connections, assistance with language, and countless other types of social and economic support. This can also promote more positive attitudes between groups. Social integration has improved well-being, health, and educational achievement for refugee adolescents across various settings (Boda et al., 2023). 0 5 10 15 20 25 30 35 Eritrean Somali South Sudanese Addis Ababa All Refugees Family Friends Figure 7.12: Share with family or friends in Ethiopia Source: World Bank Staff based on SESRE 2023. 0 5 10 15 20 25 30 35 40 Age Under 30 Age 30-44 Age 45-64 Age Over 64 Female Male Figure 7.13: Share with friends in Ethiopia by demographic group Source: World Bank Staff based on SESRE 2023. Markets and Opportunities 69 Despite the generally positive attitudes described, social integration—measured by the friends and family refugees have in Ethiopia—is low. Only 7 percent of refugees report having family