Input: the degree to which the global response should include a development element. We ﬁnd that the average stood at around 10. 3 years at the end of 2015, with a median duration of 4 years, and signiﬁcant sensitivity to a few situations. Such numbers re-emphasize the importance of effective humanitarian interventions on the right scale. They suggest that development actors have a role to play but that they need to focus their interventions on a set of discrete protracted situations. To produce these numbers, we rely on the Population Statistics Database compiled and main- tained by UNHCR. The database records the number of “ persons of interest ” to UNHCR in each year since 1951 and for each situation, where a situation consists of a pair host-origin countries. The calculation of duration of exile is obtained under a no-turnover assumption, whereby a de- crease in the number of refugees for any given situation is fully attributed to exits from refugee status, while increases are assumed to be fully accounted for by new cases. Although such ap- proach tends to over-estimate the true duration of exile, the lack of individual-level data on regis- tration precludes reﬁning the estimate further. Attempts to estimate similar statistics have been limited. Usage context: background mention, supporting mention, primary mention.

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Input: 77% Proximity to resource hubs Nearest to zone 34% 93% Nearest to woreda 24% 72% Nearest to border 37% 81% Remote 33% 78% Source: World Bank Staff based on SESRE 2023. Annexes 113 Table D.12: Determinants of welfare (total expenditure per capita) (1) (2) (3) (4) In-camp refugees In-camp hosts OCP refugees OCP hosts Female headed 0.00 0.03 -0.01 0.02 (0.03) (0.03) (0.04) (0.05) Age of head (year) 0.00** 0.00 -0.00 -0.00 (0.00) (0.00) (0.00) (0.00) Household size -0.12*** -0.09*** -0.20*** -0.16*** (0.01) (0.01) (0.01) (0.02) Head years of schooling 0.02*** 0.01*** 0.03*** 0.03*** (0.00) (0.00) (0.01) (0.00) Mobile phone 0.10*** 0.19*** 0.39*** 0.17 (0.03) (0.03) (0.11) (0.15) Household has electricity 0.15*** 0.22*** 0.14 0.19 (0.04) (0.03) (0.27) (0.13) HH owns any livestock 0.04 0.03 -0.42* (0.03) (0.04) (0.25) HH member has bank account 0.13*** 0.13*** 0.07 0.16 (0.03) (0.03) (0.10) (0.26) HH has agricultural holding -0.02 -0.08* -0.47* (0.03) (0.04) (0.24) HH operates a nonfarm enterprise 0.07** -0.00 -0.05 0.26*** (0.03) (0.03) (0.10) (0.07) Share of employed members 0.35*** 0.57*** 0.14** 0.06 (0.08) (0.06) (0.06) (0.08) Health shock 0.07 -0.02 -0.04 -0.20 (0.06) (0.06) (0.10) (0.18) Market shock -0.01 -0.09*** -0.04 -0.19*** (0.02) (0.03) (0.04) (0.05) Employment shock 0.01

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Input: Figure 22: Numbers of Refugees in Ongoing Refugee Situations end-2014 Source: UNHCR Statistical Online Population Database Note: Only includes refugee situations greater than 25, 000 people. Excludes Palestinian refugees under UNRWA ’ s mandate. D. Data on asylum-seekers, refugees and IDPs: sources, applications and credibility In this section, a distinction is made between: (a) the collection of source data; and (b) the compilation of data across sources (within a country or across countries). In general, there is a delineation of roles between data collectors and data compilers, however there are organizations, such as UNHCR, IOM and the Office for the Coordination of Humanitarian Affairs of the United Nations Secretariat (OCHA), 59 that are involved in both data collection and compilation activities. Data collection: Sources for refugees, asylum-seekers and IDPs60 Collection of primary data on forcibly displaced persons is generally undertaken by national governments through their national statistical offices, line ministries or immigration agencies. However, where countries lack the capacity to undertake this work, they may rely on international organizations as well as international and local NGOs to collect data or undertake estimates. 61 In general, governments tend to collect data on refugees in developed countries, while UNHCR and NGOs tend to collect data on refugees in developing countries. Usage context: primary mention, supporting mention, background mention.

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Input: 25 less cohesion. The increase in solidarity is less apparent among refugees where the majority (53 %) stated that the crisis had no effect on solidarity. Figure 18: Levels of trust, by group (June) (%) Source: Listening to Displaced People Survey, 2014. Perceptions that different groups have of others are important elements of peace. When asking for the degree to which neighbors, other villagers and people from other ethnic groups can be trusted the survey finds positive outcomes. Although all groups trust people from other ethnic groups slightly less, the general level of trust is high and it remains stable over time. Finally, consider how IDPs, refugees and returnees envision the future of Mali. The majority of refugees in Mauritania vie for an independent or autonomous North, while the majority of IDPs, returnees and refugees in Niger wish to see full government control over the North. 20 20This contradicts, in part, findings of an Afrobarometer perception survey on causes and consequences of the conflict in Mali conducted in December 2013. Usage context: primary mention, supporting mention, background mention.

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Input:
**KEY HIGHLIGHTS** **[1]**

 Most of the youth in NWS **face protection risks,** with 53% reporting homelessness and 55% experiencing
exploitation, while 44% face gender-based violence.

 75% of youth **lack access to protection services**, highlighting a significant gap in availability and
accessibility.
 77% of respondents indicate **no organizations offer tailored activities or services for youth** in NWS,

**Specific youth groups**, such as those with disabilities 70%, adolescent females 40%, IDPs 48%, and
homelessness 36%, are identified as experiencing significant protection risks.
 82% of **youth believe newly graduated youth have fewer working opportunities**, 66% of Youth actively
participate in community-based structures, with 74% volunteering and 53% involved in outreach teams,
promoting skill development, relationship building, and community contribution.

 76% of youth in northwest Syria **perceive unequal opportunities for social participation,** with
discrimination (85%), exclusion (34%), and stigmatization (15%) as key contributing factors.

 Only 12% of **youth have access to capacity-building or empowerment activities**,

 Expanded initiatives for **youth empowerment, leadership, and conflict resolution** are needed, with a
focus on essential skills development and resilience building.

 20% of **youth have been threatened or felt afraid**, while 24% sometimes experience such feelings,
impacting their well-being.

---
[1] The Protection Monitoring and Analysis working Group (PMA WG) of the Northwest Syria Protection Cluster, with support from the

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Input: Hosts Refugees Eritrean Somali South Sudanese Figure D.24: Household owns livestock Source: World Bank Staff based on SESRE 2023. 0 0.1 0.2 0.3 0.4 0.5 0.6 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.23: Household owns crops Source: World Bank Staff based on SESRE 2023. 0 10,000 20,000 30,000 40,000 50,000 60,000 70,000 80,000 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.25: Total value of livestock Source: World Bank Staff based on SESRE 2023. 0 5,000 10,000 15,000 20,000 25,000 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.26: Value per tropical livestock unit Source: World Bank Staff based on SESRE 2023. 0 0.05 0.1 0.15 0.2 0.25 0.3 0.35 0.4 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.27: Household has non-farm business Source: World Bank Staff based on SESRE 2023. Annexes 110 0 5,000 10,000 15,000 20,000 25,000 30,000 35,000 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.28: Value of productive assets in households with business Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 Percent 70 80 90 100 Hosts Refugees Hosts Refugees

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Input: As in previous sections we follow Henderson et al. (2012) who argue that the relationship between GDP and night light at the country level can be expressed fairly well in a constant elasticity model in which an increase of night light by 1 percent implies an increase of GDP of about 0. 25 percent. Hodler and Raschky (2014) also look at the relationship between log nighttime light intensity and log GDP at the regional level using the panel data of regional GDP per capita assembled by Gennaioli et al. (2013) 48 and they conﬁrm that the relationship is linear and also ﬁnd an elasticity of around 0. 3. Access to political power is ranked on a scale from 1 to 7 in the GROWup dataset. Ethnic groups are"powerful"(monopoly of power or dominant group in power), have access to central power through a formal system of power sharing (as"Senior"or"Ju- nior"partner) or are “ excluded ” from power (self excluded, powerless or discriminated). Strong executive constraint is measured as a dummy indicating whether or not we have executive parity or subordination of the executive at the country level, a value 7 for “ xconst ” variable in Polity IV dataset. Usage context: background mention, primary mention, supporting mention.

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Input: Considering that these statistical standards and recommendations were established in recent years, it may not be surprising that the overall level of compliance with EGRISS recommendations is still evolving. Figure 6: Prevalence of Identifying Questions in FDP Datasets A) Refugee identification questions B) IDP identification questions Notes: Panel A shows the percent of FDP datasets containing each of the core identification questions recommended by EGRISS for refugees (in all publicly available datasets designed to sample from refugees that are not project specific and collected after 2010) whereas Panel B shows IDP equivalent of that. For refugees, we do not make a distinction between the question on the country of citizenship and the acquisition of citizenship because many datasets we study often collapse these questions into one by simply asking respondents to indicate their nationality (or nationalities). 5. Conclusion With an ever-growing number of people forced to flee their homes due to conflict, violence, fear of persecution, and human rights violations, data on FDP has become ever more important. A solid evidence base is crucial to inform effective policy responses to address their challenges and to establish such a base, 35 More than 95 percent of the FDP datasets asked questions on either the country of birth or citizenship. 36 While the country of birth does not change, nationality or citizenship can. And it is the country of citizenship or acquisition of citizenship that determines whether refugees and refugee related persons should still be regarded as refugees by the national authorities even though their country of birth may be different from that of their citizenship or nationality and how citizenship interplays with refugee status varies by country (EGRISS 2019, p. 28). Usage context: background mention, supporting mention, primary mention.

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Input:
_returns to education are heterogeneous across countries. The second set of Mincerian returns are those estimated by Montenegro and Patrinos (2014)._
_Source: The data has been collected from PWT 9.0 (Feenstra, Inklaar and Timmer 2015)._

natural capital: (i) it represents only the contribution of the physical capital stock from PWT 9.0 in the conventional

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decomposition, and (ii) it shows the contribution of the physical capital stock (from PWT 9.0) and natural capital (Lange

et al. 2018) in the natural resource decomposition. The average annual rate of growth in output per worker for the

respectively- are then computed using the estimated relative income shares (which vary across groups) and the PWT   9.0 labor share (which varies across countries and over time).

Since  is calculated from the share of labor force in PWT 9.0 and 𝛼�1 �𝛾� is proxied by the ratio of natural resource

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Input:
Polity data - political regime or patterns of authority. Countries with larger positive (negative) polity values have a more democratic (autocratic) system.

This paper describes an approach to forecasting future climate at the local level using historical weather station and satellite data and future projections of climate data from global climate models (GCMs) that is easily understandable by policymakers and planners.

policymakers. It draws on historical climate data from weather stations and satellites;

We begin with monthly temperature and rainfall data for the period 1961-2000

historical climate data from weather stations and satellites

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Input: Proclamation of Ethiopia provided a long list of areas52 exclusively reserved for Ethiopian nationals, including small businesses that would have been of interest to refugees (FDRE, 2020). Hence, it allows many business activities to go beyond the reach of refugees. A draft MoU signed between RRS and MoLS/MoTRI/ MoR proposed exceptional treatment of refugees engaged in business due to their vulnerability. According to the MoU, refugees can own a business in agriculture, manufacturing, services, small and medium enterprises, handicrafts, and trade sectors through establishing private limited companies or cooperative societies. Hence, refugees can obtain a business license as a private business or association by providing proof of refugee ID, support letter from RRS on the type of business, source of capital, utilization of profits, qualification certification (depending on the sector), and tax identification number. A business license renewal requires a valid refugee ID, tax clearance, and audit report for a limited liability company. 52 Restaurants, tearooms, coffee shops, bars, nightclubs, catering services, producing bakery products and pastries, barbershop and beauty salon services, smithery, tailoring, sawmilling, timber manufacturing, brick and block manufacturing, quarrying, laundry services, translation secretarial services, security services, brokerage services, and attorney and legal consultancy. Annexes 87 Following the

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Input: In contrast, districts of origin are distributed widely across the country. This reﬂects the fact that much work migration is from remote rural areas to towns and cities. The main characteristics of work migrants are reported in Table 1, together with those of non- migrant adult males. We see that work migrants are on average younger and better educated. The census contains detailed information about ethnicity, language, and religion. In the Nepal census, the term ‘ ethnicity ’ is used to capture a hodgepodge of caste and tribal distinctions. The census distinguishes up to 103 ethnic categories. Most of these categories only account for a tiny proportion of the total population. In terms of the total adult population, the most common ethnic categories are Chhetri, Brahmin, and Newar who, together, account for 35 % of 13 Usage context: primary mention, background mention, supporting mention.

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Input: However, another regressor indicates that security may still be pivotal: those who owned a weapon were up to 30 percentage points more likely to plan to go back. In addition to this, it is quite surprising that, if the respondent thought that the Northern Mali crisis was improving, he or she was less likely to plan a return to that area. From a technical point of view, we should point out that we have used an LPM even if the dependent variable was a binary outcome. This choice has been made since in this linear model it is straightforward to add fixed-effects. Furthermore, the coefficients can be interpreted as average partial effects. A simple logit or probit model would not have allowed the inclusion of individual fixed-effects because of the incidental parameter problem. An alternative approach would have been to estimate a conditional logit model. However, since the distribution of the fixed effects is unknown, it would not have been possible to estimate the average partial effects in this model, but only the effect of the regressors on the log-odds ratio. 13 We conclude by stressing that the monthly phone interviews were relatively short, so we did not have a rich panel data set. This may have led to omitted variable biases. Indeed, there may still be time varying factors which could have affected both the probability of being employed and the respondents ’ intentions to go back. Nevertheless, we believe that our model managed to control for 13 See (Wooldridge, 2010) page 639. Conclusions from the conditional logit model are qualitatively similar. Usage context: background mention, supporting mention, primary mention.

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Input: Colombian and Venezuelan migrant children and adolescents. VII Discussion In this study, we analyze novel and unique data on forcibly displaced migrants and hosts, focusing on children and adolescents, to highlight the disparities in human development between them. The structure our analysis in two parts. In the first part, we characterize the main trends in the data. We show that forcibly displaced households have a wealth distribution skewed towards lower values relative to Colombian households. This is likely explained by the assets ownership loss that forcibly displaced households expe- rienced after the migration episode. We also identify meaningful lags in human capital accumulation between Colombian and Venezuelan children and adolescents of approxi- mately 1 year. We further note that the Colombian government ’ s supportive policies for Venezuelan forced migrants are evident through high levels of service access and pro- gram participation for migrants. Nevertheless, it remains surprising that participation is not higher, suggesting significant potential for improvement in increasing sisb ´ en and health insurance enrollments. In a second part of our analysis, we document sizeable lags in physical and cognitive de- velopment of Venezuelan children and adolescents, relative to their Colombian counter- parts. However, we were not able to identify any gaps in the socioemotional and mental health between the two groups. Usage context: supporting mention, background mention, primary mention.

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Input: Challenges around skill mismatch exacerbate exclusion, as many young Lebanese lack the skills and competencies demanded by private sector employers, particularly ‘ soft skills ’. To address some of these challenges, the Lebanese government (GOL) identified volunteerism as a mechanism to enable diverse youth to work together for improved community assets and service delivery as well as increased employability. In September 2012, the GOL issued a Decree (Number 8924 / 2012) that created a new extra curriculum program that requires secondary school students to complete 60 hours of civil work. In addition, the Ministry of Social Affairs (MOSA), through its Volunteering Department, launched annual action plans for the implementation of youth volunteer summer camps across Lebanon. 4 Father ’ s education and residence (region and location of school) are the two largest contributors to inequality of opportunity in students ’ math test scores, accounting for 44 and 23 percent of total inequality, respectively (World Bank, 2016). 5 According to the 2013 Gallup Poll, 90 percent of respondents in Lebanon agreed with the statement that knowing people in high positions is critical to getting a job. Usage context: background mention, supporting mention, primary mention.

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Input: (b) Disaggregation and geo-mapping of data by location (current location and location of habitual residence; urban, peri-urban or rural location), accommodation (organized camp versus non- camp), and demographics (age and sex); (c) Expanded coverage of data collection exercises to include all areas of affected countries (security permitting); (d) Improved coverage and detailed data on displaced populations living outside of organized camps; (e) Improved coverage of ‘ flows ’, i. e. new displacement, durable solutions (returns, integration, resettlement), births, deaths, and in the case of IDPs, the numbers that flee across international borders becoming refugees; (f) Systematic data collection beginning from the earliest moment following displacement, following up as populations disperse, and continuing until sustainable / durable solutions have been achieved; and (g) Better aggregation, analysis and presentation of forced displacement data currently compiled separately by UNHCR, IOM, IDMC and UNRWA. Additional efforts are required to address the gaps in the data required for development policy and planning. These data are critical for informing the design of development policies and assistance programs. Usage context: primary mention, background mention, supporting mention.

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Input:
The government of Chad continues to ensure the security of refugees and asylum-seekers through the
Humanitarian Workers and Refugee Detachment (DPHR). Generally, refugees are not more exposed to
[existing violence and crime. According to protection data collected through Project 21](https://response.reliefweb.int/west-and-central-africa/protection/projet-21) (‘regional protection
monitoring’) approximately 15 per cent of refugees and asylum-seekers claim to have been victims of
physical assault, but it is noteworthy that these cases occurred in the country of origin at the time of fleeing.

While rape and child marriage remain prohibited by Law, other forms of gender-based violence (GBV)
are insufficiently covered by existing Laws and policies to protect the Chadian and refugee populations.
The national policy to respond to GBV, in effect since 2011, applies in refugee camps and refugee hosting
villages but faces challenges due to limited resources (human and logistic) to fully implement this policy. The
referral mechanism for refugee victims for medical, legal and psychosocial support remains in place but its
effectiveness depends on the human and financial resources available in the relevant hosting areas.

protection data collected through Project 21

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Input: A map highlighting Medell ´ ın ’ s geographic position and the locations of the households interviewed for this study is provided in Figure 2, offering visual context to our research setting. Representativeness and stratification. VenRepS-Kids is designed to be representative of two groups of youth. The first group consists of Colombian children and adolescents, aged 5 to 17, born to Colombian parents. The second group encompasses Venezuelan migrant children and adolescents of the same age range, born to Venezuelan parents, who mi- grated to Colombia between 2016 and 2020. The sample was further stratified by gender and socioeconomic levels, using Colombia ’ s neighborhood income-based classification system that ranges from 1 to 6, where six indicates the wealthiest neighborhoods. Our 13 Usage context: supporting mention, primary mention, background mention.

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Input: High-skill occupations include managers, professionals, and associate professionals. Ln Earnings is the log of monthly earnings winsorized at the 1st and 99th percentiles. All other models are linear probability models. Standard errors clustered at the EA level. * p < 0.10, ** p < 0.05, *** p < 0.01 Annexes 107 Table D.8: Refugee Household Reliance on NGOs/Donations (1) (2) (3) (4) All Eritrea Somali South Sudan Years in Ethiopia -0.007** -0.017** -0.011** -0.001 (0.003) (0.006) (0.005) (0.005) Member works outside the camp -0.080** -0.335*** -0.180*** -0.001 (0.035) (0.099) (0.051) (0.041) Region Fixed Effects Yes No No No Demographic Controls Yes Yes Yes Yes N 1252 423 412 417 Source: World Bank Staff based on SESRE 2023. Note: Each column is a linear probability model where the outcome is a binary indicator of whether the household relies primarily on donations for income. Demographic controls include the household size and the share within each age and education group. Standard errors clustered at the EA level. * p < 0.10, ** p < 0.05, *** p < 0.01 Table D.9: Determinants of refugee-host earnings gap (1) (2) (3) Earnings Earnings Earnings Refugee (% difference from hosts) -24.9** -22.4** -18.5* (0.137) (0.115) (0.114)

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Input: The MIS was designed to serve as the single source of truth for beneficiary-level data across all three components. It captures individual registration records, service delivery events, transfer payments, and complaint submissions. Each implementing partner has read access to data from their own operation area, while the central PIU has system-wide read and write access. The MIS generates automated exception reports flagging duplicate registrations, inconsistent household composition records, and transfers issued outside the scheduled payment windows.

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Input: 10 as the Demographic and Health Surveys (DHS), though researchers have reduced under-reporting by providing special training to interviewers, placing greater emphasis on respondents ’ privacy and safety, and allowing women multiple opportunities to disclose their experiences (Ellsberg et al., 2001a; Garcia Moreno et al., 2003; Ellsberg et al., forthcoming). Estimates of the magnitude of the problem Population-based surveys have found that between 10-70 % of women report being physically assaulted by an intimate male partner at some point in their lives (Heise, Ellsberg and Gottemoeller, 1999). See Annex A for estimates from many recent population based studies (Ellsberg et al., forthcoming). Findings from a multi-country study on domestic violence and women ’ s health carried out by the World Health Organization in fifteen sites and ten countries found that between 13-62 % of women had experienced physical violence by a partner over the course of their lifetime, and between 3-29 % of women reported violence within the past year (Figure 1. 1). Figure 1. 1.

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Input:
observations. The ENILEMS-ENLACE panel also includes the information from ENOE

for all 3,714 matched observations plus information from ENLACE's context question

in means between the observations of ENILEMS that were merged with ENLACE scores

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Input: Deciding on whether to flee or not to flee a conflict (the migration choice) can be an individual or household choice and risk coping strategies may include temporary migration, shuttling between places, migration of only selected members of the households or migration of the whole household. This implies that individuals may stay put throughout the period observed, join or leave the household during the period, or have several episodes of out and immigration. Households may decide to leave and come back several times. In econometric terms, this means that longitudinal data may be left and right censored and have spells within. They are therefore the most complex set of panel data possible and require particular treatment of data and modeling. Survival or duration models can usually accommodate many of these complexities but it is very rare to find similar data sets used in published articles. Collecting such type of data is also not obvious, particularly if conflict is intense and survey areas cannot be reached. This is an issue where empirical economics could provide a real contribution by defining the optimal data format and adapting panel models to this format. Macro models Macroeconomics has attempted to model forced migration using models borrowed from the trade and economic migration literature such as the gravitational model (Echevarria and Gardeazabal, 2016) or used other macro models to test the impact of refugees on trade (White and Tadess, 2010). A more recent body of work is adapting trade models to take into account stochastic shocks in a dynamic framework (Cameron et al., 2007; Artuc et al., 2008). These are rational expectations models that are able to model the unpredictability of shocks, and recent work has tried to adapt these models to the context of violent

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Input:
Based on specification (1), we estimate total 2013 GDP for Kenya at $26.8 billion (2005 USD), close to its actual level of $26.9 billion (WDI, 2014). On county-level, we find that Nairobi had the highest overall GDP in 2013 ($3.4 billion), followed by Kiambu ($3.0 billion), Nakuru ($2.3 billion), Nyeri ($1 billion), and Kilifi ($1 billion). Counties with the lowest GDP are the sparsely populated counties of Isiolo ($56 million), Lamu ($58 million), Samburu ($67 million), Elgeyo Marakwet ($108 million), and Tharaka Nithi ($109 million). Nairobi has the highest contribution to national GDP (13 percent), followed by Kiambu (11 percent),

Based on specification (1), we estimate total 2013 GDP for Rwanda at $4.58 billion (2005 USD), only slightly higher than the national-accounts estimate of $4.57 billion (WDI, 2014). On the district-level, we find that Gasabo district had the highest GDP in 2013 ($925 million), followed by the two other districts of Kigali (Kicukiro at $538 million and Nyarugenge at $371 million). Districts in the secondary urban centers come next: Rubabu ($219 million), Rusizi ($186 million), Huye ($166 million), and

As evident from the title of this paper, we also tried to estimate poverty levels and changes based on nightlights data. The estimated associations were however not robust, and more time and effort would need to be invested in examining this relationship in a more detailed fashion.

Based on national labor survey data (EPAM 2010), it appears that mean income from mining activity for each active worker is higher than the average income for all other activities, especially the agricultural and industrial sectors in the Sikasso region.

WDI, 2014
national labor survey data (EPAM 2010)

nightlights data
national labor survey data

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Input: 18 Figure 3 Job finding, job separation and the change in employment for young men who ever worked between 2016 and 2020 by half year and nationality conditional on informal employment in their most recent job (Seasonally adjusted) Source: Authors ’ calculations using SYPJ data Figure 4 Job finding, job separation and the change in employment for Syrian young men who ever worked between 2016 and 2020 by half year and residency in camp (Seasonally adjusted) Source: Authors ’ calculations using SYPJ data Usage context: background mention, supporting mention, primary mention.

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Input: 1 Introduction The political and economic crisis in Venezuela has given rise to a massive exodus, esti- mated at 4. 3 million people (as of the end of 2019). Many Venezuelans sought refuge in neighboring countries. It is estimated that 1. 5 million Venezuelans had settled in Colombia by the end of 2019, and over 2 million elsewhere in Latin America. Naturally, Venezuelan migrants have sought employment in the host countries but, because of their recent arrival and their transient status, our knowledge of their working conditions is scant. Our paper aims to ﬁll this gap focusing on Ecuador, where almost 400, 000 Venezuelans have settled and many more have transited through the country on the way to other destinations. More speciﬁcally, we provide the ﬁrst analysis of the labor-market conditions of Venezuelan migrants in Ecuador, based on a new nationally representative survey of this population that also includes information on the Ecuadorans living in the same localities. The survey (known by its Spanish acronym EPEC) was promoted by the World Bank and the government of Ecuador and implemented during the summer of 2019. The design and scope of the survey are unique in the context of the countries across Latin America hosting Venezuelan migrants. Usage context: supporting mention, background mention, primary mention.

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Input: The 2023 survey collected data on 1,980 rural enterprises across nine provinces using a stratified random sample drawn from the business registration database maintained by the national statistics office. The 2023 survey questionnaire covered enterprise age, legal form, employment, revenue, access to credit, and adoption of digital technologies. Due to budgetary constraints, the 2023 survey did not include a module on international trade linkages; this limitation is noted where relevant in the interpretation of findings on market integration.

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Input: The World Bank's online screening tool classified this operation as High Risk for GBV/SEA/SH due to the presence of civil works in isolated rural communities and a history of gender-based violence documented in the project area. In response, the project's ESMF includes an expanded GBV annex specifying minimum requirements for contractor codes of conduct, confidential reporting channels, survivor support services, and community sensitization activities. These requirements are contractually binding and subject to third-party verification on a biannual basis.

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Input:
**Appendix E: LFS Harmonization Across Survey Rounds**

The LFS underwent a questionnaire redesign between round 4 (2015) and round 5 (2016), introducing changes to the employment status classification and the self-employment income module. To enable pooled analysis across rounds 1–7, we harmonize the LFS employment status variable using a crosswalk table developed by the national statistics office. The harmonization reduces the number of employment status categories from seven (rounds 5–7) to four (rounds 1–4), which is sufficient for the binary employed/not-employed distinction used in our main analysis.

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

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Input: protracted nature of refugee hosting in Ethiopia, it is essential to better understand how vocational training programs and cooperatives can become self-sustainable, especially in the more remote border regions with poor market linkages. Box 3.3: Refugee Vocational Training and Cooperatives Jobs and Livelihoods 35 In line with high reliance on remittances, labor force participation and employment rates among OCP refugees are low, with rates similar for male and female refugees. Table 3.2 presents labor force participation (LFP) data; among those aged 15-64, LFP is 46 percent for refugees and 66 percent for hosts. This increases to 67 and 72 percent when you use the relaxed definition of unemployment, reflecting the large number of OCP refugees who say they are ready to work but are not actively searching. The unemployment rate is an astonishing 63 percent for refugees relative to 12 percent for hosts, and it increases to 75 percent under the relaxed definition. Only 17 percent of OCP refugees work, and 23 percent are inactive and not in school. Female refugees have similarly large rates of inactivity and unemployment, and the total share working is similar to male refugees. Female refugees also have high rates of self-employment relative to female

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Input:
obtained from the Center for Research in Security Prices (CRSP). Stocks with prices less than

of all stocks included in CRSP.

Firm characteristics are obtained from COMPUSTAT. Size is computed as the log of total assets.

of stock returns on the Fama and French (2015) 5 factors.

Center for Research in Security Prices (CRSP)

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Input: The LFS is a rotating panel in which households are interviewed for two consecutive quarters, rotated out for two quarters, and then re-interviewed for two further quarters (a 2-2-2 rotation scheme). Because the LFS does not follow individuals across household moves, our analysis is restricted to non-movers — defined as individuals observed in the same dwelling across all four LFS interview waves. This restriction reduces the analytical sample from 18,400 to 14,230 individuals but eliminates the bias that would arise if mobility decisions are correlated with labor market outcomes.

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Input: Figure 18: Significant Refugee Returns by Country of Origin 1991 – 2015 Source: UNHCR Statistical Online Population Database, UNHCR Global Trends 2015 Note: Countries selected based on their cumulative returns of refugees over the period 1991-2015. Return does not necessarily lead to the full reintegration of a person into their home country or area of origin. In the absence of global data on the success of reintegration following return, data on returns appear to be taken as indication of sustainable return. In reality, many returnees face impediments to reintegration and continue to have specific economic and social vulnerabilities linked to their displacement. They may not be able to reclaim land, access sufficient financial resources (e. g. accumulated during their displacement) or reestablish social networks in areas of origin, which are critical factors for successful reintegration (World Bank 2015). Sustainable refugee return is therefore not a one-off event but a process that provides returnees with adequate safety, housing, livelihoods and services that address their specific vulnerabilities and reduce the likelihood of secondary displacement (World Bank 2015). Figure 19: Voluntary Returns of Refugees 1991 – 2015 Source: UNHCR Statistical Online Population Database, UNHCR Global Trends 2015 Note: Includes returns of refugees and people in refugee- like situations protected or assisted by UNHCR.

UNHCR Statistical Online Population Database

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Input: Figure 20: Returns of IDPs Protected or Assisted by UNHCR 1993 – 2015 Source: UNHCR Statistical Online Population Database, UNHCR Global Trends 2015 Note: Includes returns of IDPs and people in IDP-like situations assisted and protected by UNHCR. Consequently, the average length of protracted refugee situations has increased over the past two decades according to UNHCR estimates (see Table 2). UNHCR estimates that the average length of ongoing

UNHCR Statistical Online Population Database

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Input: Figure 18: Significant Refugee Returns by Country of Origin 1991 – 2015 Source: UNHCR Statistical Online Population Database, UNHCR Global Trends 2015 Note: Countries selected based on their cumulative returns of refugees over the period 1991-2015. Return does not necessarily lead to the full reintegration of a person into their home country or area of origin. In the absence of global data on the success of reintegration following return, data on returns appear to be taken as indication of sustainable return. In reality, many returnees face impediments to reintegration and continue to have specific economic and social vulnerabilities linked to their displacement. They may not be able to reclaim land, access sufficient financial resources (e. g. accumulated during their displacement) or reestablish social networks in areas of origin, which are critical factors for successful reintegration (World Bank 2015). Sustainable refugee return is therefore not a one-off event but a process that provides returnees with adequate safety, housing, livelihoods and services that address their specific vulnerabilities and reduce the likelihood of secondary displacement (World Bank 2015). Figure 19: Voluntary Returns of Refugees 1991 – 2015 Source: UNHCR Statistical Online Population Database, UNHCR Global Trends 2015 Note: Includes returns of refugees and people in refugee- like situations protected or assisted by UNHCR. Usage context: primary mention, background mention, supporting mention.

UNHCR Statistical Online Population Database

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Input:
The effort was inspired by the U.S. Drought Monitor (USDM) and involved USDM experts and experienced officials from Mexico, which had recently implemented a similar drought monitor process.

The World Bank performed a disaster risk financing diagnostic to gain a more nuanced understanding of the economic impacts of the drought throughout the Eswatini economy.

World Development 157, 105932
Anseeuw, W., Bache, W., Bru, T., Giger, M., Lay, J., Messerli, P., Nolte, K., 2012. Transnational land deals for agriculture in the
global South: Analytical report based on the land matrix database.

by SGC** 2015 1,935 1,530 28,345 0 0.54 2016 2,817 1,916 42,754 0 0.87 2017 3,388 2,139 43,358 0 0.84 2018 5,108 3,519 65,859 0.06 0.85 2019 8,710 5,327 83,269 0.51 0.69 2020 2,431 847 13,408 0 0.50 2021 7,805 5,232 58,442 0.09 0.38 Pre-Prozorro 7,094 4,774 54,425 0 0.41 Prozorro 711 458 4,017 1 0 2022 2,041 1,043 9,964 1 0 Total 34,235 21,553 345,399 0.22 0.61 _Source:_ Own computation from SGC and Prozorro data as described in the text.

0.322 0.255 0.469 0.202 0.174 0.319 0.203 Contract length (years) 8.61 8.33 9.51 8.84 9.04 7.98 7.08 _**Land use**_ Crops 0.48 0.48 0.47 0.65 0.66 0.61 0.69 Pasture 0.35 0.34 0.36 0.29 0.27 0.37 0.38 Forest 0.15 0.15 0.13 0.09 0.09 0.08 0.06 _**Distance in km to**_ Main road 8.65 8.48 9.22 9.31 9.30 9.32 9.38 Nearest city 15.64 15.66 15.58 16.58 16.59 16.57 17.16 Grain elevator 13.39 13.55 12.84 13.56 13.50 13.84 14.43 Kyiv 297.22 295.17 304.04 312.33 309.85 323.26 334.55 _Source:_ Own computation from SGC and Prozorro data as described in the text.

U.S. Drought Monitor
land matrix database

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Input: Both treatment and control group respondents report equally high confidence in their ability to return to school “ should [she] decide to do so. ” These findings from the quantitative impact evaluation complement the results from a set of qualitative focus group discussions that were held with participants at the end of the 6 months of classroom training. Twenty-five percent of the trainees from Round 1 participated in a total of 34 focus group discussions that covered a variety of topics including their satisfaction with the program and their empowerment in both social and economic realms. The trainees overwhelmingly voiced a high degree of satisfaction with the training, and trainers commented on how the motivation or “ seriousness ” of the participants grew over the 6 month period. The trainees credited the transport allowance and free childcare in particular as features that facilitated their full participation; as one trainee commented, 22 Questions adapted from the Adolescent Self-Regulation Inventory, developed and validated for youth in the United States by Moilanen, 2006. The questions were revised and translated into an 11-item for the Liberian context. In the future, we plan to conduct basic testing on this scale on internal consistency and reliability. 17

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Input: Our evaluation explicitly investigated these spillovers by including household-level indicators such as food security and attitudes of the household head toward gender norms. Our results show strong impacts on economic outcomes, including large and statistically significant increases in employment and earnings of EPAG participants. We show mixed results on empowerment- related outcomes, and very little evidence of spillovers on non-participants. Self-assessed measures of self-confidence show huge gains, as does ownership and control over monetary resources such as savings. The remainder of the paper is organized as follows: Section 2 describes the EPAG project including some of its innovative design features and implementation details. Section 3 reviews the methodology of the evaluation and Section 4 presents results on the three groups of outcomes discussed above: economic, empowerment, and spillovers. Section 5 includes a short discussion of cost-effectiveness. Section 6 presents a series of robustness checks and Section 7 concludes with a discussion of next steps and policy implications. 2. The EPAG Project The EPAG project is part of a larger Adolescent Girls Initiative (AGI) administered by the World Bank with support from the Nike Foundation and the Governments of Australia, the United Kingdom, Norway, Denmark, and Sweden. Launched in Washington DC in October 2008, the AGI was spearheaded by President Ellen Johnson Sirleaf, who signed on to undertake the initiative ’ s first pilot project in Liberia. The Liberian pilot was launched in March 2010 and has served as a role model to seven subsequent pilot projects in Rwanda, South Sudan, Nepal, Afghanistan, Haiti, Jordan, and Lao PDR. Under the global AGI, young women and adolescent girls are given a package of skills training and complementary services in order to facilitate their successful transition to employment. In the case of EPAG, the intervention consisted of a six month phase of classroom-based training, followed by a six 4 Usage context: primary mention, supporting mention, background mention.

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Input:
To complete this analysis with information on how these losses are distributed in the population and especially on the poorest, a survey was conducted with informal dwellers affected by the 2005 floods. It was found that the aggregated losses they suffered from are about $250 million (for total losses due to the 2005 flood of about $2 billion), but the relative impact on their savings and consumption was extremely large, with average capital losses of the same order of magnitude than their average total savings (in other terms, their savings were totally wiped out by the event).

<!-- PAGE 12 --> _Figure 2: Roofer wages in an area where losses have been significant after the 2004 hurricane season in_ _Florida. Data from the Bureau of Labor Statistics, Occupational Employment Surveys in May 03, Nov 03,_ _May 04, Nov 04, May 05, May 06, May 07._

The box figure illustrates the effect of insurance penetration [13] on the household's budget, for a July 2005 like flood estimated using the ARIO model. Three scenarios are included: (i) γ=0, equivalent to the absence of insurance system, but with an access to credit; (ii) the current value of flood insurance penetration estimated by RMS (γ=0.08 for households, γ=0.15 for firms); and (iii) γ=1, representing the situation where all the reconstruction is paid for by insurance.

<!-- PAGE 5 --> methodologies and approaches, and they often reach quite different results. In the US, for instance, a systematic analysis by (Downton and Pielke, 2005) showed that loss estimates differ by a factor of 2 or more for half of the floods that cause less than $50 million in damages.

One of the appealing features of night lights data is their availability on every level. Night lights
data are measured on the so-called 30 arc sec level, corresponding to roughly 1 square kilometer
at the equator.

Bureau of Labor Statistics, Occupational Employment Surveys

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Input: 10 as the Demographic and Health Surveys (DHS), though researchers have reduced under-reporting by providing special training to interviewers, placing greater emphasis on respondents ’ privacy and safety, and allowing women multiple opportunities to disclose their experiences (Ellsberg et al., 2001a; Garcia Moreno et al., 2003; Ellsberg et al., forthcoming). Estimates of the magnitude of the problem Population-based surveys have found that between 10-70 % of women report being physically assaulted by an intimate male partner at some point in their lives (Heise, Ellsberg and Gottemoeller, 1999). See Annex A for estimates from many recent population based studies (Ellsberg et al., forthcoming). Findings from a multi-country study on domestic violence and women ’ s health carried out by the World Health Organization in fifteen sites and ten countries found that between 13-62 % of women had experienced physical violence by a partner over the course of their lifetime, and between 3-29 % of women reported violence within the past year (Figure 1. 1). Figure 1. 1. Usage context: background mention, supporting mention, primary mention.

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Input: most land cover by built-up and shops, and nearest to Zone capital city, respectively. All estimates are controlled for refugee camps. Standard errors in parentheses. +p<0.10, * p<0.05, ** p<0.01, *** p<0.001 Variables Basic Model Local Market Proximity Market access Model I Model II Model I Model II Annexes 119 Table D.16: Proximity and market accessibility effects on engagement in agriculture activity: logit model Variables Proximity Market access Model I Model II Individual feature Male 0.1979*** 0.2016*** 0.1998*** (0.0289) (0.0286) (0.0297) Age -0.0307*** -0.0294*** -0.0296*** (0.0083) (0.0081) (0.0088) Age squared 0.0004*** 0.0004*** 0.0004** (0.0001) (0.0001) (0.0001) Some primary -0.1403*** -0.1436*** -0.1484*** (0.0305) (0.0298) (0.0307) Household feature HH size: member age [15,29] -0.0157 -0.0171 -0.0186 (0.0118) (0.0113) (0.0117) HH size: member age (30,44] 0.0422* 0.0414* 0.0320+ (0.0179) (0.0178) (0.0185) HH size: member age (45,64] 0.0187 0.0278 0.0314 (0.0221) (0.0226) (0.0237) HH access electricity -0.2980** -0.2655** -0.2658** (0.0929) (0.0884) (0.0974) Proximity and market access Level two 0.2065*** (0.0607) Level three 0.2358** (0.0788) Level four 0.3559*** (0.0769) Distance to Zone city (Km) 0.0022*** (0.0006) Market accessibility indicator -0.0792* (0.0330) Observations 742 737 742 Chi-square test 0.0000 0.0000 0.0000 R2 0.2517 0.2435 0.2128 Source: World Bank Staff based on SESRE 2023. Standard errors in

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Input: Regrettably, until now almost all enrollment numbers cited have been based on establishment surveys which do just that. These data sources show that around 200, 000 children were enrolled full-time in madrassas before 2001. Since 2001, our school census suggests that these numbers may have increased somewhat, although the experience varies across districts. To put this number in context, total primary enrollment (grades 1-5) in public and private schools stood at 17. 4 million in 2003 (Government of Pakistan, Ministry of Finance, 2003). The choice of madrassa schooling viewed as either the percentage of eligible children or the percentage of enrolled children, is statistically insignificant for the average Pakistani household. Enrollment in madrassas accounts for approximately 0. 3 percent of all children between the ages of 5 and 19. Given that the overall enrollment rate for this age group is roughly 42 percent, this represents less than 0. 7 percent of all enrolled children, an order of magnitude less than the 33 percent cited by the International Crisis Group report (2002). 3 This is complemented with the census of private schools carried out by the Federal Bureau of Statistics in 2000 to provide statistics for private versus public enrollment. 4The PIHS is the equivalent of the widely used Living Standard Measurement Surveys (LSMS) implemented in various countries. See http: / / www. worldbank. org / lsms for extensive notes on the 1991 PIHS. See also www. statpak. gov. pk for information on the census and the Federal Bureau of Statistics data. Usage context: supporting mention, primary mention, background mention.

PIHS
Living Standard Measurement Surveys

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

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Input: NGOs. Initiatives such as JIPS, a collaborative project of UN and NGO actors, have also been established to support governments and operational organizations to design and implement data collection processes. There are a variety of data sources for generating statistics on forced displacement, each of which has strengths and weaknesses. Despite the significant challenges, large amounts of data are collected and disseminated every year. The main data sources and methods for the generation of statistics on forcibly displaced populations include: (a) registration of refugees and asylum-seekers; (b) registration of IDPs; (c) profiling of IDPs; (d) population movement tracking systems; (e) national population censuses; (f) sample surveys; (g) border crossings; (h) administrative records and registers; (i) general population registers; and (j) a variety of estimation methods for producing statistics when adequate and reliable data on individuals are unavailable (UNSD 2014). Several of these data sources might be used together to triangulate estimates of stocks and flows for a particular displacement situation. Usage context: supporting mention, background mention, primary mention.

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Input:
data are collected from the World Bank's World Development Indicators (WDI). In this context, TFP growth is:

Oil Metal **Trade Openness** Percent of GDP 1990 - 94 64 95 65 56 2010 - 14 77 94 93 70 **Herfindahl Index** Product Concentration 1990 - 94 0.41 0.84 0.69 0.29 2010 - 14 0.30 0.67 0.46 0.21 Market Concentration 1990 - 94 0.20 0.30 0.08 0.19 2010 - 14 0.20 0.15 0.28 0.18 **Natural Resources** Percent of GDP 1990 - 94 17.0 46.9 26.8 9.8 2010 - 14 13.2 43.0 16.3 8.9 Percent of total exports 1990 - 94 0.82 0.99 0.95 0.78 2010 - 14 0.73 0.89 0.71 0.72 _Sources: WDI, and author's calculations using WITS, COMTRADE_

World Bank's World Development Indicators (WDI)

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

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Input: There is a clear increase in the entry of new foreign ﬁrms which may be driven by refugees ’ enterpreneurship. Cheaper low-skilled labor may have helped all businesses cutting costs. Balkan and Tumen (2016) had also found a decline in prices and attribute their ﬁnding to lower labor costs, which may also be one of the mechanisms driving our results. Gross proﬁts and sales also appear to have gone up, which would be consistent with an increase in demand. As noted by Maystadt and Verwimp (2014), heterogeneous eﬀects on speciﬁc subgroups of the native population should be expected from refugee crises. In case of the Syrian refugee crisis in Turkey, the business activity in hosting region appears to have beneﬁted. For a complete picture of the eﬀects of the Syrian refugee crisis on local economies in Turkey, further research will be needed on market activity, health and longer term eﬀects. More speciﬁcally for the line of research this study focused on, further analysis using micro-level ﬁrm data would be needed to understand how ﬁrms adjust their activity, 24 Usage context: primary mention, background mention, supporting mention.

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Input:
and Fonden threshold information for 1,745. As shown in table 1, using 2000 census data, we

various administrative records that allow us to observe at the municipal level: the number of

**Keywords:** Disaster Risk Financing and Insurance; Financial Institutions; Climate Change and Disaster Risk; Shocks and Vulnerability to Poverty   _∗_ We would like to thank Artemio Couti˜no of SAGARPA who provided administrative CADENA data, as well as information about program rules.

To determine the effect of   insurance payments on yields and area sowed, we use agricultural production data from SAGARPA   detailing the annual hectares sowed, hectares harvested, and total production in metric tons at the   municipality-crop level.

Note. Standard errors are clustered at the state level. Asterisks indicate statistical significance: _∗_ _p_ _<_ 0 _._ 10, _∗∗_
_p_ _<_ 0 _._ 05, _[∗∗∗]_ _p_ _<_ 0 _._ 01. Observations are at the municipality-year-level. Hectares sowed are defined as the total
hectares growing any rainfed agricultural crop as reported in SAGARPA production data.

administrative CADENA data
SAGARPA production data

agricultural production data from SAGARPA

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

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Input: 9 Bank Account No member has a bank or mobile money account. 1 / 12 Many of the indicators align with goals identified in the 2030 Agenda for Sustainable Development, such as no hunger, good health, access to quality education, clean water and sanitation, and decent work, as well as indicators that are especially relevant for displaced people, such as possession of legal identification, physical safety, and food security. The focus on gendered dynamics justifies health indicators related to pregnancy care, combining information on prenatal care, assisted delivery, and early marriage. A full discussion of the MPI ’ s indicator selection can be found in Admasu et al. (2021). We focus on six of these 15 indicators that use individual-level data – viz years of schooling, school attendance, pregnancy care, early marriage, legal identification, and unemployment. Our intrahousehold analysis drops the two health indicators due to data limitations; the question about age at marriage was only asked to the household head in Ethiopia, Nigeria, and South Sudan, whereas in Somalia and Sudan, it was applied to more members than the head. Usage context: supporting mention, background mention, primary mention.

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Input: All regression models are estimated using ordinary least squares with standard errors clustered at the DHS cluster level. Clustering at the DHS cluster level is appropriate because households within the same DHS cluster are subject to common shocks — including local health facility quality, crop yield variation, and community-level program exposure — that generate within-cluster correlation in error terms. Alternative specifications clustering at the administrative district level are presented in Appendix Table A4; point estimates are unchanged and standard errors are slightly wider.

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Input: This database lists seven categories: refugees, asylum-seekers, returned refugees, internally displaced persons (IDPs), returned IDPs, stateless persons and others of concern. For each group the database provides yearly information about their composition by loca- tion of residence and origin. We exploit only the data on “ refugees ”. 22 In particular, we are interested in the annual stock of refugees for each country of residence, i. e. how many people with refugees status have left their home country each year. We focus on these numbers as they appear to be the most comparable across time and countries. However, this is likely to capture only the tip of the iceberg in some cases. The number of IDPs is extremely high in some instances but cannot be captured with the same level of conﬁdence as refugees generally. 23 Cross-country data about conﬂict is provided by the UCDP / PRIO. As for the index of country-level economic activity, we use again information provided by the Penn World Table and World Bank databases. As mentioned above, our aim is to explore the dynamics of refugees during conﬂicts. In other words, we attempt to answer several questions.

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Input: required to purchase other basic staple foods such as salt and vegetables. Given that the WFP provisions are the only reliable rations that refugees receive, we approximate a cash transfer of 450 taka per week to at least double potential weekly consumption. Relative to the wealth refugees possess, 450 taka per week is likewise sizeable: average baseline savings is 195 taka, with the median refugee reporting zero taka in savings. Average baseline borrowing (typically in the form of store credit) is 1, 600 taka, with a median of 600 taka. Refugees have no economically meaningful assets that may be more common among the rural poor, such as land or cattle, given the unanticipated displacement which forced them from their homes. Relative to other employment opportunities, average reported pay is 300 taka per day for less than three days. The monthly cash transfer is therefore more than double what a refugee might expect from alternative employment if he or she is fortunate enough to secure a job. 4 Data Collection and Survey Instruments Timeline and survey instruments We collected data via a baseline, commencing in November 2019, and endline survey, commencing in February 2020, as well as seven midline surveys conducted prior to payment disbursal each week. These weekly surveys collected a small subset of well-being outcomes.

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Input: 5 does not have migration or geographic identifiers. The SILC contains geographic identifying variables, (at the NUTS1 level) but still lacks migration variables. The data set this study uses is the Labor Force Survey (LFS) since there is an adequate availability of both migration and geographic variables. The LFS is representative at the NUTS2 level which corresponds to 26 regions in Turkey. One caveat is that income in the LFS refers to only wage income from employment, 9 and is an insufficient measure of income that should be used for welfare measurement. For example, important sources of income such as social assistance, asset liquidation, or remittances are missing. Therefore, income in the LFS is imputed with a few assumptions using information from the SILC. The NUTS1 spatial effects of the SILC are a good proxy for NUTS2 welfare dynamics in the LFS which increases the accuracy of the imputation model. However, since the original sample frame of the LFS does not account for the recent influx of foreign migrants in Turkey, the labor market characteristics of recent migrants might not be representative of the actual SUTP population. Therefore, results of the imputation could be interpreted as upper bound estimates for recent migrants. More details of survey techniques used to complete this exercise are available in the Annex.

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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 6832 This paper presents findings from the impact evaluation of the Economic Empowerment of Adolescent Girls and Young Women (EPAG) project in Liberia. The EPAG project was launched by the Liberian Ministry of Gender and Development in 2009 with the goal of increasing the employment and income of 2, 500 young Liberian women by providing livelihood and life skills training and facilitating their transition to productive work. The analysis in this paper is based on data collected during two rounds of quantitative surveys in 2010 and 2011, the second of which was conducted six months after the classroom-based phase of the training program ended. Usage context: background mention, primary mention, supporting mention.

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Input: more than five consecutive years—increased over time, accounting for 40 percent of all refugees in 2021 (World Bank, 2023). In Ethiopia, 95 percent of all refugees live in a protracted situation, according to SESRE data. 11 According to UNHCR mid-2022 statistics, South Sundanese, Somali and Eritrean refugees constitute 46, 29 and 18 percent of the total refugee populations in Ethiopia. (https://www.unhcr.org/refugee-statistics/download/?url=2bxU2f) 12 https://www.unhcr.org/refugee-statistics/insights/explainers/children-born-into-refugee-life.html Sociodemographic Profile 10 53% 30% 5% 12% South Sudanese Somali Eritrean Addis Refugees Figure 2.1: Refugees by survey domain Source: World Bank Staff based on SESRE 2023. 68% 62% 63% 88% 31% 38% 32% 11% 0 10 20 30 40 50 60 70 80 90 100 Percent Eritrean Somali South Sudanese Addis Refugees Country of origin Ethiopia Other Figure 2.2: Country of birth Source: World Bank Staff based on SESRE 2023. Refugees fled from their country of birth mainly due to conflict and violence. Almost all South Sudanese refugees, or 99 percent, left their country because of conflict and violence, as did 91 percent of Somalis, and 73 percent of Eritrean refugees. On the other hand, OCP13 refugees came to Ethiopia with the hope of going to a Western country (35 percent), to escape from conflict and

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Input: 10 Last, specific adjustments are made in the case of Germany and the Republic of Korea. For Germany, bilateral data are available only by nationality. However, these data fail to take adequate account of the large number of ethnic Germans who arrived from other countries between 1944 and 1950 (mainly expellees) and those who arrived after1950 (mainly resettlers). Material from the German 2005 micro-census was therefore used to supplement the data for Germany (see appendix 3). In the case of Korea, data by nationality are readily available for each census round. However, these data fail to account for the large numbers of migrants from the People ‘ s Democratic Republic of Korea living in the Republic of Korea. Since the United Nations Trends in International Migrant Stock details the total migrant stock in the Republic of Korea by the country of birth definition and because citizenship is rarely granted to people from outside, it is simply assumed that the nationality data were comparable to the foreign-born definition. The nationality total was then subtracted from the UN total and the remaining migrants were assigned to the People ‘ s Democratic Republic of Korea. Usage context: primary mention, background mention, supporting mention.

United Nations Trends in International Migrant Stock

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Input: percent for refugees and 57 percent for hosts if you include all available to work regardless of whether they are searching (relaxed unemployment). The remaining 57 percent of refugees are inactive, and just over half are currently in school, leaving 23 percent of refugees neither working nor studying, compared to 20 percent of hosts. In-camp refugees have high unemployment rates relative to hosts. Figure 3.2 shows that only 25 percent of in-camp refugees performed paid work in the week before the survey, compared to 48 percent for hosts. At the household level, only 54 percent of refugee households have any workers, relative to 86 percent for hosts. The strict unemployment rate is 21 percent for refugees and 7 percent for hosts, while the relaxed unemployment rate is significantly higher at 43 percent for refugees and 15 percent for hosts. Across camp domains, Eritreans have the highest rate of relaxed unemployment at 55 percent, while it is 45 percent and 40 percent for Somalis and South Sudanese, respectively. South Sudanese have the highest rates of inactive workers remaining in school, reflecting that they have a younger population and that more young adults stay in school (mainly primary) after age 15.40 During

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