Input: The countries that are the largest source of refugees include: Afghanistan, Syria, Somalia, South Sudan, Sudan, Democratic Republic of Congo, Central African Republic, Iraq, Myanmar, and Eritrea (UNHCR, 2017). These countries account for the vast majority of refugees worldwide. We will also consider three countries in Europe that are an important source of asylum seekers in Europe, and whose recognition rate is low, and account for many returnees – these are Kosovo, Serbia and Albania. Is return possible and safe, and if so, does the economic situation bode well to provide essentials, namely a job, housing, education and reliable public services? It is helpful to identify three groups of countries: ones that are still mired in war and / or high ‐ intensity civil conflicts, countries where medium ‐ intensity conflict persist and are already in the process of rebuilding, and countries which are not in conflict. According to the Armed Conflict Survey (IISS 2017), high ‐ intensity conflict is defined by frequent (daily) armed clashes between governments, government forces and insurgents, or among non ‐ state armed groups that control territory. Usage context: background mention, primary mention, supporting mention.

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Input: (a) High frequency sample surveys using smartphone and cellular technologies. For example, a high-frequency survey initiative in Somalia employs a dynamic questionnaire loaded onto smartphones, which enables data to be collected from household interviews in 60 minutes. This approach was developed to overcome the challenges of insecurity, limited data gathering capacity and budgetary constraints. (b) The use of mobile phones to conduct surveys or follow up interviews following face-to-face household surveys. For example, a Bank paper on the impact of the 2012 crisis in Mali on IDPs, refugees and returnees used information from a face-to-face household survey as well as follow-up interviews with its respondents via mobile phones. This combination provided a mechanism to monitor the impact of conflict on hard-to-reach populations who at times live in areas inaccessible to enumerators. And in Sierra Leone and Liberia, the Bank supported the use of mobile phones to collect key socio-economic data on the effects of the Ebola virus. (c) Crowdsourcing data on displacement. Platforms such as the Kenyan Ushahidi has crowd- sourced data on displacement in Kenya and eastern DRC by encouraging IDPs and host communities to report incidents using their mobile phones or the internet, including information about living conditions. The platform references these reports geo-spatially. (d) Geo-mapping of data on displaced populations and affected host communities.

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Input:
The algorithm is fed with 24 different satellite bands, measuring surface reflectance in the visible and infrared spectra, topographical data from the Shuttle Radar Topography Mission (SRTM), and road network data from the OpenStreetMap project.

Information on aquaculture production in Vietnam's two main river deltas was obtained from two data
sources. In the Red River Delta, a vector dataset of the locations of individual aquaculture ponds was used.
It was created and provided by researchers of the German Aerospace Center (DLR). As part of their
methodology, an algorithm extracted individual ponds from time series of radar satellite data. Specifically,
83 Sentinel-1 scenes from between 2014 and 2016 were processed. Radar data, such as the observations
from the Sentinel-1 series of satellites, enables the detection of water-covered surfaces irrespective of
daylight and clouds.

Overall, an
accuracy of 0.84 is reported for pond detection in the Red River Delta (Ottinger et al. 2018). In the Mekong
Delta, a vector dataset containing the locations of individual aquaculture ponds was provided by SWIRR.

Shuttle Radar Topography Mission
OpenStreetMap project

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Input: Not all cross-sectional studies have multiple rounds of comparable data, covering the period before and after the crisis. When comparing impacts between locations within a country, cross-sectional data also usually does not allow to capture impacts on those who moved out and to differentiate impacts between those who were already there before the shock and those who moved in afterwards. Some of the models based on administrative areas qualify as spatial econometrics models in that they use estimation methods that derive from this literature and are published in spatial econometrics journals. Studies that compare different areas within a country are not only confronted with the potential endogeneity of the size and skill composition of the inflow and the choice of destination, but also with the endogenous reactions of the host community. Local workers might respond to the labor supply shock by dropping out of the labor force, investing in education, occupational upgrading or moving to other areas and diffusing the impact of the inflow. Even if local workers do not respond to wage variations, capital flows may equalize capital / labor ratios within the country, labor-intensive industries might move towards the regions with a high refugee or IDP influx or firms might use more labor-intensive production technologies. The reactions of the host country workers, investors and firms are medium-to long-term in nature and will play less of a role in the short-term if there are large, sudden and geographically concentrated inflows. Some of the papers explicitly analyze these potential channels, notably migration of local workers, and, to a lesser extent, occupational upgrading. Outmigration of hosts is a critical complement to the labor market analysis and excluding this outcome can lead to an underestimation of the impacts of forced displacement on the labor market outcomes of natives. The papers we reviewed that looked at tasks complexities and the question of substitution vs complementarities between refugees and natives found occupational upgrading among Usage context: primary mention, background mention, supporting mention.

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Input: Figure 5: Significant Historical Crises as a Share of Total Forced Displaced 1991 – 2015 Source: UNHCR Statistical Online Population Database, UNHCR Global Trends 2015 Note: Includes IDPs protected or assisted by UNHCR, asylum-seekers and refugees. Excludes IDPs not protected or assisted by UNHCR and Palestinian refugees under UNRWA ’ s mandate. Figure 6: Top 15 Countries of Origin end-2015 Source: IDMC Global Report on Internal Displacement 2016, UNHCR Global Trends 2015, UNRWA A small number of countries carry the burden of hosting the majority of refugees. Historically since 1991, 15 asylum countries, overwhelmingly in the developing world, have hosted more than 50 percent of refugees and asylum-seekers (see Figure 7). 44 By the end of 2015, while almost all countries in the world were hosting refugees, the burden was unevenly shared (see Figure 8). Only seven countries hosted more 44 Major host countries are identified based on the cumulative number of refugees and asylum-seekers over the period 1991-2015.

UNHCR Statistical Online Population Database

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Input: 15 4. 1. 2. Empirical strategy In order to make use of the retrospective information on school attendance provided in the dataset, we have constructed what we have called an ‘ ad hoc panel ’, whereby we exploit the time-variation of the variables of interests (age, attendance status and grade attained by the respondents) by reshaping the cross-sectional structure of the TLSS 2001 dataset. In this way, we are able to obtain observations for each individual over three academic years. All key education variables are time- variant, while other individuals and households characteristics are time-invariant. Within these three years, we focus our analysis on individuals that were of primary school age (between 7 and 12 years old) in each year. In practice, we keep all children aged at minimum 7 years old in 1998 and at maximum 12 years old in 2000. As a consequence, our panel data contains children aged 8-11 years in 1999, the year of the violence. 11 Since we are interested in looking at different effects across groups of individuals, we have split the sample between boys and girls and between younger children (aged 8-9 in 1999) and older children (aged 10-11 in 1999). Usage context: primary mention, supporting mention, background mention.

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Input: Respondents who were untraced were much more likely to be residing outside Kagera (43 %) compared to their counterparts who were re-interviewed (8 %). The consumption data come from an extensive consumption module administered in 1991 and again in 2004. The consumption aggregate includes home produced and purchased food and non-food expenditure. The non-food component includes a range of non-food purchases, as well as utilities, expenditure on clothing / personal items, transfers out and health expenditures. Funeral expenses and health expenses prior to the death of an ill person were excluded. Monetary levels were adjusted to account for spatial and temporal price differences, using price data collected in the Kagera survey in 1991 and 2004, and, for households outside Kagera, data from the National Household Budget Survey. Consumption is expressed in per capita, per annum terms. The poverty line is set at TZS 109, 663, calibrated to yield for our sample of respondents who remained in Kagera the same poverty rate as the 2000 / 1 National Household Budget Survey estimate for Kagera (29 %). 4. Growth, Poverty and Physical Mobility in Kagera In this section, we discuss changes in living standards overall, and the changes for four mutually exclusive groups based on residence in 2004: (i) still residing in the baseline community, (ii) residing in a

National Household Budget Survey
Kagera survey

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Input: namely those refugees who arrived in Addis Ababa after November 2020. Data collection took place between November 2022 and January 2023. Sample population The SESRE covers three types of groups, all of which require a distinct sampling procedure:55 (i) refugees in camps; (ii) refugees out-of-camps; and (iii) host communities. This section discusses the sampling frames of each group. (a) Refugees in Camps The sampling frame for refugee camps is based on UNHCR’s proGRES database. The refugee camps were grouped into three domains based on the concentration of refugees from the three major origin countries: South Sudan, Somalia, and Eritrea.56 The first sampling stage divided each camp into enumeration areas (EAs). Based on the proGRES database, we created pseudo EAs by taking 150-200 Annex C: Survey Design and Methodology 54 Formerly the Household Consumption and Expenditure Survey and Welfare Monitoring Survey. 55 Prior to the sampling process, the survey team conducted a pre-sampling assessment by visiting the camps to verify on-the-ground conditions. 56 Refugees from Sudan were not included in SESRE as, at the time of sampling, there were less than 50,000 Sudanese refugees in Ethiopia and inclusion was not deemed cost effective. Annexes 93 households in a row from the

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Input: We, therefore, first examine whether or not there is structure, both, to selection into the treatment group and attrition, which could undermine our econometric approach, where we rely on difference-in-difference estimators. Imbalance between treatment and control groups could undermine the key assumption of parallel trends. For example, given that men and women face different barriers in the labor market, we should not expect employment to evolve in the same way for men and women after the treatment. We would expect to observe a difference-in-differences for a treatment group where women are more common than in the reference group, even without the program. To test for imbalances, we run a simple regression of treatment and attrition indicators at baseline on the socio-economic and demographic controls, GRIT indicators, self-reported optimism, employment status and risk. Table 4 (Column 1 for the treatment analysis, Column 2 for the attrition analysis) shows some signs of structure. In particular, host status and risk preferences are significantly different between treatment and control, with 9 For example, “ hummus ” is used to refer to chickpeas in general but can also be used for the dish involving mashed chickpeas, tahini, lemon and garlic in Lebanon. In other dialects, some qualifiers are required to specify this dish (e. g. hummus ne ’ em, or smooth hummus). This is akin to identifying a British or American individual using similar variations in foodstuffs such as courgette / zucchini; coriander / cilantro; etc. 10 Specifically, we regress variables with missing observations on the list of all variables with a complete record. We then use the predicted values from this regression to populate the missing variables. Where appropriate, predicted values are rounded to the nearest integer and within answer codes of that variable. In a second round, this process is repeated on the full set of actual and predicted values from the first stage. Usage context: supporting mention, background mention, primary mention.

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Input: These surveys are part of a long-term data collection effort by the research team (Vinck & Pham 2014) and were collected separately from the focus group discussions. The focus group discussions thus did not directly inﬂuence the design of the surveys, but rather directed the analysis strategy of the surveys that our team has collected at regular intervals in eastern DRC. The survey data are analyzed in two ways. First, 11 surveys collected between 2017 and 2021 8Eastern DRC is a site of ongoing violence, raising a number of ethical, methodological, and practical concerns about collecting data. We discuss the ethical protections we implemented when collecting this survey data in the Appendix, Section B. 9Territoires are sub-provincial administrative units. Additional details on the structure of administrative units are available in the Appendix, Section A. 1. 21

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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

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Input: The JLMPS sample is restricted, after matching it to the 2010 school census, to individuals born in Jordan who are aged 25 to 70 in 2010 and who have nonmissing information on age, subdistrict of birth, years of schooling, father ’ s schooling, mother ’ s schooling, and local supply of schools in subdistrict of birth. 9 These exclusions resulted in a sample of 4, 139 males and 4, 131 females, which are referred to as the male and female full samples, respectively. 7. Because of the absence of annual estimates of subdistrict populations, the population used to normalize the supply of schooling at the subdistrict level is the 2004 population of the subdistrict. There are 86 subdistricts in Jordan. If subdistrict populations are growing at different rates, this could introduce some measurement error of the true supply of schooling available to different cohorts. 8. Secondary schools include both general and vocational secondary schools. Public schools include schools under the jurisdiction of: (i) Ministry of Education, (ii) Ministry of Higher Education, (iii) Ministry of Defense, (iv) Ministry of Social Development, (v) Ministry of Religious Endowments (Awqaf), and (vi) UNRWA. 9. The original sample size of all individuals who are aged 25 to 70 years in 2010 and are born in Jordan is 8, 312 observations. The sample restrictions on the missing values result in the exclusion of 34 observations (missing age), 1 observation (missing father ’ s schooling), and 7 observations (missing mother ’ s schooling).

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Input: B Description of Variable ’ s Construction This section describes how we constructed each of the variables in our main analysis. B. A Outcome Variables Outcome variables were constructed using the data from the Afghanistan Welfare Moni- toring Survey conducted for this study in the fall of 2021. • Integration: we measured the integration dimension with three different types of questions. The first included the individual reported answer from a 1 to 5 scale, where 1 means strongly disagree, and 5 strongly agree of the following questions: (i) ” Would you feel comfortable if your child or grandchild were to socialize or be friends with children of Refugee community people? ”, (ii) ” Do you feel welcomed in this village / town / city? ”, (iii) ” Do you think that everyone living in this village / town / city feels like they are a part of this village? ”. The second, included the answer to the following question ” On a scale of 1 to 10, with 1 being not very much to 10 very much, how much do you feel that Tajikistan is your home? ”, and the third, the total number of refugee, and Tajik friends among all of their friends, respectively. Usage context: background mention, primary mention, supporting mention.

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Input: C Details on outcome measures Outcome Variable Descriptions Psychological Well-being PHQ9 The standardized total score of 9 questions from the Patient Health Questionnaire-9 (PHQ9) Life Satisfaction Index A standardized average of survey responses to four questions from Di- ener ’ s standardized scale, responses made along a seven-point Likert scale. Stress Index The standardized total score from three elements of adapted from the Cohen Stress scale. “ How many of the last 7 days have you [been able to fall asleep peacefully / felt nervous / felt frustrated]? ” Sociability (Total) The total number of conversations in the past day with adults. Sociability (Positive) The total number of conversations in the past day with adults that the respondent felt were positive. Self-Worth Index The standardized total score from the responses on a scale from 1 to 10 to two questions: “ Think of a person you know who you most respect and who brings greatest value to your [family / community]. Usage context: supporting mention, background mention, primary mention.

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Input: 7 Database. Where both censuses and population registers are available, censuses receive priority. Censuses, generally conducted decennially, are retrospective tools for surveying an entire population (or in some cases, a representative sample) at a single point in time. In addition to their universal coverage, their greatest strength is the inclusion of questions on place of birth and nationality. Censuses also typically aim to enumerate the resident population, whether documented or undocumented (Bilsborrow and others 1997). So although some migrants have a strong incentive to provide false information to enumerators, many undocumented migrants will be captured in these matrices. 7 The size and scope of the census questionnaires vary enormously, both over time and in different destination countries. And there is potential variation in the quality of censuses both across countries and over time. Richer countries have many resources at their disposal to design questionnaires, train interviewers, employ statisticians, and disseminate results. Researchers have little choice but to accept the data at face value. However, where the underlying census is clearly substandard (when there are errors that are obviously not coding errors or not easily corrected), these data are omitted from the analysis. Popular in many parts of Europe, population registers are continuous reporting systems providing up-to-date demographic and socioeconomic information for everyone surveyed. Usage context: primary mention, background mention, supporting mention.

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Input: Host response to “Would you feel comfortable having a refugee as a neighbor?” by gender ��������������������������������������� 65 Figure 7.5: Share of hosts who agree refugees should have access to... 66 Figure 7.6: Host beliefs about refugee impact in Ethiopia ......................... 66 Figure 7.7: Negative experiences due to refugees �������������������������������������� 66 Figure 7.8: Positive experience due to refugees ����������������������������������������� 66 Figure 7.9: Are most Ethiopians/refugees in Ethiopia trustworthy? .......... 67 Figure 7.10: Host attitudes index................................................................... 67 Figure 7.11: Host attitudes index by gender ������������������������������������������������� 67 Figure 7.12: Share with family or friends in Ethiopia ������������������������������������� 68 Figure 7.13: Share with friends in Ethiopia by demographic group ............. 68 Figure 7.14: Share of refugees who think interactions with hosts are “easy to do” ........................................................................... 69 Figure 7.15: Who do refugees rely on in times of need �������������������������������� 69 Figure 7.16: Share of refugees who agree they are “culturally similar to hosts”....................................................................... 70 Figure 7.17: Share or refugees involved in a community representative body 70 Figure 7.18: Share or refugees engaged in a community representative body by demographic group ���������������������������������������������������� 70 Figure 7.19: Discrimination and harassment ������������������������������������������������ 71 Figure 7.20: Discrimination and harassment by demographic group ....... 71 Figure D.1: Age group by

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Input: 26 Source: Listening to Displaced People Survey, 2014. 95 % of the refugees in Mauritania envision an independent or autonomous North and 26 % of the refugees in Mauritania even state the independence of Azawad (= the north) as a main condition for returning home. Stark differences can also be observed with regard to the discussion around a possible federalist solution for the North that was ongoing when the monthly phone interviews were conducted in October. As illustrated in the Figure 20 below, 80 % of the refugees in Mauritania support a federalist solution, while the majority of IDPs, returnees and refugees in Niger are not in favor. Of those who do not support a federalist solution (96 % of the IDPs, 88 % of the refugees in Niger and 95 % of the returnees), the majority of IDPs (61 %) and returnees (70 %) as well as 38 % of the refugees in Niger suggest decentralization as a possible solution to resolve the conflict. 13 % of the refugees in Niger also mention war and 27 % the integration of the North. Nonetheless, 49 % of IDPs, 86 % of returnees and 89 % of refugees believe a stable and sustainable peace accord can be achieved. by 4 % of the population living Timbuktu, 2 % in Gao and nobody in Kidal.

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Input: 28 In section three of this study, we could not find taxes and regulations among the potential barriers to sales and employment growth that clearly separated the ups from the downs in the formal sec- tor. We also showed that the large sector has become a smaller share of the economy rather than a bigger share due to self-employment growth and due to the process of de-industrialisation. In substance, the CIS-7 may fit the developing countries scenario better than the transitional countries scenario in the Schneider and Klinglmair (2004) regressions. If this is the case, we should expect that the growth of the informal sector negatively contributes to growth. The data we have do not contradict this hypothesis given that the shadow economy has been on the rise during the recession period and has stabilised during the growth period. This digression on informality suggests that self-employment may partially act as an host to in- formal and illegal activities especially during recessions where self-employment may constitute a refuge for small informal and illegal businesses. Self-employment is also evidently a sector of ne- cessity for those who wish to keep health and pension records alive and do not want to formally register anywhere else. In times of growth this sector may instead function as a first step to for- mality, an entry gate to the formal sector given its lower entry barriers and taxes. Usage context: primary mention, supporting mention, background mention.

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Input: The UNHCR data identify principal applicants for each household and our analysis examines differences in household poverty between households with a female rather than male principal applicant. 6 The principal applicant is the person who receives assistance from UNHCR for the family and is self ‐ selected or selected by the family. This definition of female headship has advantages over the way that household headship is commonly identified in household surveys. An often ‐ noted drawback of the headship variable is that female headship may reflect the enumerators ’ perception about who should be considered a family head rather than who has the most responsibility for the family ’ s welfare in practice. 7 Social norms can also affect whether female respondents self ‐ identify as household heads. For example, some Eritrean returnees who would in other cultural settings be regarded as de jure female headed (single mothers, widows, divorcees, separated women) reported being male ‐ headed. Other Eritrean female returnees who would be considered de facto heads reported headship by absent husbands or male relatives (Kibreab, 2003). Our approach is therefore to distinguish between different types of female and male principal applicant households, using a typology that reflects some of the indicators of vulnerability used by UNHCR. We find that distinguishing between different types of female principal applicant households is important in the setting of Syrian refugees in Jordan. Usage context: background mention, primary mention, supporting mention.

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Input:
Data sources: UNHCR PRIMES, UNHCR Resettlement Statistics Report.   For more information or to contribute, please contact UNHCR RBSA DIMA (rsarbdima@unhc

**1,729**

**154**

**57**

**53**

**34**

**13**

**12**

**4**

**3**

**2**

**COD**

**BDI**

**SOM**

**RWA**

**TUR**

**ZAM**

**ETH**

**UGA**

**ANG**

**AFG**

**COD**

**BDI**

**SOM**

**RWA**

**ETH**

**PAK**

**TUR**

**CAR**

**BOT**

**ERT**

**3,619**

**263**

**235**

**220**

**40**

**36**

**19**

**14**

**8**

**8**

UNHCR PRIMES
UNHCR Resettlement Statistics Report

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Input: We only found reliable approximations from the International Displacement Monitoring Center (IDMC) between 2003 and 2013. According to IDMC, there were about 12. 5 million internally displaced people in SSA at the end of 2013 (IDMC 2014), more than one third of the total number of IDPs and more than tripling the number of refugees in SSA. Although the number of IDPs in SSA is the highest since 2007, the share of IDPs in SSA has been decreasing from 53 % in 2003. Usage context: background mention, supporting mention, primary mention.

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Input: 33 Ratha, D., and W. Shaw. 2007. ― South-South Migration and Remittances. ‖ World Bank Working Paper 102, World Bank, Washington, DC. United Nations Statistics Division. 1998. Recommendations on Statistics of International Migration Revision 1. New York: United Nations. United Nations, Department of Economic and Social Affairs, Population Division. [2008]. United Nations Global Migration Database. New York: United Nations. http: / / esa. un. org / unmigration — — —. 2006. Trends in Total Migrant Stock 1960 – 2000, 2005 Revision. Database. POP / DB / MIG / Rev. 2005 / Doc. New York: United Nations. — — —. 2009. Trends in International Migrant Stock: The 2008 Revision. Database. POP / DB / MIG / Stock / Rev. 2008. New York: United Nations. http: / / www. un. org / esa / population /. — — —. 2010. ― World Population Prospects: The 2009 Revision, Highlights ‖, Working Paper No.

United Nations Global Migration Database

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Input: The GBV Action Plan specifies a case management protocol that must be followed for all SEAH allegations regardless of whether the alleged perpetrator is a project employee. The protocol prohibits confrontation between the alleged perpetrator and survivor, requires referral to a designated survivor support specialist within 24 hours of a report being received, and mandates that case management records be stored separately from the project's general MIS to protect survivor confidentiality. The PIU's social development officer is the designated GBV focal point responsible for implementing the protocol.

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Input: Sources of information This work includes a descriptive analysis that allows us to identify how the prevalence of non- standard employment (NSE) has evolved in the last two decades in different regions of the planet, as well as the evolution of the profile of workers in those roles, in terms of their educational level, salary per hour, and type of tasks performed. This analysis was based mainly on periodic surveys of households that included information regarding the employment and educational situation of individuals. Although the denomination of this type of surveys varies from country to country, in all the cases analyzed there is usually a survey of annual or higher frequency that includes information required to identify the labor status of the individuals as well as to analyze the salary profile and education of the employed. However, it should be noted that the identification of the type of work relationship (standard or non- standard) is frequently limited in these data sources. Indeed, it is only possible to identify part-time employment and temporary employment (not in all cases) within the non-standard forms of employment mentioned in the previous section. Usage context: primary mention, supporting mention, background mention.

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Input: using the Washington Group Short Set on Disability. 11 Sharing a home is common, likely as an economic coping mechanism, with on average of 1. 3 families living in the same house. Housing quality is low, with most houses in some state of disrepair or incomplete construction. Table 1 also illustrates descriptive statistics for the treatment versus control households to as- sess balance across groups, where the third column presents a mean difference test. Respondents across the study arms are largely balanced by age (with an average age of 34 years), marital status (84 % married), and incidence of a disability (Panel A). There is a slight imbalance in the share of respondents who are female, with the proportion slightly higher in the control group. Moreover, average household size is just above ﬁve members, with nearly three children on average, and these are balanced between treatment and control, as is the number of families per residential unit (Panel B). Refugee households in the sample face challenging and precarious housing conditions, but these characteristics are generally balanced across groups (Panel C). For example, only 66 % of households have access to piped water, 22 % have functional windows, and 44 % completed ﬂoors. Usage context: background mention, supporting mention, primary mention.

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Input: Our analysis exclusively uses data from the 1951-2015 UNHCR Population Statistics Reference database (extracted September 18 2015). Data were provided for 173 countries: 77 percent of these data were based on individual refugee registration, 13 percent on estimates, 5 percent on combined estimation and registration, and 5 percent on other sources. The data are structured as follows: for each situation, the database records annual numbers of persons of concern, which comprise “ Refugees (including refugee-like situations) ”, “ Asylum seekers ”, “ Internally Displaced Persons ”, “ Returnees ”, “ Stateless ” persons, and “ Others of concern ”. A situation is a pair country of origin / country of destination. For example, Somali refugees in Kenya account for one situation, Somali refugees in Ethiopia for another, and South Sudanese refugees in Kenya for yet another. Furthermore, a situation is considered major if it involves more than 25, 000 people. It is referred to as protracted if it is major for at least 5 continuous years. The database, and therefore our analysis, is limited to refugees under UNHCR protection. It does not include asylum seekers, i. e. individuals who have sought international protection under the 1951 Convention but whose claims for refugee status have not yet been determined, and persons in “ refugee-like situations ”, i. e. individuals outside their country or territory of origin who face protection risks similar to those of refugees, but for whom refugee status has, for practical or other reasons, not been ascertained (e. g., undocumented Rohingya originating from Myanmar 4

UNHCR Population Statistics Reference database

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Input: appear to be a relationship between perceptions of the helpfulness of donors and non-state actors and the willingness to defer to the police and to the courts. Individuals who believe that donors and non-state actors exert too much, rather than, too little inﬂuence over one ’ s government is associated with the willingness to defer to the court and to the police. Findings also suggest that citizens who believe non-state actors are responsible for provid- ing law and order are less likely to be willing to defer to the police and to the courts than respondents who believe the state is responsible for providing law and order. 7. 4 Conclusion This paper demonstrates that the logic of the ﬁscal contract is relevant to a wide variety of contemporary African states. Findings from a cross-national analysis of survey data from Africa link citizens ’ legitimating beliefs — in- dicated by a willingness to defer to the tax department, the police and the courts — to a government ’ s fulﬁllment of a ﬁscal contract. Citizens who are satisﬁed with their government ’ s provision of services and goods are more likely to be willing to defer to the tax department, courts and police than citizens who disapprove of government service provision.

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Input:
Coastline changes in the Mekong Delta, including Ho Chi Minh City and Bà Rịa-Vũng Tàu, were evaluated
based on data provided by the Viet Nam Disaster Management Authority in vector format [2] . By analyzing
the coastline in 1988 and 2015 in imagery from Landsat satellites, sediment changes in this period could
be quantified.

Similarly, coastal erosion data in the provinces further north were developed by companies Deltares and
Royal Haskoning DHV (Deltares at al. 2017). Coastline changes in the period between 1990 and 2015 were
detected automatically based on imagery from Landsat and Sentinel satellites. In this vector format
dataset, average erosion or accretion is available by coastline segments with a length of 500 meters.

To analyze this hazard, a dataset in raster format describing the worst saline intrusion event in 2016 was provided by the (Southern Institute of Water Resources Research (SWIRR). With a resolution of about 50 by 50 meters, it shows the salinity level at each point in the delta during the 2016 event

The exposure of various types of agricultural production and urban areas is estimated based on land use
data with a very high spatial resolution. This dataset was developed by the Japanese Aerospace Exploration Agency and is openly and freely available online (JAXA EORC, 2018).

The land use map provides a fine-grained overview of land use for all of Vietnam for 2015, for northern regions and for central and south Vietnam in 2017.

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Input: 16 is the number of children born in the five years prior to the data collection. In the 2000 RDHS, this corresponds to the period between May 1995 and June 2000. This time span will be compared to the period between May 1987 and June 1992, when data collection for the 1992 RDHS began. Similarly, in the pooled 1992-2005 data, the time span of interest is the ten years prior to the starting date of the 2005 RDHS, which is the period between May 1995 and February 2005. This corresponds to the period from September 1982 to June 1992 in the 1992 RDHS. To explore the marriage market effects of conflict on fertility, the following equation is estimated: Ki = α0 + β1Xi + β2D + β3R + β4Year + β5Conflicti + β6Conflicti x Year + μi (1b) which additionally includes a time dummy Year for the survey year and an interaction term between the proxy for conflict exposure Conflicti and the time dummy. The estimated coefficient β6 captures the impact of actual conflict exposure on fertility after the genocide relative to women with similar risk of exposure to conflict before the genocide. Usage context: supporting mention, primary mention, background mention.

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Input: 2 Over the past three or four decades, the Arab world has experienced a massive expansion in educational attainment. According to the Barro and Lee educational attainment dataset, seven out of the top 20 countries in terms of increase in number of years of schooling from 1980 to 2010 were Arab countries (Barro and Lee 2013). 1 Jordan, the subject of this paper, had the seventh highest increase in educational attainment in the world, with an increase of about five years in the average years of schooling over the period. This increase is widely believed to be attributable to a massive public investment in the supply of schooling in the postindependence period in the context of a state-led development model, which virtually guaranteed employment in the public sector for graduates (Assaad 2014; Saleh 2016). The rapid increase in educational attainment has continued unabated despite the fall in returns to education that accompanied the demise in the state-led model and its employment guarantee schemes (Pritchett 2001). A slew of recent literature on the drivers of the Arab Spring protests, some of which occurred in Jordan, has identified the low economic returns to this massive increase in education as the single most important cause of the uprisings (Goldstone 2011; Campante and Chor 2012a, 2012b, 2014; Sanborn and Thyne 2014). Usage context: background mention, supporting mention, primary mention.

Barro and Lee educational attainment dataset

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Input: 7 Figure 1: Map of regions in Ethiopia, location of refugee camps, and refugee source countries. Source: Database of the Global Administrative Areas (GADM) (https: / / gadm. org / data. html, accessed on November 20th, 2020) In Ethiopia, the Refugees and Returnees Services (RRS, former Agency for Refugees and Returnees Affairs (ARRA)) is responsible for managing refugee camps and its oversight by making sure that the commitment of the federal government is met (Nigusie and Carver 2019). Except for Eritrean refugees, most of whom are eligible for out of camp policy, arriving refugees, at the time the data was collected, were allocated to one of the 26 refugee camps spanning the five refugee hosting regions. Refugees living outside of camps represent about 10 percent of the refugees in Ethiopia (Abebe et al. 2018). The allocation tends to be based on shared identity between the refugee and the host communities and the distance of the refugee camps from the border of the source country. The South Sudanese refugees are hosted in the refugee settlements in Gambella, except the few who were relocated to the refugee camps in Benishangul-Gumuz region. Most of these refugees arrived during the civil conflict in South Sudan in 2013 (Nigusie and Carver 2019).

Database of the Global Administrative Areas

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Input: 5. 5 Ethnic diversity at different levels Despite the use of sampling weights in the construction of the diversity indices, we have no guarantee that our diversity indices are representative at the local level. Although similar ethnic diversity indices have been used at the local level (Nunn and Wantchekon, 2011; Rohner et al., 2013; Robinson, 2017; Desmet et al., 2020; Gomes, 2020b, a; Hodler et al., 2020), we cannot exclude the possibility that a lack of representativeness at the local level introduces some noise into our estimates. Ideally, we would have liked to construct our local diversity indices based on census data. However, such data are not available on an annual basis and only a minority of African countries include ethnicity questions on their censuses (Robinson, 2017). Robinson (2017) highlights other benefits but also warns against the risk of using non-random samples or of the size of samples introducing significant errors. Usage context: supporting mention, background mention, primary mention.

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Input: % 83 % 28 % 9 % 14 % Equal contribution 93 % 81 % 83 % 16 % 17 % 17 % Majority male earners 78 % 56 % 57 % 19 % 15 % 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). 8. Conclusion This paper contributes to the literature by analyzing multidimensional poverty among refugees and internally displaced populations. We observe that forcibly displaced communities are poorer than host communities in each of the five countries ’ sub-populations covered in the surveys, with the difference in incidence between displaced and non-displaced population ranging between 15 and 19 percentage points in South Sudan and Somalia to over 30 percentage points in Ethiopia and Sudan. Displaced communities also experience greater deprivations in nearly every indicator, although there is significant variation in which indicators are the most salient, with having a bank account and cooking fuel in Ethiopia, years of schooling in Somalia, electricity in Sudan, drinking water in South Sudan, and legal identification in Nigeria showing the largest differences between the two populations. The results also indicate gender differences in the experience of multidimensional poverty, with female-headed households more likely to be poor than male-headed households in most of the countries. In addition, displaced households headed by women have a higher incidence of poverty and MPI than non-displaced female-headed households. Particularly, female-headed households in camps have higher multidimensional poverty and intensity compared to their counterparts living outside camps. Dissaggregating further, we find heterogeneity among de facto and de jure female heads. This variation lends itself to further research questions about

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Input:
on violence using data from the Armed Conflict Location & Event Data Project (ACLED) on

Security Council meeting and subsequent news reporting- Nigeria, Somalia, South Sudan, and Yemen (e.g., World Bank 2018b). 7In the 2016 IPC classification, the mVAM was actually the key component of determining food access across the country.

Authors' calculations using the 2014 Household Budget Survey. 16Registration for the World Bank's cash transfers program being implemented by UNICEF, which covers approximately one-quarter of the total population and is aimed at relatively poorer households, demonstrates the vast majority of households can be reached via phone (e.g., World Bank 2018c); evidence from different WFP surveys of food aid benefic

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survey is very similar in its relative ranking of governorates based on food access as compared

to the face-to-face Emergency Food and Nutrition Security Assessment that was undertaken
during the survey period. [20] Additionally, the regions that the WFP survey identifies as receiving

produced by another famine early warning system (FEWS NET 2017). These unofficial updates

Armed Conflict Location & Event Data Project (ACLED)

Emergency Food and Nutrition Security Assessment

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Input: The Women ’ s Empowerment in Agriculture Index (WEAI) (Alkire et al. 2012) uses individual-level data, and the linked Gender Parity Index reflects inequalities across women and men ’ s deprivation scores within the same household. Alkire, Apablaza and Jung (2014) design and implement an exploratory individual-level MPI for 31 European countries over six waves of data using EU-SILC data sets, finding no cases in which are women significantly less poor than men, and in many cases, they are significantly poorer. Espinoza-Delgado and Klasen (2018) create an individual-level MPI to understand differences in poverty between women and men in Nicaragua, finding similar overall incidence, but much higher intensity of poverty among women. Bessell (2015) and Pogge and Wisor (2016) explore deeply contextual gendered poverty measures and elucidate the ways that participatory consultations can inform the design and uses of gendered measures. Rogan (2016) uses the global MPI to analyze the gender poverty gap in South Africa. Alkire, Ul Haq, and Alim (2019) use individual-level data alongside MPI data to expose gendered and intrahousehold differences among MPI poor and non-poor children. Usage context: supporting mention, background mention, primary mention.

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Input: 2 INTRODUCTION In 2015, an estimated 2. 2 million Syrians Under Temporary Protection (SUTPs) were residing in Turkey, the majority arriving in the country over the last 4 years. 2 Turkey ’ s national population is roughly 75 million; recent refugees account for approximately 3 percent of the population. For a country that has never experienced such a large-scale, sudden inflow of foreigners, demographic changes in the composition of the population and labor force will yield unprecedented implications. This paper examines, as data allows, the relationship between the size of the foreign-born population and host community poverty rates in Turkey. First, this paper finds the poverty rates of ‘ recent migrants ’ near the Syrian border (NSB) significantly increased from 2009 to 2013. Second, the number of foreign-born households being captured by the Labor Force Survey (LFS) is expanding, which suggests a growing number of foreign households that are likely to be Syrians. Third, with respect to poverty, the results show no negative impacts on the host community as a result of the increasing size of the foreign-born population. The impact of SUTPs has been both positive and negative. Overall, a significant negative impact on host communities ’ welfare is not observed in the data.

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Input: contributing to their overall vulnerability and lack of self-reliance. As this report shows, few refugees in Ethiopia work, and those who do work mostly inside camps. Research indicates that extended periods of forced unemployment negatively affect refugees’ longer- 8 As granted under Article 26 of the 1951 Geneva Refugee Convention. Introduction 6 term labor market participation (Hainmueller et al., 2016; Hvidtfeldt et al., 2018; Brell et al., 2020), thereby also hampering the host society through larger expenditure on assistance and forgone taxes (Marbach et al., 2018; Fasani et al., 2022). Enabling refugees’ labor market participation outside of refugee camps as early as possible is key to achieving their integration (Fasani et al., 2022; Slotwinski et al., 2019) by limiting long-term scarring effects, such as long-term unemployment or inactivity. Integrating refugee children into education soon after arrival avoids loss of valuable years of education and harm to human capital accumulation that hinders future prospects. Globally in 2019, almost half of all refugee children were out of school (UNHCR, 2020d). Of those attending school, most do not make it past basic education; gross enrolment in primary education stood at 77 percent in 2019. Yet, the contrast between primary and secondary school enrolment

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Input: The countries that are the largest source of refugees include: Afghanistan, Syria, Somalia, South Sudan, Sudan, Democratic Republic of Congo, Central African Republic, Iraq, Myanmar, and Eritrea (UNHCR, 2017). These countries account for the vast majority of refugees worldwide. We will also consider three countries in Europe that are an important source of asylum seekers in Europe, and whose recognition rate is low, and account for many returnees – these are Kosovo, Serbia and Albania. Is return possible and safe, and if so, does the economic situation bode well to provide essentials, namely a job, housing, education and reliable public services? It is helpful to identify three groups of countries: ones that are still mired in war and / or high ‐ intensity civil conflicts, countries where medium ‐ intensity conflict persist and are already in the process of rebuilding, and countries which are not in conflict. According to the Armed Conflict Survey (IISS 2017), high ‐ intensity conflict is defined by frequent (daily) armed clashes between governments, government forces and insurgents, or among non ‐ state armed groups that control territory. Usage context: primary mention, background mention, supporting mention.

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Input:
**Annex 5: Stakeholder Engagement Plan Summary**

The SEP was prepared in accordance with ESS10 and identifies four categories of project-affected stakeholders: (i) direct project beneficiaries in the 24 target communities; (ii) host community residents not enrolled in project services; (iii) national and subnational government agencies involved in implementation; and (iv) civil society organizations active in the project area. The SEP specifies communication channels, frequency of engagement, and mechanisms for recording and responding to feedback for each stakeholder category. A stakeholder engagement log is maintained in the MIS and reviewed at each Bank supervision mission.

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Input: 4. 2 Perceptions of Social Cohesion The outcome of interest is how respondents perceive various dimensions of social cohesion in their communities. The surveys capture each of the locally directed dimensions of social cohesion described above. Table 4 groups these measurement strategies by the dimensions of social cohesion from the qualitative exercise. Social Cohesion Dimension Relationships Solidarity Governance Perception of In-Group Relationships Participation in socio-cultural activities with Other Ethnic Groups Access to Basic Needs Perception of Out-Group Relationships Contact with Other Ethnic Groups Access to Services Table 4: Operationalizing the Locally-Led Deﬁnition of Social Cohesion with Survey Responses First, to measure how respondents perceive the quality of their relationships, the survey asked respondents to report their perceptions of the quality of their relationships with their own ethnic group and with other ethnic groups. Two binary variables based on each respondents ’ answers to these questions are used to measure relationships, with respondents answering either “ Good ” or “ Very Good ” coded as perceiving high-quality relationships. Second, respondents report their willingness to participate in socio-cultural activities / ceremonies, attend the same place of worship, work together, marry members of other ethnic groups, and how often they have contact with members of other ethnic groups to measure solidarity.

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Input: These findings were also echoed in the context of other developing countries such as India (Allard et al., 2022) and Zimbabwe (Mabugu, Maisonnave, Henseler, Chitiga-Mabugu, & Makochekanwa, 2023). In the MENA economies ’ context, the evidence is considerably sparcer. Early work on the impact of the COVID-19 pandemic on labor markets in the MENA region re- lied on high-frequency phone surveys and highlight important job losses among wage workers and an uneven impact across industries (Krafft, Assaad, & Marouani, 2021, 2022). Providing evidence from Labor Force Surveys in the Islamic Republic of Iran, Dang and Salehi-Isfahani (2023) find that the pandemic exacerbated the pre-existing low participation of females in the labor force. Wahby and Assaad (2023), on the other hand, focus on the impact of the pandemic on Syrian refugees in Jordan and find a divergence in job finding and separation rates of Syrian refugees relative to their Jorda- nian hosts after the onset of the pandemic. Focusing on cross-border commuters in the West Bank and Gaza, Adnan and Etkes (2022) find that undocumented commuters benefited relative to their documented peers after the pandemic, as Israeli policies inadvertently created incentives for employers to favor the former. This sharply con- trasts the results by Borjas and Cassidy (2020) on the impact of the pandemic on immigrants in the United States. The rest of this paper is organized as follows. Section 2 provides background information on labor markets in the West Bank and Gaza, as well as background in- formation on the COVID-19 pandemic and government responses. Section 3 describes the data. Section 4 discusses our methodology. Section 5 presents the main regression results and investigates heterogeneous effects. Section 6 provides robustness checks. Finally, we provide concluding remarks in Section 7. 4 Usage context: primary mention, background mention, supporting mention.

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Input: Ideally, we would conduct a comparative analysis of the characteristics of migrants residing in Medellin versus those in other parts of the coun- try to discern the extent of these differences. However, the lack of comprehensive data regarding the living conditions of this population makes such analysis unfeasible. To explore how this population compares with other migrant groups in the country, we turn to the only two available data sources on migrants. First, we use the Venezuelan Refugees Panel Survey (VenRePS), conducted by Ib ´ a ˜ nez et al. (2022), which captures a 19 Usage context: supporting mention, background mention, primary mention.

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Input: For refugees, the situation is more varied, with most staying close to their country of origin while a smaller minority fled to countries further away. UNHCR (2020) estimates that three-quarters of all refugees were hosted by neighboring countries. To reflect the increase in forced displacement over the last decade and enable sustainable and long-term solutions to refugee situations, the UN Statistical Commission approved a new indicator, SDG Indicator 10. 7. 4, in early 2020 to measure and track the “ proportion of population who are refugees, by country of origin ” (UNHCR 2020). While the specific challenges for displaced communities depend on the country or host community context, often, in new locations, key challenges confronting IDPs and refugees include food insecurity, lack of livelihood opportunities, and tensions and competition over resources with host communities. The multiplicity of deprivations faced by displaced Usage context: background mention, supporting mention, primary mention.

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Input: 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. We applied the ESS EA maps around the area where refugees in Addis Ababa are located. We selected EAs in the first stage and then conducted a complete listing. Sampling design The sample for this survey was 3,456 households from eight domains, with data was collected from 3,452 households (Table C.1).58 There are three domains for the three largest in-camp refugee groups—Eritreans, Somalis, and South Sudanese— three for host communities of these major refugee groups, and one for refugees and one for host communities in Addis Ababa. In all categories, a stratified, two-stage cluster sample design technique was used to select EAs and 12 households per EA, whereby the EAs were considered a Primary Sampling Unit and the households as the Secondary Sampling Unit. The SESRE is designed to estimate demographic, socioeconomic, welfare, and refugee- specific indicators of the eight domains. 57 The cartographic map (frame) was prepared in 2018

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Input: 14 The fundamental unit of observation in ACLED is the event. Figure 2 illustrates the ACLED data for Central Africa for the 1980s and the 1990s. Each location of a conflict event is represented by a symbol. In several of these locations, multiple events occured over the periods. Events always involve two actors – a rebel group and a government – and are coded to occur at a specific point location and on a specific day. Most of the events are battles, but the dataset also records other activities. The dataset includes information on and distinguishes between six types of events: battles resulting in no change of territory, battles resulting in a transfer of territory to the rebel actor, battles Usage context: background mention, supporting mention, primary mention.

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Input: Female Male Figure 7.13: Share with friends in Ethiopia by demographic group Source: World Bank Staff based on SESRE 2023. Markets and Opportunities 69 Despite the generally positive attitudes described, social integration—measured by the friends and family refugees have in Ethiopia—is low. Only 7 percent of refugees report having family in Ethiopia, and 25 percent report having an Ethiopian friend outside the refugee camp. This rate is slightly higher among OCP refugees in Addis Ababa but still relatively low at 11 for having family and 31 percent for having a friend. The share with Ethiopian friends is higher for men, but similar across age groups (though lower for refugees over age 64). This masks some variation across domains; refugees under age 30 are likely to have friends than older refugees in the Eritrean and South Sudan domains. In contrast, refugees under age 30 are less likely to have friends in 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

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Input: 1 POST-CONFLICT TRANSITIONS WORKING PAPER NO. 16 Population Size, Concentration, and Civil War. A Geographically Disaggregated Analysis * Håvard Hegre Centre for the Study of Civil War, PRIO (CSCW) Clionadh Raleigh CSCW, PRIO & University of Colorado at Boulder Abstract Why do larger countries have more armed conflict? This paper surveys three sets of hypotheses forwarded in the conflict literature regarding the relationship between the size and location of population groups: Hypotheses based on pure population mass, on distances, on population concentrations, and some residual state-level characteristics. The hypotheses are tested on a new dataset – ACLED (Armed Conflict Location and Events Dataset) – which disaggregates internal conflicts into individual events. The analysis covers 14 countries in Central Africa. The conflict event data are juxtaposed with geographically disaggregated data on populations, distance to capitals, borders, and road networks. The paper develops a statistical method to analyze this type of data. The analysis confirms several of the hypotheses. World Bank Policy Research Working Paper 4243, June 2007 The Post-Conflict Transitions Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about post-conflict development (more information about the Post- Conflict Transitions Project can be found at http: / / econ. worldbank. org / programs / conflict).

Armed Conflict Location and Events Dataset

conflict event data
geographically disaggregated data

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Input: the West Bank and Gaza. Out of all the estimated coefficients for each period for both outcomes (job loss and job gain), we only find a negative effect on job gain in 2019Q4, which is very small in magnitude (1 percentage point). Taken altogether, the results presented in this section bolster our confidence that we are correctly identifying the effects of the pandemic shock on labor market outcomes. Figure 12: Placebo effect on labor market flows Notes: The figure shows the output of a placebo test with a set-up analogous to Figures 6 and 9. We perform the same regression as specified in Equation (2). Our sample includes data from 2018Q2 to 2020Q1 and assumes that the pandemic started in 2019Q2. Therefore, the post-pandemic period refers to the quarters between 2019Q2 to 2020Q1. The analysis is restricted to men aged 20-59. 7 Conclusion This paper examines the effect of the pandemic on labor markets in the West Bank and Gaza using quarterly labor market data provided by national labor force surveys. With a focus on men ’ s labor market outcomes, this paper sheds light on how labor markets in the West Bank and Gaza adjusted to the COVID-19 shock examining adjustments at the extensive (employment) and intensive (hours of work) margins. Usage context: supporting mention, primary mention, background mention.

national labor force surveys
quarterly labor market data

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Input: List of acronyms CAR Central African Republic DHS Demographic and Health Surveys DRC Democratic Republic of Congo DTM Displacement Tracking Matrix FCS Fragile and Conflict-affected Situations GIDD Global Internal Displacement Database GIS Geographic Information Systems IASC Inter-Agency Standing Committee ICRC International Committee of the Red Cross IDMC Internal Displacement Monitoring Centre IDPs Internally Displaced Persons ILO IOM International Labour Organization International Organization for Migration IRRS International Recommendations for Refugee Statistics JIPs Joint IDP Profiling Service LSMS Living Standards Measurement Study MICS Multiple Indicator Cluster Surveys NGOs Non-Governmental Organizations NRC Norwegian Refugee Council OCHA Office for the Coordination of Humanitarian Affairs of the United Nations Secretariat OAU Organization of African Unity ODA Official Development Assistance OECD Organisation for Economic Co-operation and Development SDG Sustainable Development Goal SKOPE Somalia Knowledge for Operations and Political Economy SuTPs Syrians under Temporary Protection UAV Unmanned Aerial Vehicle UNDP United Nations Development Programme UNHCR United Nations High Commissioner for Refugees UNITAR United Nations Institute for Training and Research UNOSAT UNITAR ’ s Operational Satellite Applications Programme UNRWA United Nations Relief and Works Agency for Palestine Refugees in the Near East UNSD United Nations Statistical Commission WFP World Food Programme Usage context: primary mention, background mention, supporting mention.

Global Internal Displacement Database
Demographic and Health Surveys
Geographic Information Systems
Multiple Indicator Cluster Surveys

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Input: street vending (48 % of those with at least 1 IGA), food processing for sale, including baking, cooking, and drying (16 %), and home production of crops, livestock, and fish (11 %). It is important to note that the EPAG program was not targeted toward the most vulnerable segments of Liberian society, but rather toward young women with enough education to be able to benefit from a training program of this nature. Based on comparisons from the 2007 CWIQ (Core Welfare Indicators Questionnaire) survey, the average EPAG participant is more educated, more literate, more likely to be engaged in an income-generating activity, and owns more assets than the average Liberian women of the same age group: mobile phone ownership was high (63 %), as was the proportion reporting that they had some money of their own (79 %). Even compared to other similar residents of Monrovia, the EPAG participants are better educated and have higher income. A strong sense of female empowerment at baseline emerges from the sections of the survey instrument having to do with self-confidence and agency.

Core Welfare Indicators Questionnaire
CWIQ

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Input: in-camp refugees, their hosts, and out-of-camp refugees (Table D.12 in Annex D). The predicted poverty rate decreases with the share of employed household members, indicating that employment is essential to lowering poverty for in- camp refugees (Figure 5.19). 0 10 20 30 40 50 60 70 80 90 100 Poorest 2 3 4 Richest Poorest 2 3 4 Richest Poorest 2 3 4 Richest Poorest 2 3 4 Richest In Camp Refugees In Camp Hosts Addis Ababa Refugees Addis Ababa Hosts Electricity Mobile phone Any livestock Bank account Agricultural holding Nonfarm enterprise Percent Figure 5.17: Household wealth indicators by expenditure quintiles Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 90 Labor force participation Employment to working age population ratio Unemployment rate 0 10 20 30 40 50 60 70 80 90 100 Agriculture Industry Services 0 10 20 30 40 50 60 70 Poorest 2 3 4 Richest In Camp Refugees Inside the Camp Outside the Camp 0 10 20 30 40 50 60 70 80 Poorest 2 3 4 Richest Poorest 2 3 4 Richest Poorest 2 3 4 Richest Poorest 2 3 4 Richest Low-skill Medium-skill High-skill Percent Percent

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Input: 7 All data collection is done by GISSE a research institute in Bamako. The anonymized unit record data of the baseline and the monthly surveys can be downloaded from www. gisse. org. The response rate for the phone interviews has been very high (Table 1): after 6 rounds of monthly interviews the original sample is almost entirely intact. The low level of attrition demonstrates that mobile phone samples can be maintained over prolonged periods without being unduly affected by (non-random) respondent drop-out. 3. Characteristics of the Displaced and Returnee Population According to the 2009 population census, the two most sizeable ethnic groups in northern Mali are the Songhai (45 %) and Kel Tamasheq (32 %)-- see Table 2. The crisis brought about an ethnic divide, which is reflected in the composition of the three sub-samples. The majority of IDPs and returnees are Songhai (75 % and 71 % respectively), while the majority of refugees are Kel Tamasheq. Results suggest that the decision of where to flee was determined by ethnicity: Kel Tamasheq and Arabs left the country; Songhai fled towards Bamako. Usage context: primary mention, background mention, supporting mention.

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Input: 14 Source: Authors ’ calculations based on data from the High Frequency Surveys of Ethiopia (2017), Nigeria (2018), Somalia (2017), South Sudan (2017) and Sudan (2017). 5. 2 Composition of poverty Unpacking the headline numbers further, important patterns emerge about the composition of multidimensional poverty among forcibly displaced and host communities in these countries. Overall, the censored headcount ratios (proportion of people who are poor and deprived in a given indicator) are lower among non-displaced communities than among refugees and IDPs, but there are large differences in which indicators are the most salient in different countries. The indicators with the largest difference between the two populations are bank account and cooking fuel in Ethiopia, years of schooling in Somalia, electricity in Sudan, drinking water in South Sudan, and legal identification in Nigeria. These findings reinforce the need for policies and programming that take into account the measured experiences of IDPs and refugees. In this way, the MPI can function both as tool to monitor, track, and bear witness to the lived experiences of forcibly displaced communities, as well as advise on evidence-based interventions that address the needs of the local population. Figure 1 shows the censored headcounts of each indicator in Sudan ’ s MPI, with large differences appearing by displacement. Usage context: background mention, supporting mention, primary mention.

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Input: Programs designed to enhance employment among young people can focus on the supply side of the labor market, including skills training programs for both wage employment and entrepreneurship training; or programs to augment demand, such as wage subsidies, public works, and community service programs; or programs to help the labor market clear, such as job search assistance and placement services. In addition, it may be that the constraints facing young people are not in the labor market itself, but in other markets, such as for credit. The vast majority of jobs programs have focused on the supply side: training programs make up about 79 percent of over 600 cases included in the World Bank ’ s Youth Employment Inventory database. 3 Although rigorous and general evidence of success is limited, it seems that successful skills training programs share a few key features: they are responsive to local market conditions, they provide more than just technical skills in a specific area (including, for example, “ life skills ”), and they include ancillary services that alleviate other constraints preventing successful labor market integration (e. g., access to credit). Among the most celebrated are the Jovenes programs that provide demand-driven technical training, plus social skills that help in the labor market, plus internships. Usage context: supporting mention, background mention, primary mention.

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Input: The countries in our sample are Benin, Burkina Faso, Burundi, Cameroon, Gabon, Ghana, Guinea, Ivory Coast, Kenya, Liberia, Malawi, Mali, Mozambique, Namibia, Niger, Nigeria, Senegal, Sierra Leone, Tanzania, Togo, Uganda, Zambia, and Zimbabwe. As described in Table B. 1, we also incorporate information on the quality of our refugee data, which is determined by comparison with official UNHCR bilateral data. Below we describe how these data have been used to define our main variables of interest and present some descriptive statistics in Table B. 2. 11 Conflict. In Equation 1, we first relate variation in ethnic diversity with data on conflict from ACLED (Linke et al., 2010). Two main definitions are used: the incidence of conflict and the intensity of conflict. Incidence is captured by an indicator equal to one if conflict occurred in a particular year within a pre-defined buffer around cluster j. Intensity is measured by summing the number of conflict events occurring in a particular year within the same buffer area. A conflict event is defined as a single altercation wherein force is used by one or more groups for a political end (Linke et al., 2010). We further describe events (non-exclusively) as violent events, non-violent events, violence against civilians, and riots. In our main analysis, we focus on violent conflicts (Section 5. 1) and report results for other outcomes as robustness tests (Section 5. 3). In doing so, we follow a recent and large literature that has combined the ACLED dataset with geographically disaggregated data in Africa (Besley and Reynal-Querol, 2014; Berman and Couttenier, 2015; Michaelopoulos and 11Panel A of Table B. 2 shows descriptive statistics for the data from refugee-hosting areas specifically, whereas panel B of Table B. 2 shows descriptive statistics for our data in all covered areas. 11 Usage context: background mention, primary mention, supporting mention.

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Input: The data on total gross proﬁts and net sales acquired from the Turkish Ministry of Science, Industry and Technology are compiled from administrative taxation data and was provided upon request by the ministry. The key diﬀerence from the Chamber of Commerce data is that the sales and proﬁts data include all businesses including self- proprietorships. 9 Data were provided for the years between 2010 and 2014 and are re- ported in nominal Turkish Liras (TL). It is worth noting that the administrative data will not include any informal activities by deﬁnition and they are likely to be less accurate and complete for smaller ﬁrms. Firms whose sales do not exceed an annually determined limit do not have to report their balance sheets which includes sales and proﬁt ﬁgures. 10 We scale the variables according to province size by dividing sales and proﬁts by the pop- ulation of the provinces. If we use sales and proﬁts in absolute terms, we get qualitatively similar results. The IV estimations use data from the years 2011 and 2014. Since the number of refugees was still relatively small in 2011 and really started picking up only in 2012, we 12

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Input: Figure 5 Panel A illustrates the percent of FDP datasets that cover various topics in their questionnaire modules and Panel B shows differences in the percent of datasets covering each topic between FDP datasets and all other non-FDP datasets stored in the WB MDL. 32 The topic of health is by far the most common with roughly 78 percent of datasets mentioning keywords related to health in their descriptions of the questionnaire modules. Other common topics include food insecurity (49 percent) and water sanitation (39 percent). Less frequently included are topic areas related to labor and employment (19 percent); security and conflict (18 percent); finance, credit and debt (14 percent); agriculture and livestock (10 percent), and shocks (9 percent). The fact that topics such as security, conflict and shocks are often not included in the survey modules is not unique to FDP datasets. In fact, those topics are also relatively uncommon in other micro-level household surveys available in the WB MDL. When compared to the topic coverage of all non-FDP micro-level datasets in the WB MDL, FDP datasets are scarcer in such topics as labor, finance, agriculture / livestock / fishery, and education. As shown in Figure 5 Panel B, these topics are much more likely to be picked up in the non-FDP micro-level datasets. When it comes to labor and employment in particular, the gap is over 50 percentage points illuminating 32 See Annex C for further details on the methodology used to analyze topic coverage. For this topic coverage analysis, we exclude those datasets that are project specific or collected before 2010. Usage context: supporting mention, background mention, primary mention.

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Input: However, an endline survey was conducted after the second round of the EPAG program as per the timeline depicted in Figure 1. Examination of this endline survey data will permit a descriptive analysis of the outcomes of the first group of trainees 12 months after they completed the EPAG program, as well as examination of the outcomes of the second batch of trainees. The second round included not only the control group from this impact evaluation but also newly recruited participants who were offered brief basic literacy and numeracy training program prior to program entry. Work is already underway to design and implement the third round of EPAG, with a substantial redesign of the Job Skills track, an emphasis on reaching younger girls with lower literacy, and expansion to communities outside of Monrovia. If the high success rates found in this study are replicated for these future cohorts, the EPAG program should serve as a model for policy makers in Africa and the world seeking to improve lives and livelihoods of all youth, male and female. 25

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Input: Ababa live in rented houses; the team faced challenges in tracing some refugees due to changes in their residential locations. Challenges related to identifying the eligible sample households were also observed due to outdated names of the household heads in UNHCR lists, and UNHCR’s registration of names which is not consistent with the Ethiopian context58. Thus, these challenges required additional effort by the team to ensure that sampled households and replacements were traced, identified, and interviewed. Another challenge was that some refugees were not willing to provide their current location due to personal security reasons, but these situations were resolved by reaffirming the confidentiality of the survey. 58 UNHCR register names starting with last name, whereas, in Ethiopia names starts with first name. Annexes 97 Annex D: Descriptive Statistics and Regression Results Results on Sociodemographic Profile Table D.1: Demographic characteristics by survey domains Eritrean Somali South Sudanese Hosts Refugees Hosts Refugees Hosts Refugees Age group <15 39% 46% 54% 50% 47% 56% 15 to 24 19% 19% 17% 22% 21% 21% 25 to 44 26% 25% 21% 17% 21% 16% 45 to 64 13% 8% 7% 9% 8% 5% >=65 4% 2% 2% 2% 3% 1% Gender Male 48% 51%

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Input:
Still, despite these critiques, the evidence in this paper cautions against a naive switch to the HCES
direct method. In our survey experiment, we calculate hunger to range between 19 and 68 percent -this

is a difference of more than 23 million people in Tanzania (a country with a population of 45 million

presenting a strong challenge to both the HCES-direct and the FBS-CV methods. The FBS-CV is

Note: estimates of Equation (1). Each column represents the results of a (separate) regression (OLS or LPM) of a selected HCES-derived measure (mentioned in the titles of the panels) on 7 module assignment dummies, a single selected household characteristic (mentioned in the column headings) and 7 interaction terms of that household characteristic with the module assignment dummies.

Smith L. 1998. Can FAO's Measure of Chronic Undernourishment be Strengthened? _Food Policy_ 23(5):

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Input: about 333,000 Venezuelan children were enrolled in government schools in 2020 (about 3.4 percent of the total student population in Colombia) (UNHCR, 2021a). In Turkey, the government is supporting the transition of Syrian refugee children into the national school system, redirecting resources to locations with high concentrations of refugees (Abu-Ghaida and Silva, 2020), resulting in nearly 80 percent of Syrian primary school-aged refugee children being enrolled in education programs by 2020/2021 (UNHCR, 2021). In addition to benefiting refugee children, high school enrolment and learning outcomes increased for local Turkish students (Tumen, 2019; 2021). Educational attainment is low among both hosts and refugees, especially in camps. About 73 percent of in-camp adult refugees and 59 percent of adult hosts (aged 18 and above) either did not attend school or did not complete primary education. South Sudanese refugees have the worst educational attainment. Refugees in Addis Ababa have relatively better educational attainment compared to their hosts, with a higher percentage of refugees in Addis Ababa completing primary (45 percent) and secondary (27 percent) education (Figure 2.7). Although more educated, even youth’s (age 15 to 24) educational attainment is low, with large differences by survey domains. Many youth refugees and hosts have not

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