Input: 16 Investors actively trade-off disaster risk with gains from economic density. In addition to the city or location specific analysis, we examine how investors value risk from natural disasters. Data from a recently compiled dataset of a sample of global cities provides some insights. Gomez-Ibañez and Ruiz Nuñez (2006) constructed a dataset of central business district office rents for 155 cities around the world in 2005 to identify cities where rents seem elevated or depressed by poor land use or infrastructure policies. Their dataset also includes information on many factors that determine the supply and demand for central office space such as construction wage rates, steel and cement prices, geographic constraints, metropolitan populations and incomes. We link this information to the natural disasters hotspot dataset (Dilley et al. 2005), and examine if city demand – as reflected in office rents, is sensitive to risk from natural disasters. Gomez-Ibañez and Ruiz Nuñez (2006) focus on offices in the primary business district, which they define as the district having the highest density of employment; a very large, if not the largest, concentration of offices; and the highest rents in the metropolitan area. As we are interested in the tradeoff between economic density and disaster risk, using the central business district works well for our analysis.

dataset of central business district office rents for 155 cities around the world

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Input: reason to believe that the provision of services by donors and non-state actors could either strengthen or weaken citizens ’ deference to government. I will identify the conditions under which these two scenarios are likely to occur. On the one hand, citizens may be less likely to support the government with deference to its laws and regulations when they credit non-state actors or donors for service provision. The provision of services by donors and non- state actors is likely to prompt citizens to question why they should pay taxes to a government that is not providing them with anything in exchange. On the other hand, the provision of goods and services by donors and non-state actors might strengthen citizens ’ legitimating beliefs and their willingness to defer to governmental laws and regulations if citizens view their government as essential to leveraging and managing these external resources. I assess these competing hypotheses using multi-level analyses of Afro- barometer survey data. The sample, drawn from a continuum of developing societies in Africa, allows us to analyze associations between donor and non- state actor service provision and the sense of obligation to comply with the tax authorities. Third, I assess the relationship between the provision of ser- vices by donors and non-state actors and citizens ’ willingness to defer to two additional authorities, the police and courts.

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Input: Despite notable disparities in the characteristics of our sample compared to the VenRePS and RAMV samples, understanding the interaction of these attributes within a frame- work of self-selection among migrants into Medellin is challenging. Moreover, it is cru- cial to note two primary distinctions between our survey and the VenRePS and RAMV surveys. Firstly, the inherent differences in the sampling frames of each survey stem from their distinct measurement objectives. Second, both surveys were conducted at different times compared to our survey. The RAMV survey was undertaken in 2018 in response 10See Ib ´ a ˜ nez et al. (2022) for specific survey and sampling details. 11Refer to Ib ´ a ˜ nez et al. (2022) for further details. 12Since the VenRePS and RAMV surveys lack information regarding children and adolescents within households, our analysis concentrates only on the household and household head characteristics that are available in all three surveys. 20

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Input: 10 inflow). We then use the composite variable as an instrument to identify the causal impact of refugee presence on livelihood diversification and commercialization in host communities. Figure 2: Household livelihood strategy framework under refugee inflow Source: Adapted from Nielsen et al. (2013) and Walelign and Jiao (2017) 4. Data sources The major data source of the current study is the World Bank ’ s Development Response to Displacement Impacts Project (DRDIP) 12 baseline survey from Ethiopia. The Ethiopia DRDIP survey was administered between September 2017 and August 2018. The survey covers 113 Kebeles (wards) in 16 Woredas (districts) from the top five refugee-hosting regions in Ethiopia. The selection of the sample households follows stratified random sampling with proportion to size (the number of households) using Woredas as a geographic stratum. The sample originally comprised a total of 3, 390 households, who were selected using systematic random sampling within each Woreda. We used data from 3, 375 households, as 15 of them were excluded due to missing location information (GPS). Usage context: supporting mention, primary mention, background mention.

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Input: poverty and well-being. With increasing income, more affluent households are more likely to spend a greater share of their budget on high-value food items such as animal- origin diets, processed food, and food away from home, as well as on non-food items. Except for Addis Ababa, food consumption patterns, as indicated by expenditure shares, differ by food groups (Figure 5.6). Overall, refugees expenditures are higher on cereals and less on animal-origin food items associated with the types of food aid provided. This could be because refugees receive assistance for cereals/grains, not animal-origin food items. Food away from home is lower for refugees than hosts, except in Addis Ababa. - 10,000 20,000 30,000 40,000 50,000 60,000 70,000 Hosts Refugees Hosts Refugees Hosts Refugees In Camp Addis Ababa Total Food Non-food non-durables Durables Rent Figure 5.3: Expenditure components (in birr) Source: World Bank staff based on SESRE 2023. Note: The expenditures are in December 2022 values. 61% 58% 59% 68% 56% 65% In Camp Addis Ababa Total Hosts Refugees Figure 5.4: Shares of food expenditure Refugees’ Aspirations 45 Expenditures for in-camp refugees is almost half that of hosts, despite the sizeable food aid and cash transfers (in selected camps) the WFP and

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Input: Our research complements and extends the findings of Demirci, Foster and Kirdar (2022), who investigated health and nutrition disparities between native children and Syrian refugee children aged 0 to 5 years in T ¨ urkiye, using data from the Demographic and Health Survey. The authors document find no significant differences in infant or child mortality rates between refugee children born in T ¨ urkiye and their native counterparts, it did reveal that refugee infants have lower birth weights and age-adjusted weights and heights compared to native infants. Our work broadens the scope of analysis beyond anthropometric indicators to encompass a holistic assessment of child development. By incorporating measures of physical, cognitive, socio-emotional, and mental health devel- opment, along with factors such as food security, time use, risky behaviors, and social integration, we offer a more comprehensive understanding of the developmental chal- lenges faced by displaced minors. Additionally, our study includes a wider age range, 5Chiovelli et al. (2021) examine the effects of forced displacement on separated sibling in the long-term. 8

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Input: Enumerators reminded respondents that the survey was part of an academic study and not connected to service provision decisions, which we hope alleviate some of these incentives. That said, it is important to note that this project analyzes self- reported perceptions of the presence of IDPs or refugees, not the conﬁrmed presence of displaced populations. Hosting Status Aggregate Individual % Respondents Displaced Currently Self-Reported Hosting % Respondents Recently Displaced Self Reported Hosting IDPs Self Reported Hosting Refugees Table 3: Operationalizing Hosting Status 24 Usage context: background mention, supporting mention, primary mention.

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Input: Table 5: Coverage of Published Data on Location, Accommodation and Demographics 2015 Population end- 2015 (millions) Urban or Rural Location Accommodatio n Age Sex Refugees and people in refugee-like situations 16. 1 85 % 83 % 58 % 68 % Other people of concern to UNHCR 47. 8 (including 37. 5 IDPs) 70 % 47 % 25 % 39 % UNHCR ’ s total population of concern 63. 994 73 % 56 % 33 % 46 % IDPs monitored by IDMC but not included in UNHCR's data 3. 3 0 % 0 % 0 % 0 % Source: UNHCR Global Trends 2015 Note: Other people of concern to UNHCR include asylum-seekers, IDPs and people in IDP-like situations protected or assisted by UNHCR, stateless persons, and ‘ other ’. Overall robustness of current data The robustness of data is difficult to estimate. A review of data collection and compilation methodologies shows broad variations in terms of the accuracy and reliability of the global estimates of forced displacement that are widely used. Headline figures on forced displacement are significant in shaping public opinion and are critical for sound decision making, both to inform the allocation of resources and to design effective humanitarian and development responses. However, the available estimates are potentially misleading and should not be referred to without appropriate caveats and qualifiers. Usage context: supporting mention, background mention, primary mention.

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Input: 16 Source: Authors ’ calculations based on data from the High Frequency Surveys of Ethiopia (2017), Nigeria (2018), Somalia (2017), South Sudan (2017) and Sudan (2017). 6. Gender differences in multidimensional poverty Next we examine differences in multidimensional poverty outcomes by the gender of the household head. Existing literature points out the limitation of household level MPI analysis in masking the intrahousehold distribution of deprivations, and thus being less sensitive to gender based differences in individual outcomes within the family unit, which might lead to underestimation of inequality and gender gaps (Espinoza-Delgado and Klasen 2018; Franco 2017; Klasen and Lahoti 2020, Rodriguez, 2016). However, as the MPI identifies poverty at the household level, our initial analysis focuses on disaggregated results by the gender of the household head. 19 We acknowledge that this approach has several limitations since most women reside in male-headed households, and the composition of households can change after displacement due to separation of family members, and widowhood. Regardless, the analysis at the household level remains relevant given the high prevalence of female-headed households that emerge after displacement, with the analysis showing large differences across countries between households based on the gender of the head. Usage context: background mention, primary mention, supporting mention.

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Input: To take advan- tage of the much larger ProGres database of nearly 2. 2. million refugees, we compute area averages for the above-mentioned case-level host community conditions, aggregat- ing to the smallest possible geographic unit available (district level for Lebanon and governorate level for Jordan). This information is then matched with all refugees in the ProGres database that have location information in Lebanon and Jordan, yielding a sample of 1. 85 million refugees. Finally, we worry about reporting bias. Respondents may have felt they were more likely to receive assistance if they reported worse living conditions. The bias could also go the other way if refugees want to signal their gratitude for the assistance they receive. The problem is even more acute given our research question. Those who intend 13 Usage context: background mention, primary mention, supporting mention.

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Input: 29 evaluations have been conducted (Renton et al., 2000; Shaw, 2000; Shaw, 2002a; Shaw, 2002b; Paine et al., 2002; White, Greene and Murphy, 2003; Interagency working Group, 2003). For example, the Medical Research Council (from the United Kingdom) conducted an external evaluation of program effectiveness in the Gambia using key informant interviews, focus groups, and a KAP (knowledge, attitudes and practices) survey in four villages, including two program sites and two controls. That study found that the Gambia program improved self-reported attitudes and behaviors related to violence against women. Specifically, the program reduced the social acceptability of wife-beating at the community level and appeared to produce a corresponding drop in that behavior. Qualitative findings from other Stepping Stones sites suggest similar benefits. Program H (Bolivia, Brazil, Colombia, Jamaica, Mexico and Peru) is being carried out by four NGOs. It aims to change gender norms and sexual behaviors in Bolivia, Brazil, Colombia, Jamaica, Mexico and Peru (Barker, 2003; White, Green and Murphy, 2003; Guedes, 2004).

KAP (knowledge, attitudes and practices) survey

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Input: in Bangladesh). The data set we use does not cover the 5. 1 million Palestinian refugees who are under the man- date of the United Nations Relief and Works Agency for Palestine Refugees in the Near East (UN- RWA). The deﬁnition of Palestinian refugees in international law is distinct from other refugees. Palestinian refugees are people “ whose normal place of residence was Mandatory Palestine be- tween June 1946 and May 1948, who lost both their homes and means of livelihood as a result of the 1948 Arab-Israeli conﬂict ”. Importantly, their patrilineal descendants are also considered refugees regardless of citizenship (UNRWA 2009). For the purpose of the analysis, we do not include Internally Displaced Persons (IDPs), who are deﬁned as “ persons who have been forced or obliged to ﬂee or leave their home or place of habitual residence, in particular as a result of or in order to avoid the effects of armed conﬂict, situations of generalized violence, violations of human rights or natural or human-made disas- ters, and who have not crossed an internationally recognized border ” (United Nations 2004). The categories “ returnees ”, “ Stateless ”, and “ Others of concern ” are also not included.

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Input: Secondary Figure 3.13: Share employed by age – camp hosts Source: World Bank Staff based on SESRE 2023. Jobs and Livelihoods 32 When refugees own livestock, the value and flock size of this livestock is low. Somali refugees mostly own sheep, goats, and donkeys, and compared to Somali hosts, they have smaller flock sizes and lag them in terms of cattle ownership. As Figure 3.17 shows, the lower value of livestock in refugee households also reflects lower reported monetary value of equivalent livestock (per Tropical Livestock Unit). For the most part, however, it reflects the lower value of the type and number of livestock refugees own. In Eritrean and Somali camps, refugees and hosts report a similar rate of non-farm business ownership; but the value of productive assets in refugee businesses is low, indicating they are primarily small-scale and low-income. The exception is Somali refugees, partially driven by ownership of animal-drawn carts. Across all domains, refugees have a lower value of productive assets such as farming tools and construction equipment. They are also less likely to own commercial cars, motorcycles, or Bajaj, a cause of a significant portion of the gap in total value of assets between refugees and hosts.

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Input: cope with the emergencies that arise all too often. 20 To facilitate successful coping and provide a safe place to save, the EPAG program assisted each participant to set up a savings account at a local bank if she did not already have one. Table 5 presents midline survey results that indicate that the treatment group were nearly 50 percentage points more likely to have savings than the control group, and were saving on average LD 2500 (nearly US $ 35) more than the control group. EPAG graduates were also twice as likely as the control group to have outstanding loans (six percent v. three percent), and have loans from formal lenders (five percent v. two percent), 21 although the overall rate of obtaining credit remains extremely low. 4. 3. Empowerment The Adolescent Girls ’ Initiative is based on the hypothesis that livelihood and life skills training for young women will improve their lives in more than just narrowly-defined economic dimensions. In addition, evidence is increasing that these soft skills are also essential for success in employment (Borghans et al. 2008). Usage context: supporting mention, primary mention, background mention.

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Input: consultation with UNHCR and RRS. We used the ESS EA maps to assess the settlement of communities around camps, ensuring a precise fit to the definition of a “host community”. The assessment highlighted that using the list of EAs obtained from the new cartographic frame57 meets the definition of host community In the SESRE, host community members are defined as those who live adjacent to a refugee camp but within a radius of 5km. We use the updated Ethiopian Statistics Service 2018 cartographic database of enumeration areas (EAs) to define them. An EA is a defined area where 100-150 households live in rural areas, while in urban areas, it is an area where 150- 200 households live. The first stage of sampling for the host community involved using simple random sampling to select EAs—the primary sampling unit— from the list of EAs that are adjacent but within a radius of 5km. Following EA selection, a fresh list of households was prepared at the beginning of this survey, which was used as a frame to choose sampled households from each sample EA. In Addis Ababa, a separate host domain was developed as refugees spatially concentrate in a few sub-cities and Woredas.

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Input: The United Nations Economic Commission for Europe ’ s (UNECE) guidelines include a question on reason for migration, population with a refugee-like background and IDPs as non-core topics / questions (UNHCR 2016). 72 While most countries include questions on country of birth and citizenship, only about 40 percent include a question on year of migration, less than a quarter include a question on reason for international migration, and about a fifth include a question on the reason for internal migration (UNHCR 2016). 73 E. g. Kyrgyz Republic 1999 (refugee status), West Bank and Gaza 2007 (refugee status), Zambia 2000 and 2010 (purpose of stay), Germany 1970 (federal refugee identity card), Greece 2001 (reason for settling in Greece), Sudan and South Sudan 2008 (type of household including IDP and refugee), Liberia 1990 (ever displaced by war since 1990), Uganda 2014 (refugees). 74 UNHCR is collaborating with the Statistics Norway on systematically embedding forcibly displaced peoples in national statistics exercises and collaborates with national authorities and with UNFPA in various countries on the design of census exercises that include refugees, IDPs, returnees and stateless persons. 75 LSMS is a household survey program housed in the Bank's Development Research Group that provides technical assistance to national statistical offices in the design and implementation of multi-topic household surveys covering household behavior, welfare and interactions with government policies. All data gathered through the LSMS is published online in the Bank ’ s Central Microdata Catalog. Usage context: supporting mention, background mention, primary mention.

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Input: 4 The article employs a unique data source from Jordan, the 2010 Jordan Labor Market Panel Survey (JLMPS 2010), which includes information on parents ’ schooling for every adult in the sample, along with the 2010 School Census produced by the Jordanian Ministry of Education (Hashemite Kingdom of Jordan, 2010). The school census provides the subdistrict, type, and date of establishment of every school in Jordan, allowing us to measure the local supply of each type of schools in each subdistrict in every year (under the presumption that there were no significant school closures or changes in type over time, which is likely the case). The exposure of an individual in the JLMPS 2010 sample to the supply of public schooling is then determined by the number of sex-appropriate basic (or secondary) public schools (per 1, 000 individuals) that were available to them in their subdistrict of birth at the time they were of age to enroll in that school level (six years of age for basic and 15 years for secondary). The richness of the data set makes it the first in the Middle East to allow such a study. Usage context: primary mention, background mention, supporting mention.

2010 School Census
2010 Jordan Labor Market Panel Survey

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Input:
Oseni and Pollitt (2013) use cross-sectional data on electricity outages collected by the 2007 World Bank Enterprise Survey of 6,854 firms in 12 African countries.

** **Data** We used the social accounting matrix (SAM) of year 2007.

We use a choice experiment study to fill this knowledge gap and identify preferences for

goods, when market data are not available for assessing these valuations. A choice experiment

survey presents the respondent with choice scenarios where each choice scenario has

The enumerators spoke local languages and were trained in conducting choice   experiment surveys (and most had previous experience with collecting choice experiment data

social accounting matrix (SAM) of year 2007

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Input: This study aims to assess the consequences of forced migration on ethnic diversity and conflict in Sub-Saharan Africa. We combine a unique dataset on refugee camps with individual data from the Afrobarometer Surveys across 23 African countries for the 2005 — 2016 period. We construct two standard measures of ethnic diversity: indices of ethnic fractionalization (EF) and ethnic polarization (EP). Ethnic fractionalization measures the probability that two individuals drawn from the society at random will belong to two different ethnic groups and thus increases with the number of ethnic groups present. Ethnic polarization captures antagonism between individuals and is maximized when the society is divided into two equally sized and distant ethnic groups. Although these indices have been widely used, little variation over time has been found, making causal inference difficult. The innovative aspect of our analysis is that we use data on the precise locations of refugee camps, their yearly size, and — most importantly — their annual composition in terms of countries of origin. Combined with the Ethnic Power Relations- Ethnicity of Refugees 2019 dataset, we are able to predict changes in ethnic diversity induced by refugee inflows. We then assess the relationship between refugee diversity and the likelihood of conflict. In an additional analysis, we also assess how refugee-induced changes in diversity affect the incidence of theft and violence, participation in protests, and perceptions of ethnic attachment, inter-personal trust, and institutional trust. Other studies have investigated the links between displacement and social conflict or social co- 3 Usage context: supporting mention, primary mention, background mention.

Ethnic Power Relations- Ethnicity of Refugees 2019

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Input: A panel database tracking outcomes for a cohort of 2,400 households across six districts was established during the baseline survey phase. The panel database will be updated at 18-month intervals through follow-up surveys using the same household roster, allowing the evaluation team to track changes in income, consumption, and access to services at the individual household level. Attrition in the panel database will be documented and analyzed to assess whether survey non-response is systematic and whether inverse probability weighting adjustments are required.

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Input: The paper extends the GTAP 8 database by separating Lebanon, Jordan, Syria, Iraq, and West Bank and Gaza from the rest of the Western Asia aggregate and Algeria and Libya from the rest of North Africa. Kuwait, Qatar, Bahrain, Saudi Arabia, UAE, and Oman are aggregated into a GCC composite group. In addition, the 57 sectors in the GTAP 8 database are aggregated into 22 sectors based on their importance for the countries in the MENA region (Table 1). The resulting MENA-specific database contains 26 countries, among which are the six Levant economies of interest in this paper (Turkey, Lebanon, Syria, Iraq, Jordan, and Egypt) and the rest of the developing MENA countries (Table 1). The procedure used to construct the individual country information employs data from several sources. The UN Statistics Division data for 2007 is the source for the six components of GDP – agriculture, hunting, forestry, and fishing (ISIC A-B); mining, manufacturing, and utilities (ISIC C-E); construction (ISIC-F); transport, storage, and communication (ISIC I); wholesale, retail trade, restaurants and hotels (ISIC G-H); and other activities (ISIC J-P).

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Input: years) ......... 103 Figure D.12: Average annual per capita health expenditure ....................... 103 Figure D.13: Types of disability..................................................................... 104 Figure D.14: Rent expenditure (Refugees and hosts in Addis Ababa) ........ 104 Figure D.15: Hand washing facility................................................................. 104 Figure D.16: Top 3 difficulties with being a refugee by survey domains ..... 108 Figure D.17: Work status by survey domains ������������������������������������������������ 108 Figure D.18: Type of work by survey domains ���������������������������������������������� 108 Figure D.19: Occupation by survey domains ������������������������������������������������� 108 Figure D.20: Work location by survey domains ��������������������������������������������� 108 Figure D.21: Hours per week by survey domains ����������������������������������������� 108 Figure D.22: Hourly earnings by survey domains ����������������������������������������� 109 Figure D.23: Household owns crops ............................................................. 109 Figure D.24: Household owns livestock......................................................... 109 Figure D.25: Total value of livestock ............................................................ 109 Figure D.26: Value per tropical livestock unit ������������������������������������������������ 109 Figure D.27: Household has non-farm business ����������������������������������������� 109 Figure D.28: Value of productive assets in households with business ........ 110 Figure D.29: Primary source of income pre-post migration by survey domains......................................................................... 110 Figure D.30: Youth work status by survey domains �������������������������������������� 110 Figure D.31: In-camp refugee locations by ecological Zone ........................ 115 Figure D.32: Refugee’s labor market performance ��������������������������������������� 115 Figure D.33: Economic sector........................................................................

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Input: problems. Previous literature has shown that immigrants are more likely to move to locations where they have a network of peers from the same country. We show below that this is true among Venezuelans in Peru as well. Our main interest is on β1, which represent the impact of the labor market conditions in centro poblado j on the discrimination experienced by Venezuelans. Venezuelans who arrive to the country clearly evaluate where to settle based on the labor market opportunities (among other reasons), and therefore to causally identify β1 we need a source of exogenous variation for the labor market at the local level. We use an instrumental variable strategy that exploits variation in the share of workers employed in diﬀerent industries in 2007, along with national level shocks to trade in speciﬁc industries between Oct 2016 and Oct 2017 when the census was collected. More precisely, the ﬁrst stage regression is given by: lnEmpj = α + νSharejk (2007) × ∆ lnExportk + ηXij + νZj + αo + ϵj (2) where Sharejk (t − 1) is the share of workers in centro poblado j employed in industry k in 2007, and ∆ Exportk represents the log change in national level exports in industry k between 2016 and 2017. The remaining control variables are similar to those in Equation 1. Usage context: supporting mention, background mention, primary mention.

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Input: 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 10631 This paper aims to understand the existing gaps in micro- level data on forcibly displaced people — refugees and internally displaced persons. The paper undertakes a comprehensive review of all existing micro-level data sets in the United Nations High Commissioner for Refugees Microdata Library and the World Bank Microdata Library. It first identifies a corpus of micro-level data sets that are designed to have a representative sample of refugees and / or internally displaced persons and assesses gaps in geographical and thematic coverage. The paper then evaluates whether the data sets contain a core set of questions that are essential for the proper identification of refugees and internally displaced persons. Usage context: supporting mention, primary mention, background mention.

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Input: Papaioannou, 2016; Berman et al., 2017; Harari and Ferrara, 2018; Eberle et al., 2020; McGuirk and Burke, 2020b). As a further robustness check, we also use data on conflict incidence and intensity from the UCDP, which uses a more conservative definition of conflict. The UCDP dataset is manually curated and compiled with automated computer assistance (Sundberg and Melander, 2013). The UCDP defines an armed conflict event as “ an incident where armed force was used by an organized actor against another organized actor, or against civilians, resulting in at least one direct death at a specific location and a specific date ” (Pettersson et al., 2020). We extract daily event observations from the UCDP dataset if the location of the actual event is exactly known, the event location is within a radius of less than 25 km around a known point, or at least the administrative district where the event happened is known. As pointed out by Eberle et al. (2020), the UCDP events are more likely to capture violence between large-scale and more structured groups. Table B. 2 shows that on average, conflict events seem to occur more in refugee-hosting areas. This is of course not a causal interpretation but a simple correlation.

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Input: 5 3. Data The data used in this paper have been collected through the Listening to Displaced People Survey (LDPS). 4 The baseline face-to-face interviews were executed between June and August 2014. The following 12 monthly interviews – from August 2014 until August 2015- were conducted using mobile phones. 5 The original sample comprised 501 respondents (51 % Male, 49 % Female) and was divided between internally displaced people (IDPs) located in the capital city Bamako, 6 refugees living in refugee camps in Mauritania and Niger, as well as returnees living in the regional capitals Gao, Timbuktu and Kidal in Northern Mali. This survey did not collect information on individuals who were never displaced. The attrition rate was very low, always around 1-2 % per wave. We need to stress that the locations were not randomly selected. Bamako was selected because it hosted a large number of IDPs. Furthermore, the main cities in the north of Mali were chosen to obtain a large sample of returnees given the funds available. Finally, a refugee camp was located in Niger since bureaucratic issues did not allow the inclusion of a camp in Burkina Faso. Nevertheless, households were selected randomly within each location.

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Input: Columns 2, 3, and 4 show that age, school attendance, and employment status at baseline are all correlated with survey attrition. To further investigate whether these characteristics lead to differential attrition between the treatment and control groups, we interact treatment with particular characteristics at baseline. Columns 5 and 6 show that, conditional on being in the control group, the most likely predictor of attrition is having a child. By itself, being a mother does not predict attrition, but when interacted with treatment, we see that control group mothers are more likely to have dropped out of the panel than their treated counterparts. Employment at baseline, while positively correlated with attrition, does not differentially affect treated and untreated individuals. Because the differential attrition between treatment and control groups may bias our results, we use Inverse Probability Weighting (IPW) as outlined in Wooldridge (2002) to adjust the estimates of our key outcomes, using the inverse probability of inclusion in the panel as a probability weight. As a first step, we use the probit model in Column (6) of Table 10 to regress the likelihood of being observed twice on baseline individual characteristics, including those likely to affect attrition, such as employment and parental status. In the second step, we use the inverse of the predicted values from that probit model as probability weights to redo the difference-in-difference regressions for our key outcomes of interest. This method gives more weight to the individuals with the highest chance of attrition, giving them more influence on the estimate of the impact than those with a low probability of attrition. The results are reported in Table 11. The results show a high degree of similarity between the original (unadjusted) and the adjusted estimates. Across all outcomes, the point estimates and standard errors vary only slightly. 27 Of these 305 cases, nine are dropped from the attrition analysis because the household head was not interviewed at baseline, hence the household level control variables are not available. 23

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Input: migration, and reason for movement including asylum / refugee protection (or conflict-induced internal migration) (UNHCR 2016), or a specific question to identify IDPs or refugees. However, not all censuses cover refugees and asylum-seekers (if foreigners are considered outside the scope of the census or because they are considered a special category), 71 nor is it common practice for national censuses to include questions related to forced displacement. 72 Nevertheless, there are several examples of national censuses that have included relevant questions on forced displacement. 73, 74 In the case of protracted internal displacement situations, IDPs are likely to be included in national censuses; however, census instruments may be subject to manipulation for political purposes. There are several drawbacks of population censuses including their cost, the significant training required for enumerators to ensure consistent answers to questions on forced displacement, impediments to field operations and data processing (such as weather conditions and technical problems), the relative infrequency with which they are carried out, and the long processing time before data and statistics become available, which have consequences for the timeliness of data. Moreover, often censuses are not conducted in contested territory or conflict zones where many displaced persons reside, and this limits the completeness of the data. Usage context: background mention, primary mention, supporting mention.

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Input:
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.

longitudinal and cross-country comparable national phone surveys

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Input: In our employment arm, we oﬀer gainful employment in the form of a surveying assignment for an average of three days per week for two months. 1 The surveying task requires workers to walk through their blocks four times per day tallying the various activities their neighbors are engaged with and consumes approximately 2. 5 hours per workday, resulting in a form of part-time employment. The job is designed to embody the key features inherent to ‘ work ’. Drawing from the economics literature, workers must exert real eﬀort and their task occupies a meaningful portion of their work day. Drawing from the sociology literature, the work involves some degree of sociability and purpose in the completion of a productive task. Employment lasts for eight weeks, a long duration given the scarce daily labor opportunities that arise in our setting. Relative to this employment arm, our control arm receives no work and a small fee for weekly survey participation. A comparison of the control to the employment arm therefore yields the psychosocial beneﬁts of the employment intervention. In order to estimate the non-pecuniary psychosocial value of employment, we include a cash treatment arm, in which no work is oﬀered, but a large fee (equivalent to that received by those in the employment arm) for weekly survey participation is provided. We work in the Rohingya refugee camps, situated upon the southern tip of Bangladesh. 1We obtained formal permissions from camp administration to engage our study participants in this manner through our NGO partner, Pulse Bangladesh. 1 Usage context: background mention, primary mention, supporting mention.

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Input: Figure 19: Trust and Conﬂict in the Cross Section The problem with a lack of trust and strong group identities is that they penetrate and pervert formal institutions. The ethnic politics analyzed by Burgess et al. (2015) is just one example. Shayo and Zussman (2011), for example, use data from Israeli small claims courts to show that Arab and Jewish judges displayed signiﬁcant judicial ingroup bias. Furthermore, this bias is strongly associated with terrorism intensity in the vicinity of the court in the year preceding the ruling. Conﬁdence-building is also a crucial ingredient for the establishment of a fertile investment climate, which in turn is a trigger of economic development post conﬂict. This is the core message of the World Bank Report by Mills and Fan (2006). An important role of increasing trust doubtlessly goes to the media. It has been shown, for example, that hate radio in Rwanda played a critical role in the extent of ethnic violence during the genocide. 59 Other research has shown that media coverage can have strong eﬀects on political preferences more generally. 60 Perhaps the most direct proof of the crucial role played by the media in the post-conﬂict situation comes from DellaVigna et al. (2014). The authors exploit variation in radio reception of na- tionalistic Serbian radio in border regions in Croatia.

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Input: 10 inflow). We then use the composite variable as an instrument to identify the causal impact of refugee presence on livelihood diversification and commercialization in host communities. Figure 2: Household livelihood strategy framework under refugee inflow Source: Adapted from Nielsen et al. (2013) and Walelign and Jiao (2017) 4. Data sources The major data source of the current study is the World Bank ’ s Development Response to Displacement Impacts Project (DRDIP) 12 baseline survey from Ethiopia. The Ethiopia DRDIP survey was administered between September 2017 and August 2018. The survey covers 113 Kebeles (wards) in 16 Woredas (districts) from the top five refugee-hosting regions in Ethiopia. The selection of the sample households follows stratified random sampling with proportion to size (the number of households) using Woredas as a geographic stratum. The sample originally comprised a total of 3, 390 households, who were selected using systematic random sampling within each Woreda. We used data from 3, 375 households, as 15 of them were excluded due to missing location information (GPS). Usage context: primary mention, background mention, supporting mention.

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Input: refugees and their host communities, this work aims to inform policies and operations (humanitarian actors, development partners, and government) to facilitate refugee integration and their lives, along with hosting communities. This report’s eight chapters aim to comprehensively provide an overview of SESRE results, with the final chapter highlighting policy implications. This Chapter 1 introduces the refugee situation in Ethiopia. Chapter 2 presents the sociodemographic profile of refugees and their hosts, including demographic characteristics, education, health, and living conditions. Chapter 3 provides an in-depth profile of jobs and livelihoods of refugees and their hosts, covering labor market outcomes for refugees inside and outside of camps and those of hosts living in the vicinity of refugees, as well as a subsection on labor market outcomes of youth. Chapter 4 dives deeper into refugees’ future aspirations and their feeling of personal control over their lives. Chapter 5 describes the welfare situation of refugees and their hosts by: (i) understanding different dimensions of welfare, such as monetary poverty, inequality, multidimensional poverty, food security, and shocks; and (ii) understanding determinants of welfare and estimating the cost to meet basic needs through a combination of assistance and some economic inclusion of refugees into national systems. Chapter

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Input:
Throughout the war, HLP rights violations has been one
of the main impacts, particularly related to

**secondary/unauthorized occupation, destruction,**

**and confiscation** . Absence of ownership documents
(either due to loss or verbal agreements) increased the
exposure to house, land, and property related
violations. In the case of youth, these risks are
enhanced, due to **lack of procedures to secure tenure**

**for youth when parents have died** .

Occupied I don't
know

**What is the status if your familys property?**

**54%**

Abandoned Destroyed Rented Confiscated

Family separation, lack of access to legal services,
informality on tenure, ethnic background,
discrimination, are some of the existing drivers for **additional HLP violations for youth** . The percentage of destroyed
properties documented by the survey raised additional concerns related to future restitution of HLP rights for young
people and the need to safeguarding these documents for transitional justice purposes.

Youth participating in the FDGs also mentioned:

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Input: that are at a maximum distance of 80 km from the 7, 547 clusters. 12 Figure 1 shows the locations of these refugee camps and clusters. Clusters are represented in green, while clusters in the vicinity of a refugee camp are represented in red. Refugee camps are designated with a red + sign. There are some important limitations associated with this data. First, the data only provides information on refugees residing in camps monitored by the UNHCR. In Figure B. 7, we combine the UNHCR refugee camp data on the annual number of refugees and the UNHCR official statistics on refugees (which includes people in refugee-like situations) at the country level. 13 Although the overall trends match, our constructed dataset clearly underestimates the true refugee population in Africa, which is not surprising since our camp-specific data does not contain dispersed refugees or refugees living outside of camps. While our data seem to represent quite fairly the number of refugees in camps, there is significant heterogeneity across countries. Based on the visual inspection of Figure B. 8, the quality of the refugee data appears to be less reliable for the following countries in our sample: Gabon, Mali, Senegal, and Togo.

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Input: Children and adolescents ’ long-term exposure to households with a more equalized division of domestic labor, as a result of violent or political conflict, warrants further investigation. 2. 3 Country contexts The countries with subnational regions covered in this study, using data from 2017 or 2018, are Ethiopia, Nigeria, Somalia, South Sudan, and Sudan. All are located in Sub-Saharan Africa, have undergone or are currently involved in armed conflict, and are affected by environmental issues such as drought, famine or flooding. Despite some commonalities, each faces a unique set of social, political and economic challenges, which cannot be accurately covered in this study. However, to contextualize the findings, a brief introduction of the country context is presented alongside the poverty estimates by the $ 1. 90 / day measure and the global Multidimensional Poverty Index (MPI). 3 3 An international measure of acute multidimensional poverty, aligined with the 2030 Agenda, that captures deprivations in health, education, and living standards for more than 100 countries (Alkire and Jahan 2018; Alkire, Kanagaratnam and Suppa 2020). Usage context: primary mention, background mention, supporting mention.

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Input: 12% 63% Labor force participation rate (relaxed) 72% 67% Unemployment (relaxed) 19% 75% Employment-to-population ratio 58% 17% Source: World Bank Staff based on SESRE 2023. Note: Labor force participation ratio is the share of working-age people who are engaged in the labor market, either employed or unemployed. Unemployment is the share of people participating in the labor force who are not employed. The “relaxed” definition of labor force participation includes anyone who is available to work. The “strict” definition of labor force participation includes only those who are available to work and also actively searching for work. Employment-to-population ratio is the share of working-age people who are employed. Jobs and Livelihoods 36 Occupational downgrading among the small share of OCP refugees who work is not explained by education, gender, and age. Another way to visualize the scale of occupational downgrading among refugees in Addis Ababa is to calculate how they should be distributed across occupations if they were in the same occupations as hosts within their education, gender, and age group. For example, suppose that among male hosts under age 25 with primary education, 70 percent work in elementary occupations and 30 percent in crafts and related trades. Imagine taking

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Input: Annual surveys under the project are designed to be nationally representative and use the same sampling frame as the national statistics office's multi-purpose household survey, enabling comparison of project-area trends with national trends. The first annual survey field work was completed in March, covering 4,800 households across the six project provinces. Preliminary review of the annual survey data found data quality to be high, with item non-response rates below 2 percent on all key variables. Cleaned data will be available to the evaluation team by end of April.

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Input: 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. Usage context: supporting mention, background mention, primary mention.

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Input: 4 Internal Conﬂicts and Refugees A particularly serious aspect of internal conﬂicts is the human suﬀering they generate. This is not only those who are killed or injured in conﬂict but the large number of people who are forced to leave their homes. The issue of refugees has received particular attention in Western media in recent years as refugee ﬂows from Northern Africa, the Middle East and Afghanistan are increasingly reaching Europe. These refugee streams are linked to a severe humanitarian crisis with considerable funding needs for international donors and heavy strains on host countries. 21 The current refugee crisis, however, is in no way unique. Civil war has always been closely linked to humanitarian crisis and refugee streams are one way to capture this. In this section we provide a cross-country analysis aimed at investigating how the stock of refugees evolves when a civil conﬂict hits a country. In the analysis we will focus entirely on showing changes in the stock of refugees across time to illustrate the dimensions involved. We will base our later analysis on these population movements. We exploit country-level data gathered from several sources. Data about refugees is provided by the UNHCR Population Statistics Database. The database provides in- formation about UNHCR ’ s populations of concern from the year 1951 up to 2014. Usage context: primary mention, supporting mention, background mention.

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Input:
"Life in Transition Survey, Transition Report 2020-2021: The State Strike Back", [https://www.ebrd.com/publications/transition-report-](https://www.ebrd.com/publications/transition-report-202021) [202021.](https://www.ebrd.com/publications/transition-report-202021)

"Strengthening the business environment for productivity convergence," in OECD Economic Surveys: Romania 2022, OECD Publishing, Paris, [https://doi.org/10.1787/63318cf5-en.](https://doi.org/10.1787/63318cf5-en)

_Encuesta_ _Dirigida_ _a_ _la_ _Población_ _Venezolana_ _que_ _Reside_ _en_ _El_ _País_ _(ENPOVE)_ is a special ized survey of Venezuelans living in Peru conducted by the National Institute of Statistics (INEI) in December 2018. The sample covers five main urban areas in the country where Venezuelan immigrants were most likely to be present. The survey collects data on the immi grant's origin, migration date, and details on their current employment. Importantly, a full module asks about the immigrant's experiences with locals, which includes questions about discrimination and hostile attitudes towards them. The respondent's current location is iden tified down to the _centro_ _poblado_ level, which roughly corresponds to an urban neighborhood or a rural town.

_Encuesta_ _Nacional_ _de_ _Hogares_ _(ENAHO)_ is the Peruvian version of the Living Standards Measurement Survey, e.g. a nationally representative household survey collected monthly on a continuous basis. For our analysis, we use data from January 2007 to December 2020. The survey covers a wide variety of topics, including basic demographics, educational back ground, labor market conditions, crime victimization, and a module on respondent's percep tions about the main problems in the country and trust on different local and national level institutions. Observations are also spatially identified at the municipality level, but here we focus on variation in the Venezuelan share of the population at the province level, of which there are 196, as these are best representative of local labor markets.

_Latin_ _American_ _Public_ _Opinion_ _Project_ _(LAPOP)_ is a opinion survey conducted bi-annually in all countries in Latin America and designed to be representative of urban populations. This was fielded in Peru in 2010, 2012, 2014, 2017 and 2019 and consists of about 2,000 observations from mostly urban areas. The survey questions are centered around politics,

Life in Transition Survey
ENPOVE
ENAHO
LAPOP

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Input: Since the set of household members at baseline have subsequently moved, and usually not as a unit, the 2004 round results in more than 2, 700 household interviews (from the baseline sample of 912 households). Although the KHDS is a panel of respondents and the concept of a ‘ household ’ after 10-13 years is a vague notion, it is common in panel surveys to consider re-contact rates in terms of households. Excluding households in which all previous members are deceased (17 households with 27 people), the field team managed to re-contact 93 % of the baseline households. This is an excellent rate of recontact compared to panel surveys in low-income countries and high-income countries. The KHDS panel has an attrition rate that is much lower than that of other well-known panel survey summarized in Alderman et al. (2001) in which the rates ranged from 17. 5 % attrition per year to the lowest rate of 1. 5 % per year. Most of these surveys in Alderman et al. (2001) covered considerably shorter time periods (two to five years). Figure 1 charts the evolution of households from baseline to 2004. One-half of all households interviewed were tracking cases, meaning they did not reside in the baseline communities. Of those households tracked, only 38 % were located nearby the baseline community. Overall, 32 % of all households were not located in or relatively nearby the baseline communities. While tracking is costly, it is an important exercise because migration and dissolution of households are often hypothesized to be important Usage context: background mention, primary mention, supporting mention.

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Input: Aldo Morri for his excellent editorial support. Finally, we extend our deepest gratitude to the survey respondents for their willingness to share their experiences which has been instrumental in deepening our understanding of the challenges and needs faced by both refugees and host households. ACKNOWLEDGEMENTS ii Introduction E thiopia, with its long history of hosting refugees, is grappling with the complex challenges of accommodating close to 1 million refugees and asylum seekers. These come primarily from neighboring countries like South Sudan, Somalia, Eritrea, and Sudan housed in camps in mostly rural areas spread around the country near border areas. While Ethiopia has adopted progressive refugee policies, including the Comprehensive Refugee Response Framework (CRRF), challenges persist in translating these policies into tangible socioeconomic outcomes for refugees. Despite Ethiopia’s efforts to shift from a camp-based approach to a more inclusive model promoting self-reliance and integration, refugees live largely in camps, are reliant 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

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Input: First, I include a measure of whether citizens believe that a large portion of tax administrators is corrupt. Second, I in- clude a variable indicating whether citizens approve of how well their local government is handling the collection of license fees on bicycles, carts and barrows. 8 Third, both the size of a country and the size of the government may aﬀect a government ’ s ability to detect and punish evaders. I include the 7I also include a country-level indicator of government performance, the World Bank Governance indicator of government eﬀectiveness, in the model. This indicator measures perceptions of the quality of public services, the quality of the civil service and the degree of its independence from political pressures, the quality of policy formulation and implemen- tation, and the credibility of the government ’ s commitment to such policies (Kaufmann, Kraay and Mastruzzi, 2006, 4). This variable is not signiﬁcant at the p <. 05 level. 8I included two additional measures in the model neither of which were signiﬁcant at the p < 0. 05 level. One is a measure of citizens ’ approval of how well their local government council provides citizens with the information about the councils budget (i. e. revenues and expenditures). The other, the World Bank governance indicator, control of corruption, measures the extent to which public power is exercised for private gain, as well as capture of the state by elites and private interest (Kaufmann, Kraay and Mastruzzi, 2006, 4). 13 Usage context: primary mention, background mention, supporting mention.

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Input: Humanitarian organizations such as UNHCR and OCHA as well as international organizations such as IOM are also involved in the collection of data on IDPs, often involving international and local 59 OCHA is the part of the United Nations Secretariat responsible for bringing together humanitarian actors to ensure a coherent response to emergencies. See http: / / www. unocha. org /. 60 This section draws heavily on the “ Report of Statistics Norway and the Office of the United Nations High Commissioner for Refugees on statistics on refugees and IDPs ” presented at the UNSD in March 2015. 61 The number of countries where UNHCR exclusively collects data on refugees declined from 76 in 2010 to 72 in 2014, while the proportion of countries where refugee data were exclusively provided by governments gradually increased over the same period from 33 to 38 percent. In 2014, the proportion of countries where data were provided through collection conducted jointly by governments and UNHCR was 15 percent, while in the remaining proportion (13 percent), refugee data were provided exclusively by NGOs and other organizations. In 2014, more than 173 countries and territories provided data on refugees. Usage context: background mention, supporting mention, primary mention.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: This paper combines newly available data on the distribution of Syrian refugees across Turkey and the Turkish Labour Force Survey to assess their labor market impact. Syrian refugees are overwhelmingly employed informally, since they were not issued work permits, making their arrival a well-defined supply shock to informal labor. Consistent with economic theory our instrumental variable estimates, which also control for distance from the Turkish-Syrian border, suggest large-scale displacement of natives in the informal sector. At the same time, consistent with occupational upgrading, there are increases in formal employment for the Turkish- though only for men without completed high school education. Women and the high-skilled are not in a good position to take advantage of lower cost informal labor. The low educated and women experience net displacement from the labor market and, together with those in the informal sector, declining earning opportunities. Usage context: supporting mention, background mention, primary mention.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: The ESMF consultation process documented 14 community meetings across the project area, attended by a total of 1,847 participants including women (52 percent), youth representatives, persons with disabilities, and representatives of indigenous communities. Meeting summaries, attendance lists, and photographic evidence are appended to the ESMF in Volume II. All written feedback received during the ESMF public comment period has been reviewed, and responses are documented in the ESMF Consultation Report finalized in November.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input:
In addition to the publicly available imagery, NOAA has produced, especially for this paper, monthly frequency composites for the 2004 to 2013 period. These satellite-month datasets

from the labor force survey (LFS) ENOE. Specifically, we produce a quarter-year panel of

The national water commission (CONAGUA) provided us with three datasets: (i) Data on historical rainfall at the day-weather station level, this dataset spans the 1920 to 2015 period,

and contains the universe of weather stations. (ii) The weather station-month level triggers for Fonden eligibility. (iii) The mapping between municipalities and representative weather stations.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: The vulnerability of the Internally Displaced People in SSA has certainly been overlooked for too long, but the increased support provided by UNHCR is an encouraging but challenging sign in that respect. Figure 3. Refugees and Internally Displaced People in SSA, 2003 ‐ 2013 Source: Note: Refugee data are from the UNHCR statistical population online dataset, accessed in September 2014. Refugee data from 2007 to 2013 include people in refugee ‐ like situations (see note, Figure 1). The annual number of IDPs is collected from the IDMC (2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2012, 2013, 2014) annual reviews. Usage context: supporting mention, background mention, primary mention.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: MPI of IDP communities is considerably higher than that of the host communities, so it follows that the censored headcount ratios display a similar gap. The difference by indicator is particularly noticeable in the living standards dimension, where the electricity, cooking fuel, housing, and bank account indicators show over 34 percentage point difference between the censored headcount ratios for the IDP and host communities. Figure 1. Censored headcounts of each indicator in the MPI, by displacement status in Sudan (2018)

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

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Input: In particular we construct ∆ CEIdmt as the change in the conﬂict events index for district d between the quarter immediately prior to month m in year t from the previous quarter. 14 The second term on the right hand side ∆ luminositysmt is analogously constructed using the same lagged time periods. The third term AoCsmt is a series of Area of Control dummy variables, which capture who is in control of sub-district s in month m in year 12Syria is a unitary state, but for administrative purposes it is divided into 14 governorates, which are further divided into 65 districts and 281 sub-districts. 13As a robustness check, we also include month of the year ﬁxed eﬀects to pick up seasonal changes in migration patterns. 14Note that the conﬂict data is only available at the district level. 18 Usage context: supporting mention, primary mention, background mention.

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A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

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Input: 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. Usage context: primary mention, supporting mention, background mention.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: environment. Any issues discovered during these monitoring visits were brought to the attention of service providers and resolved swiftly in conjunction with the project coordination team at MoGD. Eligibility: The EPAG program was targeted to young women who: i) were age 16 to 27, ii) possessed basic literacy and numeracy skills, iii) were not enrolled in school within several months prior of the program initiation, and iv) resided in one of nine target communities in and around Monrovia. 6 These eligibility criteria stemmed from the project's objectives to reach young women at an early enough age to significantly improve the trajectory of their working years, to focus on girls who already had the basic literacy and numeracy skills needed to succeed in the labor market, and to avoid incentivizing applicants to drop out of school. Usage context: supporting mention, background mention, primary mention.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: as sold. Annexes 125 Table E.2: Food aid and consumption comparisons Items Quantity (per capita/year) Expenditure (per capita/year) SESRE UNHCR SESRE UNHCR Nonzero All Net of sold ration* Cereals/other cereals 23.2 186.1 175.5 493 12404 Wheat 60.5 133.2 116.6 1427 4710 Maize 39.6 125.5 118.3 312 4267 Rice 21.3 48.5 39.8 560 3392 Sorghum 12.7 132.8 125.7 4 5652 Pulses 7.1 18.9 17.5 248 1514 Vegetable oil/oil 3.7 9.7 8.9 627 1774 Salt 1.6 7.9 7.7 57 232 Biscuits 5.4 4.5 4.4 16 112 Dates 0.0 4.2 3.7 0 . CSB+ 19.3 15.0 14.0 36 532 Other food 565.9 - - 2558 Peas 5.7 - - 137 All cereals 78.2 - - 2994 All pulses 8.2 - - 385 Aggregate ration/month 46.7 - - Source: UNHCR and World Bank Staff based on SESRE 2023. Valuing food aid quantities with prices from SESRE suggests that if UNHCR food aid quantities were received/ reported by refugees, refugees’ food expenditures would be much more comparable to those of hosts (Based on this information, we compare how the distribution list shared what refugees should have received to what they reported regarding food consumption. The results show that refugees reported quantities lower than UNHCR food

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: Source: UNHCR Statistical Online Population Database Note: Only includes refugee situations greater than 25, 000 people. Excludes high-income (OECD and non-OECD) countries. Excludes Palestinian refugees under UNRWA ’ s mandate. Usage context: primary mention, background mention, supporting mention.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

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Input: 40 Sub ‐ Saharan Africa 8604000 5895000 7055000 5406100 5068000 N. A. MENA 6230000 8000000 6675000 8592900 10892000 N. A. Asia and Pacific 4325000 2405000 3392000 2128800 5490000 N. A. (excl. Australia, Japan, New Zealand) Americas 1126000 1280000 2176000 2900000 3661000 N. A. (excl. North America) Note: Refugee data are from the UNHCR statistical population online dataset, accessed in September 2014. Refugee data from 2007 to 2013 include people in refugee ‐ like situations (see note, Figure 1). IDP data from 1990 to 2008 are aggregated based on Center for Systematic Peace (http: / / www. systemicpeace. org /). As indicated in Figure A1, these data are much lower compared to those provided from 2003 by IDMC but provide a longer time series. UNHCR assisted ‐ IDP are compiled based on several UNHCR (1995, 1996, 2007, 2008, 2009, 2010, 2011, 2012, 2013, and 2014) reports. UNHCR ‐ assisted IDPs are only IDPs who are protected / assisted by UNHCR. These are also not necessarily representative of the entire IDP population in a given country. Many of the world's IDP situations are not covered by UNHCR and are thus not reflected.

UNHCR statistical population online dataset

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

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Input: Addis Ababa. Many refugees report that social interactions and sharing resources with hosts is “not easy,” especially in the South Sudanese domain. Overall, 30 percent of refugees say it is not easy to have social interactions with hosts, and 34 percent report that it is challenging to share resources such as water and food. These rates fall to 21 for social interaction and 15 percent for challenge in sharing resources in the South Sudan domain. On the other hand, refuges do not report that it is difficult to conduct market interactions. Country-wide, the relationship between integration outcomes and demographic characteristics is complex. More-educated male refugees are more likely to have Ethiopian friends, but this does not appear to improve ease the creation of social interactions or sharing resources with hosts. The results in Column 2 of Annex D, Table D.19 show—controlling for other characteristics, including region and year of arrival—that refugee men are 6.7 percentage points more likely to have an Ethiopian friend than refugee women, and those who completed secondary education are 22 percentage points more likely to have an Ethiopian friend. However, no significant difference exists in the ease of which these groups find it to have social

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: 11 there is another data source that provides independent information on conflict events. The Uppsala Conflict Data Program, Conflict Encyclopedia Database (UCDP) provides similar information that spans the time period of interest. In contrast, UCDP data is not available for Liberia- so each country draws on similar but distinct data set to incorporate independent information about conflict intensity. The study data set contains one observation for every woman in the DHS individual recode, i. e., the woman level data and variables showing the annual number of ACLED or UCDP events and fatalities beginning in the year the woman was interviewed up to 10 years preceding the survey. Providing conflict for the 10 years preceding the DHS survey is key to the methodology and helps establish temporality in how conflict may affect IPV outcomes. A 10-year period was chosen because this captured hostilities from both Liberian civil conflicts and allowed the data set to reflect the long-standing impact of the conflict in each country. Each conflict data set used is described below. Uppsala Conflict Data Program (UCDP) Data- Colombia The Uppsala Conflict Data Program (UCDP) Georeferenced Event Dataset is an event data set that disaggregates three types of organized violence: state-based conflict, non-state conflict, and one-sided violence. Usage context: supporting mention, primary mention, background mention.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source