ai4data/datause-dataset-rechunked huggingface dataset:
As a consequence, results for urban areas are not comparable across the three RDHS waves in a strict sense. 4. 2 Conflict proxies One obvious predictor of being a genocide victim in 1994 is ethnicity (that is, being Tutsi). Yet, only the 1992 pre-genocide RDHS wave records ethnicity, as self-reported by respondents. In an effort to suppress further ethnic tensions, the post-genocide government of Rwanda forbids the usage and identification of ethnic categories. Hence, RDHS collected after 1994 does not record respondents ’ ethnicity. In response to this challenge, we construct several ‘ conflict proxies ’ measuring likely exposure to conflict. These proxies allow us to differentiate two channels through which exposure to mass violence may influence fertility: replacement effects (where women choose to have children in the post-conflict period to compensate their lost children from during the conflict period) and marriage market effects (where a relative shortage of men to women creates a ‘ bottleneck ’ for women to get married). It is important to note that the conflict proxies do not necessarily identify victims of targeted genocidal violence. Rather, these proxies indicate individuals and age groups that were likely to be exposed to conflict-related violence. Given that the 1994 genocide occurred within a time span of just about 100 days, the duration or timing of conflict exposure is of less importance in the Rwandan genocide.
for 366 victims (340 men and 26 women), and abductions accounted
for 14 victims (including ten women). [6]

_Figure 3 Number of Causalities Per State in 2021_

##### **RISK 2: Displacement and Secondary Displacement due** **to Violence and Conflict**

The total number of internally displaced persons in Sudan is over 3.08
million [7], with over 89,000 newly displaced persons in Darfur from
October 2021 to January 2022. In South Kordofan, renewed intercommunal conflict resulted in the displacement of 40,000 individuals
to Abu Jubaiha in December 2021. All other hotspot localities
witnessed small numbers of new displacement in 2021.

6 Report of the Secretary-General, 2 March 2022

_Figure 4 Map IDP Concentrations in Sudan_

---
[7] According to third round of IOM DTM report, January 2022.
15 tasks (receptive spatial vocabulary, producing a set, simple addition, number identification, number comparison and shape identification), three executive functioning tasks (head, toes, knees, shoulders task, forward digit span, and backward digit span) and one social emotional learning tasks (perspective taking / empathy). The average child in KP scored a 33 % on the AIM-ECD (95 % CI: 40. 9 %, 34. 9 %). The distribution of AIM-ECD direct assessment scores is reported in Figure 5. Figure 5 Sample Distribution of AIM-ECD Direct Assessment Scores (n = 635) 8 The prevalence of stressors is presented in Table 2. For example, 26 % of the sample reported having to skip a meal, with 14 % of the sample reporting they were hungry but did not eat. Approximately 8 % of the sample was impacted by flooding in 2022, 6 % of the sample experienced flooding impacts in 2023, and 8 % of the sample were impacted by flooding in either 2022 or 2023. Of those impacted by flooding, the most common disruptions were to household members schooling, essential travel, and household members well-being.
with their high dependency ratio and high number of female-headed households. In-camp refugees working inside the camp tend to exhibit lower poverty incidence (81 percent) than those working outside the camp (88 percent). The poor tend to live in households headed by individuals with limited education. This trend is evident among both refugees and hosts, where a lower level of educational attainment by household heads and members correlates with increased poverty. While building human capital represents an essential pathway out of poverty, there appears to be low human capital among refugee and host households, as indicated by the household head and members’ low education. The data reveals that poverty incidence is more prevalent among households with no or minimal education (Annex D, Table D.11). Conversely, poverty incidence tends to decline with increased education level of the household head and members. These findings underscore the critical role of education as a means to alleviate poverty among refugees and host communities in Ethiopia. The regression results also indicate that increasing years of schooling of the household head is associated with increased household consumption (Annex D, Table D.12); average household expenditures linearly increase, and poverty headcount decreases, as the education 0.0 0.2 0.4
3 and the less educated (Ceritoglu, Tunculer, Torun, and Tumen, 2015; Del Carpio and Wagner, 2015). The economic effects of SUTPs not only vary across different segments of the labor market, there are also strong regional differences in their economic effects. Using synthetic modelling methods, Ozturkler and Goksel (2015) estimate the impact of Syrian refugees on local prices, wages, inflation, and services in 10 cities with large refugee populations. Some of the salient negative effects have been increases in rental prices, increases in inflation at border cities, illegal hiring by small business, and decreases in wages. However, in some cities (Gaziantep, Adana, Kahramanmaras, and Mardin), the presence of refugees has improved the trade balance, and economic activity in these areas are projected to increase as economic integration with MENA deepens. Orhan and Gundogar (2015) also note both positive and negative aspects of SUTPs. A primary contribution of this paper is the estimation of poverty at the sub-national level and among population groups of interest. Since migration, geographic, and welfare variables do not exist in a single data set, imputation techniques are required to overcome these limitations and to compute household level poverty.
18 corridor, so only aggregate numbers can be compared. For this comparison, mid-year estimates of the world migrant stock for 1990 – 2000 are taken from the 2008 edition and estimates for the earlier censuses, 1960 – 1980, are taken from the 2005 edition (table 8). The analysis subtracts the estimated number of refugees from the total mid-year estimates of the world migrant stock from the Trends in International Migrant Stock database to yield the net number of migrants in each decade. These numbers are then compared with the decadal estimates generated through this project, both the total and the net, after subtracting estimates of migrants within the Soviet Union for 1960 – 1980 (data for 1990 and 2000 should be directly comparable) and the number of ethnic German migrants added to the German censuses. { Table 8 here} The aggregate estimates are remarkably close (the two net totals), differing at most by around 1 million migrants, except in 1990. There are several possible explanations for these differences. First, the census totals from the current work may not match because censuses do not always make allowances for temporary workers. For example, Singapore ‘ s official 2000 census records 563, 430 foreign-born migrants. The United Nations, however, reports 1, 351, 806 foreign-born migrants for 2000.
exports. For this information, we used the World Integrated Trade Solution (WITS) database on the SITC, Revision

diversification. We use COMTRADE data on exports by product at a 4-digit disaggregated level from the SITC Revision

1.0 to compute Herfindahl indices of export product concentration. Bilateral data from COMTRADE are also used to

The CO2 emissions and energy consumption data are from International Energy Agency (IEA) Fuel Combustion Statistics database and World Energy Statistics and Balances database, respectively.
2 1. Introduction We are in the midst of protracted refugee crises. According to the latest UNHCR trends report, at the end of 2020, 76 percent of refugees globally (15. 7 million) were in a protracted situation (UNHCR 2021). 2 Most refugees reside in low-income countries, and more than eight of every 10 refugees (86 percent) live in countries within territories affected by acute food insecurity and malnutrition (UNHCR 2021a). Refugee receiving host communities also tend to be poor, experience precarious livelihood conditions and face many socio-economic challenges, such as low economic status, poor access to public services, and infrastructural development. For these communities, refugees might bring both challenges and benefits. On the one hand, refugees increase competition for natural resources (e. g., wood for energy, construction, land), public services and infrastructure (e. g., education, health, water supply), and economic opportunities (e. g., traditional livelihoods, labor employment). Refugee inflow may also affect the local market by mainly depressing wages and raising product prices (Vemuru et al. 2020).
Climate data came from two sources: US Defense Department satellites and weather station
observations. We relied on the satellite data for temperature observations and the ground station
data for interpolated precipitation observations (Mendelsohn et al. 2006). Soil data were obtained
from the FAO digital soil map of the world CD ROM. The data was extrapolated to the district
level using GIS (Geographical Information System). The dataset reports 116 dominant soil types.

These climate scenarios reflect the A1 scenarios in the IPCC's Special Report on Emissions Scenarios (SRES) (IPCC 2001) from the following models: Canadian Climate Center (CCC) (Boer et al.

These climate scenarios reflect the A1 scenarios in the IPCC's Special Report on Emissions Scenarios (SRES) (IPCC 2001) from the following models: Canadian Climate Center (CCC), Center for Climate System Research (CCSR), and Parallel Climate Model (PCM). For each climate scenario, we add the climate model's predicted change


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in temperature to the baseline temperature in each district. We also multiply the climate models
predicted percentage change in precipitation by the baseline precipitation in each district or
province. This gives us a new climate for every district in Africa.
Produced by the Research Support Team Abstract The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development / World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Policy Research Working Paper 9688 This paper provides an empirical analysis of refugee returns to the Syrian Arab Republic. Since 2011, about 5. 6 million Syrians — more than a quarter of the country ’ s pre-conflict population — have been registered as refugees. By mid- 2018, only about 1. 8 percent of them had returned to Syria voluntarily. This paper compiles a novel data set with administrative data for 2. 16 million refugees, existing and new household surveys, a new conflict-events database, and nightlights data for Syria to analyze the correlates of these returns.
on humanitarian aid, and face barriers to accessing employment and education. The country’s new Refugee Proclamation grants refugees the right to basic services, work, and freedom of movement, but implementation delays hinder their realization. To address these challenges and achieve better development outcomes for both refugees and host communities, a shift towards supporting refugees’ self-reliance and economic integration is essential. This involves enabling refugees to move toward economic opportunities, facilitating their access to the labor market through self-employment, wage- employment, and special projects, and integrating refugee children into the education system. Though refugees in Ethiopia still face significant barriers to accessing employment and education, hampering their long-term integration and exacerbating their vulnerability, initiatives are on the way to improve socioeconomic outcomes. The Socio-Economic Survey of Refugees in Ethiopia (SESRE) plays a crucial role in informing policy decisions by providing comprehensive data on the socioeconomic dimensions of refugees and host communities. By highlighting socioeconomic interactions and outcomes, SESRE aims to guide development interventions and facilitate refugee integration. The survey covers various aspects, including demographic profiles, livelihoods, welfare patterns, and social cohesion, offering valuable insights for policymakers and humanitarian actors. SESRE is a separate but integrated survey alongside the Ethiopian Household Welfare
<!-- PAGE 41 --> SOE dummies Yes Yes Yes Yes Yes Yes Age dummies Yes Yes Yes Yes Yes Yes Size dummies No No Yes Yes Yes Yes Subsidies received No Yes No Yes No Yes Industry effects Yes Yes Yes Yes Yes Yes Year effects Yes Yes Yes Yes Yes Yes Observations **[†]** 2,253,381 2,253,381 2,165,653 2,165,653 2,249,388 2,249,388 Pseudo/Within R **[†]** 0.018 0.018 0.049 0.049 0.029 0.029 Source: World Bank staff analysis using Romania MoF firm-level data from 2016-20.

SOE dummies Yes Yes Yes Yes Yes Yes Yes Yes Yes Age dummies Yes Yes Yes Yes Yes Yes Yes Yes Yes Size dummies No No No Yes Yes Yes Yes Yes Yes Value of subsidies received Yes Yes Yes Yes Yes Yes Yes Yes Yes Industry effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Year effects Yes Yes Yes Yes Yes Yes Yes Yes Yes Observations **[†]** 2,098,570 47,698 11,260 2,016,257 45,597 10,878 2,094,821 47,624 11,249 Within R-squared **[†]** 0.018 0.016 0.013 0.048 0.034 0.042 0.028 0.023 0.030 Source: World Bank staff analysis using Romania MoF firm-level data from 2016 to 2020.

<!-- PAGE 29 -->
Source: World Bank staff analysis using Romania MoF firm-level data, 2011-2019. Exit is a dummy variable equal to 1 for the last
year the firm exited the sample. Firm-level measure of allocative efficiency is computed as a cross product between two terms
defined at the 4-digit NACE sector, year, and county level: (a) the deviation of a firm's market share from the average market share
the firm exited the sample. Firm-level measure of allocative efficiency is computed as a cross product between two terms
defined at the 4-digit NACE sector, year, and county level: (a) the deviation of a firm's market share from the average market share
at the sector-year-county level, and (b) the deviation of a firm's (labor) productivity from the average firm-level productivity at the
sector-year-county level.

employment Yes Yes Yes Yes Sector size in economy Yes Yes Yes Yes Industry effects Yes Yes Yes Yes Year effects Yes Yes Yes Yes Observations 704 704 704 704 Within R-squared 0.021 0.019 0.031 0.032 Source: World Bank staff analysis using Romania MoF firm-level data, 2011-2019.
meet the requirements of the OCP residency permit (RRS, 2019). Arrival before and after November 2020 The Tigray region of Ethiopia used to host Eritrean refugees in four camps before the outbreak of conflict between the regional and the Federal government in November 2020.18 Consequently, refugees in the region fled to neighboring Afar and Amhara regions and Addis Ababa.19 Hence, the RRS granted out-of-camp residency for those refugees who arrived in Addis Ababa due to the conflict. As of April 2023, Eritrean refugees relocated from Tigray to Addis Ababa constitute 36 percent of the total Eritrean population in Addis Ababa (UNHCR, 2023a). OCP refugees who arrived before and after November 2020 have similar sociodemographic characteristics except age, education, and child health outcomes. Refugees after November 2020 are younger and less educated compared to refugees before November 2020. Moreover, child health problems in terms of nutritional indicators, underweight, stunting, and wasting are higher among refugees moved from camps relative to refugees who were in Addis Ababa for a longer time. Box 2.2: Refugees under the Out-of-Camp Policy (OCP) 18 https://www.unrefugees.org/news/ethiopias-tigray-refugee-crisis-explained/ 19 https://www.hrw.org/news/2021/09/16/ethiopia-­eritrean-­refugees-­targeted-­tigray Sociodemographic Profile 15 Primary and secondary school enrollment rates vary between hosts and refugees; refugee primary education rates are
_Gallup_ _World_ _Poll_ _(GWP)_ is a nationally representative opinion survey and has been con ducted annually since 2006 in a wide range of countries around the world. The sample collected in Peru is a repeated cross-section of about approximately 1,000 observations each year. For our analysis, we use data from 2013 to 2020. The survey questions are centered around politics, governance and opinions on current events. We make use of several opinion indices provided by Gallup that measure individual opinions on various domains. Observa tions are spatially identified at the region level for Peru, which is our level of analysis in this case (there are 25 regions in Peru).

_PTP_ We measure the location of Venezuelan immigrants on a monthly basis from January 2015 to December 2020 using administrative data on the district Venezuelan immigrants register at with the Peruvian authorities to obtain access to social services. There are strong incentives to register as this is also a prerequisite for applying to obtain the PTP. This data only records monthly gross arrivals so we do not know the outflows of Venezuelans to other locations within Peru or out of the country entirely. However, in ENPOVE, 84% of Venezuelan immigrants in Peru report having lived in the same district during their entire time since arriving in the country. The data shows the arrival of 511,223 Venezuelans as of December 2020, which, while somewhat lower than estimates of the actual number of Venezuelans living in Peru, is quite substantial.

We also use data from the _National_ _Census_ _2007_ _and_ _2017_ . We use the 2017 Census data to measure the share of workers in the formal and informal sector in each centro poblado as well as the total local population in each centro poblado, province and region. We use the 2007 data to construct both of our instruments discussed in more detail below as well as to create additional controls for the local economic environment.

To construct the _Trade_ _shock_ instrument for the first part of our analysis, we also use trade data from the reports of TradeMap. From this website
both of our instruments discussed in more detail below as well as to create additional controls for the local economic environment.

To construct the _Trade_ _shock_ instrument for the first part of our analysis, we also use trade data from the reports of TradeMap. From this website, we are able to identify export and import values for Peru on a monthly basis since 2006 at the HS 6-digit product revision. In addition, correspondence tables of HS 6-digit product revision to ISIC 3.1 revision (United Nations) are used to harmonize products with their corresponding industry sector in order

Specifically, we look at the reported (log) number of crime in each district from administrative data split into non-violent and violent crimes (data starting in 2011, means 3.54 for log violent crime and 3.31 for log non-violent crime), from ENAHO whether crime is a major national problem (12.7%), from LAPOP whether they have been a crime victim in the last two months (32.0%) and standardized variables from LAPOP on opinions about neighborhood safety and from Gallup on personal security.
Government officials repeatedly banned opposition demonstrations, fired teargas and live bullets at peaceful protesters, shut media outlets, and prevent opposition leaders from moving freely75. According to UNHCR, there are over 2 million IDPs in the DRC, and over 450, 000 refugees. In year 2016, there were about 13, 000 returned refugees and 619, 000 returned IDPs. “ Dozens of armed groups remained active in eastern Congo, many of their commanders have been implicated in war crimes, including ethnic massacres, killing of civilians, rape, forced recruitment of children and pillage. 76 ” Economic Opportunity 73 CIA the World Factbook, Sudan, https: / / www. cia. gov / library / publications / the ‐ world ‐ factbook / geos / su. html 74 CIA, the World Factbook, https: / / www. cia. gov / library / publications / the ‐ world ‐ factbook / geos / cg. html 75 Human Rights Watch, https: / / www. hrw. org / world ‐ report / 2017 / country ‐ chapters / democratic ‐ republic ‐ congo 76 Human Rights Watch, DRC, https: / / www. hrw. org / world ‐ report / 2017 / country ‐ chapters / democratic ‐ republic ‐ congo
100 Eritrean (camps) Somali South Sudanese Addis Ababa All Refugees Ethiopian refugee camp Ethiopian city Country of birth Other African country Western country Percent Figure 4.2: Expected location in three years Refugees’ Aspirations 40 Most refugees hope to go to a Western country in the next three years. When asked in the SESRE where they would like to live in three years, most refugees say they would like to live in a Western country. This rate is highest among OCP refugees (90 percent) and Eritreans in camps (83 percent), lower in Somali camps (66 percent), and lowest in South Sudanese camps (29 percent). More Somalis and South Sudanese hope to stay in Ethiopian refugee camps than Eritreans. South Sudanese refugees stand out in that almost 20 percent hope to return to their country of birth in the next three years, while this rate is meager for other groups. Despite the low probability of being resettled, refugees hold an unrealistically high belief that they will migrate to a Western country in the next three years. To distinguish between desires and expectations of reality, in addition to asking households where they hope to live in three years, the SESRE also asks where
in Refugees With Clinically Established Psychopathology. Psychiatrike= Psychiatriki. Tsolak, D., and Bürmann, M. (2023). Making the Match: The Importance of Local Labor Markets for the Employment Prospects of Refugees. Social Sciences, 12,339. https://doi.org/10.3390/socsci12060339 Tumen, S. (2019). Refugees and ‘Native Flight’ from Public to Private Schools. Economics Letters, 154 - 159. https://doi. org/10.1016/j.econlet.2019.05.030. Tumen, S. (2021). The Effect of Refugees on Native Adolescents’ Test Scores: Quasi-Experimental Evidence from PISA. Journal of Development Economics, 150, 102633. https://doi.org/10.1016/j.jdeveco.2021.102633. UNHCR. (2020). Coming Together for Refugee Education. Education Report 2020. UNHCR. (2020a). Ethiopia Refugee Education Strategy: Towards inclusion. UNHCR. (2020b). Ethiopia Fact Sheet: September 2020. UNHCR. (2020c). Ethiopia 2019 Summary Pledge Progress Report. UNHCR. (2020d). Global Trends Forced Displacement in 2019. Retrieved from https://www.unhcr.org/5ee200e37.pdf UNHCR. (2021). Global Compact on Refugees Indicator Report 2021. UNHCR. (2022). Refugee Settlement Profile: Alemwach. UNHCR. (2022a). Ethiopia Annual Results Report 2022. UNHCR. (2022b). Global Trends: Forced Displacement in 2021. https://www.unhcr.org/publications/brochures/62a9d1494/ global-trends-report-2021.html. UNHCR. (2022c). Ethiopia Country Refugee Response Plan (ECRRP) Jan Dec 2022. https://data.unhcr.org/en/documents/ details/94099 UNHCR. (2022d). Serdo Refugee Camp Profile April 2022. https://data.unhcr.org/fr/documents/details/
Jan Dec 2022. https://data.unhcr.org/en/documents/ details/94099 UNHCR. (2022d). Serdo Refugee Camp Profile April 2022. https://data.unhcr.org/fr/documents/details/92436 UNHCR. (2022e). “Global Report 2021.” http://reporting.unhcr.org/globalreport2021/pdf. 81 UNHCR. (2023). Ethiopia Global Refugee Forum Pledge Progress Report. UNHCR. (2023a). Addis Ababa Quarterly Urban Factsheet, April 2023. UNHCR. (2023b).