Input:
School feeding programs are largely implemented by the World Food Programme, reaching a total of 13,000
refugees in 14 schools in the provinces of Lake Chad and Logone Oriental.

The Unified Social Registry (RSU), launched in 2019, has made limited progress in capacity, governance and
financing, despite continuous support from WFP and NGOs.

**4.4** **Protection for vulnerable groups**

In practical terms, the national protection system for the most vulnerable has not undergone any changes
and the measures in place to support victims of human trafficking are still insufficient. This holds true for
victims of Gender-Based Violence (GBV) and at-risk children. The national protection services aimed at
these vulnerable groups continue to be underdeveloped and underfunded.

12 R E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **R E P U B L I C O F C H A D**

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Input: 20 of intense conflict. We examine also the overall impact of the 25 years of conflict on educational outcomes. This analysis allows us to consider the full long-term impact of the conflict on educational outcomes of different generations of children in Timor Leste. 4. 2. 1. The educational impact of the 1999 wave of violence We exploit variation in the number of killings over time and across districts to identify conflict affected individuals. Our intention here is to analyze whether individuals exposed to the violence during their primary school age show different primary school completion rates eight years after the end of the war, relative to those not affected by the conflict. The outcome variable in which we are interested is whether individuals completed primary school in 2007. Figure 7 shows average primary school attainment for all individuals in our sample. The graph shows an increasing trend in primary school completion across cohorts and a progressive reduction of the gender gap. The gap among the younger cohort (those born after 1987) is almost zero. The drop in the curve for the younger cohort confirms the presence of significant delays in school attendance. For the purpose of this analysis, we use the TLSS 2007 dataset and the HRVD dataset contained in the CAVR data publication. Usage context: background mention, primary mention, supporting mention.

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Input: Produced by the Research Support Team Abstract The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development / World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Policy Research Working Paper 9826 Despite the many simultaneous deprivations faced by forcibly displaced communities, such as food insecurity, inadequate housing, or lack of access to education, there is little research on the level and composition of multidimensional poverty among them, and how it might differ from that of host communities. Relying on household survey data from selected areas of Ethiopia, Nigeria, Somalia, South Sudan, and Sudan, this paper proposes a Multidimensional Poverty Index (MPI) that captures the overlapping deprivations experienced by poor individuals in contexts of displacement.

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Input: The weight given to each province in constructing the synthetic control is based on pre-treatment outcomes. We use the pre-treatment average of the outcome dimension, Y, the unemployment rate, employment rate and the import and export per capita of the province to determine the degree of similarity between control group provinces and the treated provinces, which in turn determines the weight assigned to control provinces. The unemployment and employment rates are included to control for the general economic performance while trade values are added to control for the degree of ’ openness ’ of the province. 6 The treated unit i = 1 is constructed by taking the mean of the outcome variables in the provinces hosting refugees in 2012 or 2013. 5 Data We use several data sources for the analysis. The IV estimations use data from years 2011 and 2014 while the DD estimations use data from 2009 to 2014. The numbers of refugees up to 2012 are treated as 0. The refugee data for 2012 and 2013 are obtained from UNHCR ’ s oﬃcial weekly statements in December. Data on the number of refugees in 2014 is from Erdo ˘ gan (2014), who uses statements released by the Ministry of the Interior to compile his data. All refugee data we use in the analysis is provided at the level of 81 provinces. Usage context: supporting mention, background mention, primary mention.

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Input: The third proxy for economic activity is given by per capita growth of night light, computed using satellite data from the National Oceanic and Atmospheric Administration (NOAA). 6 Night light data has the beneﬁt 6Satellite data is available for a shorter time period, 1992-2013. 9

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Input: Further, as Jordan and the international community develop new approaches that respond holistically to the specific needs of refugee and host communities, more evidence is needed about how gender ‐ based constraints and vulnerability affect refugee women ’ s ability to take up economic opportunities and to access the services and resources they need to enable their families to move out of poverty. Our analysis applies a gender lens to a rich set of microdata on Syrian refugees in Jordan collected by UNHCR between 2011 and 2014. As these data do not capture how the changes in policies affect refugees and the constant evolution of their situation since 2014, the analysis is not intended to directly inform current policy choices and decisions. Instead, our aim is to devise an approach that can provide greater insights into gender ‐ specific barriers, based on the premise that the experiences and potential vulnerabilities of women, men, and children are significantly different in refugee settings. We use household ‐ level data to examine the relationship between poverty and gender for Syrian refugees. Our approach is informed by a body of work in the academic literature that has used household survey data to examine the relationship between the gender of the household head and household 2 http: / / www. unhcr. org / globaltrends2017 /, accessed August 2, 2018. 3 http: / / www. unhcr. org / globaltrends2017 /, accessed August 2, 2018. 4 https: / / data2. unhcr. org / en / documents / download / 64568, accessed August 2, 2018. 5 https: / / reliefweb. int / sites / reliefweb. int / files / resources / 64114. pdf, accessed August 2, 2018. Usage context: supporting mention, background mention, primary mention.

household survey data
household ‐ level data

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Input: 10 Finally, we divide the communities based on land scarcity before the 1993 conflict in order to explore the possible role of posterior rules regarding land provision to returnees. Respondents in communities that had more and less pre-war land available have broadly similar attitudes towards return. 4. Research design 4. 1 The survey We collected the data for this project during January to March 2015 as part of a nationwide survey on issues related to migration for the Labour Market Impacts of Forced Migration (LAMFOR) project. The survey had two components. First, a household survey in which 15 households were interviewed in 100 communities (i. e. sous-collines) across the 17 provinces of the country. Second, a community survey in which a local leader was interviewed in each of the 100 communities. The number of communities selected in each province was based on information from the 2008 Census. Figure 4 indicates the location of the communities surveyed. Figure 4 – Location of communities surveyed in Burundi Note: Geolocation of the 100 communities (i. e. sous-collines) sampled in the survey. Each community corresponds to a dot. Fifteen households and a local leader were interviewed in each community. The number of communities selected in each province was based on information from the 2008 Census. In the analysis below we focus on rural areas. Usage context: supporting mention, primary mention, background mention.

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Input: The household and family dynamics in Liberia, as in other African settings, can be complex, with families often sending their children to live with relatives who are more able to provide for their schooling and basic needs. Young parents, in particular, often leave home to migrate for work, leaving their children back home with relatives until they are able to establish themselves and send for their children. If the economic success of the EPAG participant allowed her to bring non-resident family members into her household (including but not limited to her own children), then overall household size may have been expected to increase as a result of the program. This does not appear to have happened, at least in the short term. The results in Table 8 show that overall household size was not affected by the program. It is possible that the increase in earnings due to EPAG was too small, or too short-lived, to have induced the kinds of migrations described above. Other measures of household well-being, including food security and asset ownership, reflect shorter- term investments that might be influenced by the economic success of EPAG participants. Panel B of Table 8 shows the impact of EPAG on a broad range of food security measures. Usage context: primary mention, background mention, supporting mention.

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Input: Figure 3. Wealth Index Distribution (a) Wealth Index- Total 0. 05. 1. 15. 2. 25 k-Density- 5 0 5 10 15 Wealth Index Colombian Venezuelan Venezuelan: Before migrating (b) Adequate Housing Materials (% of Total) 0 1 2 3 4 k-Density 0. 2. 4. 6. 8 1 Average- Dwelling Material Colombian Venezuelan Venezuelan: Before migrating (c) Asset Ownership (# Total) 0. 05. 1. 15 k-Density 0 10 20 30 40 Total Assets Colombian Venezuelan Venezuelan: Before migrating (d) Access to Services (% of Total) 0 1 2 3 k-Density 0. 2. 4. 6. 8 1 Average- Access to Services Colombian Venezuelan Venezuelan: Before migrating Notes: Panel (a) presents the distribution of the wealth index for Colombian and Venezuelan households in our sample in 2022 and pre-migration. Wealth Index is an index measure of the household ’ s cumula- tive living standard constructed following The Demographic and Health Surveys (DHS) methodology. Usage context: supporting mention, primary mention, background mention.

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Input: This assistance is crucial and has been reported to support a meal a day, a better roof, and dignity for Syrians who have fled to Jordan. 8 The JD ‐ HV database has detailed information on expenditure, sources of income, and indicators of household ‐ level welfare, for example, as reflected by recourse to coping mechanisms, standard of accommodation, or access to water, sanitation, and hygiene (WASH). JD ‐ HV data collected between October 2013 and December 2014 were first analyzed in Verme et al. (2016) who produced welfare aggregates and poverty measures to help target benefits and assistance to those most in need. Verme et al. (2016) draw attention to the precarious circumstances of Syrian refugees in Jordan and Lebanon. Around 55 percent of refugees in Jordan are vulnerable to monetary poverty and more than half are vulnerable to food shocks. Family size increases the probability of being poor, with the poverty rate almost doubling if the size of the family goes from one to two members and increasing by 17 percent when the number of children increases from one to two. 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. Usage context: primary mention, supporting mention, background mention.

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Input: Estimation Procedures We thus propose the following estimation procedures to predict the poverty rate in period 2, where consumption data are missing but the relevant characteristics x are available. Step 1: Check that Assumption 1 is satisfied, which involves verifying that key features of the two surveys such as the sampling frames and the questionnaires are (essentially) the same. If data from earlier survey rounds are available, check that the regression model that is used for imputation satisfies Assumption 2 on these data. 23 The difference is that we use a random effects probit model to estimate equations (1) and (2) instead of the linear random effects model, that is, the estimating equation is)'() (j j j x j j y P ε µ β + + Φ =, with j = 1, 2, where (.) Φ is the cumulative normal distribution. 26 Usage context: background mention, supporting mention, primary mention.

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Input:
**in order to meet housegold food needs?**

**Sell HH assets/goods (radio, furniture, jewellery)**

**Reduce food expenditure**

**Spent household savings**

**Sold house/land**

**Accept degrading unsuitable high risk dangerous or exploitative work**

**Some members return to homeland**

##### **b) Food coping strategies**

**79%**

The reduced Coping Strategies Index (rCSI) includes the five most commonly used food-related coping strategies and
their order of severity as a proxy indicator to measure access to food. The higher the rCSI, the more coping strategies
households had to endure. The reduced food coping index score was the highest in the North with a value of 24.66,
followed by BML 21.4, South 16.58, and Bekaa was the lowest with the value of 10.25.

**Figure 9: Food coping reduced index score per area**

**24.66**

**21.41**

**18.74**

**16.58**

**10.25**

**Bekaa** **BML** **North** **South** **All**

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Input:
food consumption expenditure in Tanzania based on the Household Budget Survey 2000/01. To make

representative 2006-07 Household Budget Survey (the comparison results are not presented here but

This model is estimated using a sample of 206,414 children from house holds in rural villages of India from the District Level Household Survey 2007-08 (DLHS-3).

The most relevant for the current study is a recent paper that  used propensity score matching to estimate the effect of access to improved sanitation on  diarrhea in children under five using the District Level Household Survey (DLHS-3) (Ku

Another  study (Bose, 2009) using similar methods from Nepal looks at access to sanitation using  a 2006 Demographic and Health Survey (DHS) finding reductions of 5 percent from mean

District Level Household Survey 2007-08 (DLHS-3)

District Level Household Survey (DLHS-3)

2006 Demographic and Health Survey (DHS)

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Input:
Notes: The graph plots local means of secondary school outcomes by ENLACE test score
percentile in grade 6 in 2007. The solid line shows a linear fit estimated using the grouped
data. Panel (a) reports the probability of on-time graduation from grades 9 and 12, proxied
by siting in the Enlace exam in those grades. Panel (b) reports Enlace test scores in grades
9 and 12 (normalised with mean 0 and SD 1) conditional on taking the Enlace exam in 2010
and 2013. Data: ENLACE panel.

38

Figure 4: ENLACE test scores and post-secondary school outcomes

(a) College Enrollment
1
(%)
College .8
in
Enrolled
.6
.4
0 10 20 30 40 50 60 70 80 90 100
Enlace Test Score Percentile in Grade 12

d
not .5
if
(%),
Employed .4
.3
0 10 20 30 40 50 60 70 80 90 100
Enlace Test Score Percentile in Grade 12|
|---|---|
|2.7
2.8
2.9
3
3.1
3.2
Wage hourly earnings (ln)
0
10
20
30
40
50
60
70
80
90
100
Enlace Test Score Percentile in Grade 12
(c) Wage Earnings|.2
.3
.4
.5
.6
Employed in formal firm (%), if employed
0
10
20
30
40
50
60
70
80
90
100
Enlace Test Score Percentile in Grade 12
(d) Employed in Formal Firm|

Notes: The graph plots local means of post-secondary school outcomes by ENLACE test
score ventile in grade 12.

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Input:
(henceforth CRU), provided by the Climatic Research Unit of the University of East

and satellite-based observations. The data enable us to characterize historical climate

<!-- PAGE 6 -->
**2.1 Assignment of reliability weights to the eight GCMs, based on their**
**historical "goodness of fit" to the CRU data**

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Input: The most recent labor force survey from Liberia mirrors these statistics: there are roughly 1. 1 million people in the workforce, of whom 195, 000 (about 18 percent) are engaged in wage employment; the remaining 900, 000-plus workers (82 percent) are considered in vulnerable employment, working for themselves or working unpaid for their own households (LISGIS 2010). Among young women (15-24) in Liberia, the unemployment rate is 8 percent, double the rate among young men (LISGIS 2010). Most of these gaps can be explained by differences across individuals, especially in educational attainment, skills training, and years of experience. But segregation, market segmentation, and discrimination do play a role in determining these individual characteristics. Women have fewer opportunities for education or training, less access to credit, a larger share of domestic responsibilities, and less independence and control over their own lives. In Liberia, women comprise half of the employed, but only about one-quarter of paid employment (LISGIS 2011). Fourteen years of civil war in Liberia devastated the country ’ s infrastructure and institutions, and left a generation of young people with very low levels of education and training. Girls were particularly disadvantaged. Usage context: supporting mention, primary mention, background mention.

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Input: the sample frame were surveyed. In this way, all the camps in the sample frame were selected in the sample and were surveyed. For host households, areas within 5-kilometer radius of the camps were divided into EAs of 300 by 300 meters, with only residential EAs as per Open Street Maps included in the sample frame. SESRE, on the other hand, used a stratified, two-stage cluster sample design. Initially, camps were divided into EAs, and pseudo EAs were created from the proGRES database by grouping 150-200 households consecutively. EAs and households within those EAs were then selected. For host households, EAs adjacent to refugee camps were used as the sampling frame. While the definition of host households differed between SPS and SESRE, both surveys shared similarities in the selection of EAs and the random sampling of households within those EAs. In SPS, all households within the selected EAs for host community sampling were listed, and 12 households were randomly chosen and surveyed per EA. SESRE also selected 12 refugee and host households per EA, treating EAs as the Primary Sampling Unit and households as the Secondary Sampling Unit. (i) The distinct sampling designs and objectives of the two surveys render

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Input:
**7.3 Environmental and Social Commitment Plan (ESCP)**

The ESCP sets out legally binding commitments for the borrower related to environmental and social management, including: (i) operationalization of the grievance redress mechanism within 60 days of project effectiveness; (ii) disclosure of the ESMF and LMP on the borrower's website within 30 days of Board approval; (iii) submission of semi-annual E&S progress reports to the Bank; and (iv) maintenance of the MHPSS referral pathway documentation and making it available to Bank staff upon request during supervision missions.

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Input: Due to our research design and the complexity of introducing a third grouping who would play outgroup in the behavioral experiments regardless of partner identity, we exclude PRL from the main analyses presented here. 5 Data were also collected six months after the end of the training but this was heavily disrupted due to the outbreak of the COVID-19 pandemic. In Lebanon, this resulted in a change to the method of data collection (from in-person to telephone) and in Jordan, an end to data collection entirely. In Jordan, this had a more pronounced effect on the control group, due to the scheduling of data collection and implementation of restrictions in Jordan. Given these complexities, we do not present results from these analyses. 6 In addition, we attempted to collect information on the extent of social and economic interactions between hosts and refugees. At baseline, almost 95 % of respondents in both the treatment and control group reported such interactions. For this reason, we do not include this information in these analyses. Usage context: supporting mention, background mention, primary mention.

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Input: A number of different road indicators are available and we choose road line type to use in the analysis. Road type is defined by the following: The reference category (0) points out squares with dual lane / divided highways, other primary roads, or road connectors within urban areas (types 1 or 8 in the ESRI dataset). The second category include secondary roads (type 2), and the third combines squares with informal or tertiary roads (tracks, trails or footpaths) or no road registered at all (types 3 and 0, respectively, in the ESRI dataset). Figure 4 overlays the types of roads in the original dataset before our recategorization. The shaded area represents the portion of Africa for which we code Usage context: background mention, primary mention, supporting mention.

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Input: If registration is linked to the provision of services or other entitlements, there may be strong incentives to register births and new arrivals and weak incentives to deregister, leading to the inflation of the register over time or even instances of fraud and abuse (e. g. multiple registration, “ borrowing children ” etc.) (UNHCR 2003). Consequently, data from a refugee register may overestimate the number of refugees, requiring periodic corrective action through the verification of records. For example, in 2014 a verification of registration records for Somali refugees in the Dadaab camps in Kenya led to the deactivation of tens of thousands of records for individuals that are believed to have returned spontaneously to Somalia (UNHCR 2015). Additional problems with refugee registers include security concerns or inclement weather preventing refugees from accessing registration sites (UNHCR 2003) and the application of data protection principles. Registration of IDPs Individual registration is not as common a method of estimating numbers of IDPs as it is for refugees.

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Input: General population registers In a small but growing number of countries, information from the central population register is the main source of migration statistics. 80 While population registers may generate statistics on both internal and international migration (if they record changes of residence, and international arrivals and departures) they do not typically record reasons for movement. However, it may be possible to link data from the central population register to those from immigration or border authorities to identify refugees and asylum- 76 Using standard ILO definitions, Labor Force Surveys collect data on work-related issues and provide a basis for measuring employment and unemployment indicators. They are typically conducted monthly in developed countries and quarterly or annually in developing countries. 77 Supported by USAID and implemented by ICF International, the DHS Program has collected, analyzed and disseminated data on population, health, HIV and nutrition through more than 300 surveys in over 90 countries. 78 MICS is an initiative of UNICEF that assists countries in collecting and analyzing health and education data in order to fill data gaps for monitoring the situation of children and women. 79 Many refugee hosting countries issue a form of identification, either specific to refugees or based on national identification documents or those issued to non-national residents. In many cases where such documents are not issued, refugee identity cards are issued in collaboration with UNHCR. 80 A population register provides a mechanism for the continuous recording of selected data on the resident population including a unique identification number, date of birth, sex, marital status, place of birth, place of residence, citizenship and language and possibly also socio-economic data, such as occupation or education. Usage context: supporting mention, background mention, primary mention.

national identification documents
population register

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Input: While both sons and daughters of the head may be expected to be more likely to stay in the community than other initial household members, patri-locality would make this probability higher for boys than for girls. In sum, this means we are using a set of six instruments. Although we can show that statistically convincing and close to identical results can be obtained by only using a subset of these instruments, we use the full set of instruments in the reported results. While our main measure of migration (Mi) is an indicator for having moved, we also substitute this for the log of the distance moved (kilometers from the original community of the location in which the individual was found in 2004, ‘ as the crow flies ’, set to 0 for non-movers). We will also extend the multivariate analysis to explore the role of moving to more urbanized areas and the role of sector movement in raising consumption growth. 6. Regression Results Table 9 presents the basic results for the initial household fixed effects (IHHFE) and 2SLS estimates (means for covariates are in Appendix Table 1). For each we estimate using an indicator for having moved and a measure of distance of the move. The 2SLS estimates in column (3) and (4) use the six instruments defined above. In Table 10, we present the first stage results of regressions explaining migration or the distance traveled in migration.

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

UNHCR Statistical Online Population Database

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Input: refugees lived in poverty, compared to 17 percent of hosts, in 2018 (World Bank, 2019). In Kalobeyei Settlement in Turkana County in Kenya, more than half of refugees are poor (58 percent), higher than the national poverty rate of 37 percent, lower than the poverty rate in Turkana County but comparable to the average poverty rate of the 15 poorest counties in Kenya (UNHCR and World Bank Group, 2020). About 72 percent of registered Venezuelans in Brazil live in extreme poverty, compared to 48 percent of Brazilians (Shamsuddin et al., 2021). Similarly, this report finds that poverty rates in Ethiopia’s refugees in camps are much higher than for host communities. Yet, refugee inflows can significantly affect host communities. Governments have been preoccupied with whether the arrival of large numbers of people in specific locations creates risks or opportunities for decades. Experience has shown that opportunities typically result if the influx of refugees is managed well and brings benefits to host communities similar to those of voluntary migrants. A recent review of the literature on refugee effects on host communities showed that most studies find a positive or non- significant effect of forced displacement on hosts’ employment, wages, and household well-being.

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Input: For example, IDPs who subsequently cross international borders may be counted as both IDPs and refugees (e. g. in the case of the Syrian displacement crisis). Table 4: Stocks and Flows Stock Increases Decreases Asylum- seekers  New applications for asylum, separately identifying individuals who were previously IDPs  Positive decisions (convention status, complementary protection status)  Rejected  Otherwise closed Refugees  Spontaneous arrivals (group recognition, temporary protection, individual recognition), separately identifying individuals who were previously IDPs  Resettlement arrivals  Births  Administrative corrections  Repatriation  Resettlement  Cessation  Naturalization  Deaths  Administrative corrections IDPs  New internal displacement  Births  Administrative corrections  Cross border flight, becoming an asylum-seeker or refugee  Return  Settlement elsewhere in the country  Local integration  Administrative corrections Source: UNHCR Global Trends, IDMC Forced Displacement Data Model

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Input:
Of all countries in the World Bank's WDI, only 60%
(40% of the analyzed countries) had an inflation figure for the most recent 2019-2020 period. The IFS
data reported similarly on only half of the countries. This was last checked on August 31, 2021; WDI
data identifier FP.CPI.TOTL.ZG, and IFS data identifier PCPI ~~P~~ C ~~P~~ P ~~P~~ T.

The paper highlights the new price monitoring capabilities using surveys from the World Food Programme (WFP) gathered in 25 fragile and conflict-affected countries.

Subnational food prices have been surveyed in many countries for years by
humanitarians to inform their country operations. Well-known data bases are
those from the WFP, FEWS NET and the Food and Agricultural Organization
(FAO). [6] The paper focuses on raw monthly data from the WFP, but parts of the
discussion, and particularly the methods developed here, could apply to similar
data sets. [7]

The paper gathered all end-of-August data available from the WFP Vulnerability Analysis and Mapping (VAM) unit as of September 21, 2021.

WFP Vulnerability Analysis and Mapping (VAM) unit

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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.

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Input: The cross-dimensional poverty cut-off is defined as k = 50 %, with those deprived in half or more of the weighted indicators identified as multidimensionally poor. 4. Data Data on forcibly displaced populations are scarce, with many household surveys excluding refugees and IDPs from the sample framework. To ensure that MPI results are representative of these communities and that they can be disaggregated for comparative analysis, an initial review of possible data sets was conducted. Feasibility was determined based on the availability of sufficient sample sizes for forcibly displaced persons for quantitative analyses, as well as inclusion of many of the indicators (on health, education, living standards, etc.) 14 A household is deprived if the respondent reports feeling moderately or very unsafe when alone at home, walking alone after dark, or walking around during the day. In Sudan, the indicator on the ‘ feeling safe from crime and violence when at home ’ was not available, and the indicator only considers answers to the questions on safety when walking alone. 15 Unprotected dug well, unprotected spring, carts with tank, tanker-truck, surface water, or other are considered as unsafe water sources according to international guidelines. See https: / / washdata. org / monitoring / drinking-water. 16 Pit latrine without slab, bucket, hanging toilet, and no facility (open defecation) are considered as unimproved sanitation facilities according to international guidelines. See https: / / washdata. org / monitoring / sanitation. 17 According to the ILO definition, those who did not participate in employment in the last four weeks (and have no work to return to) are actively looking for work and are available to start, or those currently waiting to start work are classed as unemployed. See https: / / www. ilo. org / ilostat-files / Documents / description_UR_EN. pdf. Usage context: supporting mention, background 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.

general population registers
sample surveys

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Input: The long-term consequences of these trends are signiϐicant, as diminished educational outcomes and social isolation can hinder successful integration into host communities. Conversely, sustained social and educational integration efforts are vital for positive outcomes. For instance, studies indicate that long-term integration can be hampered by social, economic, and institutional barriers (Chiswick and Miller, 2014), while interventions focused on language support and community engagement can lower these barriers (Ozden and Wagner, 2020). Further, speciϐic interventions aimed at removing obstacles to education for children on the move can contribute signiϐicantly to better integration outcomes (Schuettler and Caron, 2020). This paper beneϐits from key information coming from administrative data on educational records of Ukrainian refugees in Italy for the academic years 2021-2022 to 2023-2024 for grades 6 to 13. This provides a unique opportunity to examine enrollment, attendance, test performance, and other indicators of integration into the Italian educational system. Supplemented by survey data collected in 2023-2024, this study offers an overview of the challenges and opportunities faced by Ukrainian students in secondary schools and highlights areas for potential policy development. This study advances the literature by adding empirical evidence on the short- to medium-term educational impacts of displacement on young refugees within a European host country, offering insights into the role of education policy in mitigating human capital losses. It also contributes to discussions on human development by identifying factors that support or hinder integration, highlighting pathways for improving educational and social outcomes for refugee students. Results highlight that despite gradual improvements, enrollment rates remain signiϐicantly lower among refugees compared to native and other foreign students. Ukrainian refugees also demonstrate higher absenteeism and lower academic performance, particularly in subjects requiring language proϐiciency such as Italian and English. However, good performance in mathematics suggests potential strengths linked to their prior educational backgrounds. Despite these challenges, teachers seem to be more inclined to recommend Ukrainian refugees for high-track education compared to other newly arrived foreigners, indicating potential optimism about their academic capabilities. The

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Input: The LFS reference week design captures the contemporaneous employment status of respondents at the time of interview, making it sensitive to the specific week in which households are interviewed within a quarter. To address seasonality, the LFS staggers interviews evenly across the 13 weeks of each quarter, ensuring that agricultural and other seasonal employment cycles are represented proportionally in the quarterly sample. We account for residual seasonality in our models by including a full set of quarter-of-year fixed effects and their interactions with the rural indicator.

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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.

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Input: The curriculum included entrepreneurship principles, market analysis, business management, customer service, money management, and record-keeping. The EPAG program was implemented by four NGOs who were selected by the Liberian Ministry of Gender and Development through a competitive bidding process: the Community Empowerment Program (CEP), Liberia Entrepreneurial and Economic Development (LEED), the International Rescue Committee (IRC), and the American Refugee Committee (ARC). Two of these organizations (ARC and IRC) further subcontracted to four Liberian NGOs. 4 The service providers were responsible for developing training curricula, identifying training venues, 5 making arrangements for childcare services, assisting with the mobilization of the nine target communities, and participating in the recruitment of training participants. The EPAG program differed from many training programs in a number of ways. First, performance bonuses were awarded to training providers that successfully place their graduates in jobs or micro- enterprises. The bonus was the last payment that the service providers received under their contracts. These were paid about 12 months after the start of training, or around the same time as the midline survey. Second, a variety of contests and competitions were also held among EPAG trainees (such as attendance prizes, quizzing contests, business plan competitions, etc.).

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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: primary mention, background mention, supporting mention.

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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.

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Input: The upcoming section provides an overview of the situation facing Venezuelan migrants in Colombia, setting the stage for understanding the context within which our study is situated. Section three offers a comprehensive description of the VenRePS-Kids study, covering aspects such as the sampling frame, the instrument used for data collection, the representativeness of the study, its implementation process, and an overview of descriptive statistics. Section four delves into the human development disparities observed among forcibly displaced chil- dren and adolescents, providing detailed insights into the nature of these gaps. In section 9 Usage context: supporting mention, primary mention, background mention.

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Input: A recent global hazard analysis generated a comprehensive database of hazard events during 1975- 2007 from observed data and of event probabilities from geo-physical models (ISDR 2009). We combined this hazard information with city-specific population projections 2 It should be noted that well-documented evidence for such externalities is quite scarce. Their importance is usually taken as given: “ A building collapse may create externalities in the form of economic dislocations and other social costs in addition to the economic loss suffered by the owner. The owners may not have taken these consequences into account when evaluating specific mitigation measures. Consider the following example. A building toppling off its foundation after an earthquake could break a pipeline and cause a major fire, which would damage other homes that had not been affected by the earthquake in the first place. “ Kuenreuther and Roth (1998). See also www. quakesmart. org / index. php? option = com_content & view = article & id = 92 & Itemid = 209. But some experiences have been documented: “ As shown by research on the Great Hanshin-Awaji Earthquake, including that conducted by the Architectural Institute of Japan, Architectural Institute of Japan (1997), houses with inferior earthquake-resistant quality triggered large negative externalities in the neighborhood. For example, broken fragile houses blocked transportation networks, thereby preventing effective fire fighting and, by severing lifelines, they made recovery more difficult. ” (Nakagawaa et al. 2007).

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

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Input:
[2 Available at http://faostat3.fao.org/home/index.html (accessed 11 June 2013)](http://faostat3.fao.org/home/index.html) 3 Smith (1998) reports that, at the time, for 18 out of the 99 countries, the CVs are estimated based on analysis of nationally representative HCES. The rest of the countries' CVs are predicted either from measures of income distribution or as the mean CV estimated for other countries in the same region.

4 In 2012 the FAO revised its distribution to be the skew-normal distribution (Azzalini, 1985), which generalises the normal distribution to allow for skewing.

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Input: 5. Time Use and Child Labor: The fifth module examined how children spend their leisure time, their involvement in child labor, and interactions with peers. 6. Pro-social Preferences and Migration Outlook: The sixth module concentrated on adolescents ’ pro-social behaviors, such as altruism and trust, and explored their expectations and intentions regarding migration. 7. Socio-emotional and Mental Health: The final module involved the administration of various scales to assess socio-emotional well-being and mental health, includ- ing trauma, behavioral problems, anxiety, and depression. The scales include the Trauma Symptom Checklist for Young Children (TSCYC), Strengths and Difficulties Questionnaire (SDQ), General Anxiety Disorder Scale (GAD-7), and Patient Health Questionnaire (PHQ-9). All these scales and the corresponding outcomes that we evaluated are described in the next subsection. The survey also employed the Peabody vocabulary test to evaluate the cognitive devel- opment of all participating children and adolescents. A summary of the survey modules is depicted in Table A. 1. III. C Sample comparability While Medell ´ ın ranks as the third city with the highest migration in Colombia, it is crucial to recognize the degree to which migrants arriving in the city differ from those migrating to other regions in Colombia. Usage context: background mention, supporting mention, primary mention.

Trauma Symptom Checklist for Young Children

Strengths and Difficulties Questionnaire

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Input: 1. Introduction Sub-Saharan Africa is the youngest region in the world, and the world ’ s fastest-growing. Between 2010 and 2025, the number of people between 15 and 24 will grow to 250 million – a net increase of nearly 50 percent. Over the next decade, roughly one million young people will enter the labor market each month in Sub-Saharan Africa. However, these young people often enter the labor market too early and unprepared. Although access to education is growing, illiteracy remains high and schooling low: among the 32 Sub-Saharan African countries in the Barro-Lee (2010) data set, nearly 40 percent of women aged 15 and above have received no education at all; and the most recent (2007-2011) statistics in the World Bank ’ s Edstats data reveal that female literacy is less than 60 percent, on average. 1 This lack of preparedness contributes to a growing problem of youth unemployment. Quantifying the level of unemployment is bedeviled by lack of data and measurement issues. Household and labor force surveys throughout Africa usually record unemployment rates of less than 10 percent, 2 but those figures belie the extent of underemployment and vulnerability. Those same surveys indicate that the vast majority of working adults have insecure work in the informal sector, on the family farm, or in less- productive or unremunerated labor. Usage context: supporting mention, primary mention, background mention.

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Input: These calculations conﬁrm our earlier assessment. 5 Conclusion Combining data from a household survey and an 11 % census of the population, we have estimated destination choice regressions for Nepalese internal migrants. Results show that population density, social proximity, and access to amenities exert a strong inﬂuence on migrants ’ choice of destination. These results conﬁrm earlier work on the factors aﬀecting the subjective welfare cost of isolation (Fafchamps and Shilpi, 2008). 29 Usage context: background mention, primary mention, supporting mention.

household survey
11 % census of the population

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Input: Addis Ababa All Hosts Increased economic opportunity Increased insecurity Are taking our land Figure 7.6: Host beliefs about refugee impact in Ethiopia Source: World Bank Staff based on SESRE 2023. 50 The numbers are combined here, but mainly measures employment competition since very few are concerned about wage competition. 0 5 10 15 20 25 30 35 40 Eritrean Somali South Sudanese Addis Ababa All Hosts Improved Infrastructure Improved Services Figure 7.8: Positive experience due to refugees Source: World Bank Staff based on SESRE 2023. Markets and Opportunities 67 Overall, hosts and refugees show similar trust rates in each other; still, refugees are generally more trusting. Questions about the trustworthiness of hosts and refugees reveal that most people either trust both (hosts and refugees) or neither group. Only 17 percent of hosts trust other Ethiopians but not refugees, and only 10 percent of refugees trust other refugees but not Ethiopians. In comparison, 39 percent of hosts and 55 percent of refugees trust both groups. Once again, hosts’ trust towards refugees is highest in the Somali domain (67 percent) and lowest in the South Sudanese domain (29 percent). On the other hand, refugee trust towards hosts is lowest in the Eritrean

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

UNHCR statistical population online dataset

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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.

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Input: obtained from the multilevel logistic model. Thus, I am conﬁdent that I did not lose substantial statistical information by dichotomizing this variable. 6. 2 Independent Variables 6. 2. 1 Socio-Demographic Variables I control for standard socio-demographic variables that can aﬀect citizens ’ acceptance of government ’ s right to make people pay taxes. A question prob- ing respondents on their household income was not included in the fourth round of Afrobarometer surveys. Asking respondents to quantify their in- come can be problematic in the context of developing economies, where in- dividuals are often embedded in barter or commodity exchange, rather than, market economies. There are, however, reasonably good proxies including whether respondents own a television, radio, car, and mobile phone, and use the internet. Age, education, employment, and urban or rural residence are demographic factors that also aﬀect household resources. 6. 2. 2 Experience with Paying Taxes or Fees It is diﬃcult to assess just how ubiquitous taxes are in ordinary Africans ’ lives. There has not been any systematic eﬀort to take stock of the types and amount of taxes citizens pay across Africa. Similar to pre-modern European states, African states ’ revenue raising capacity is generally low. Usage context: primary mention, supporting mention, background mention.

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Input: 3 population study2 (Brown et al, 2019) revealed that 78 percent of the population of registered refugees lived below the Jordanian poverty line, and between 2017 and 2019, there was only a 2- percentage point reduction of highly vulnerable cases. 3 UNHCR (2018a) also reports that close to 37 % of the registered Syrian refugees in Jordan are separated from a family member. Household structures have often been fluid. Many Syrian families sent members ahead to Jordan to settle and sometimes, after the reunification of the rest of the family in Jordan, male family members traveled on to Türkiye or to Europe (UNHCR, 2018a). These separations likely affected families emotionally and economically. However, little is known about the changes in economic well-being over time or how gender inequality has shaped poverty and expenditure outcomes. We use two waves of data from a unique household survey, the United Nations High Commissioner for Refugees (UNHCR) Home-Visits survey for 2013-14 and 2017-18. First, we create comparable measures of expenditure per capita over time. Then, we assess whether certain types of households are more likely to be below the median of the per capita expenditure distribution in each time period. Usage context: supporting mention, background mention, primary mention.

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Input: and 6 percent for hosts, and in the camps is 13 percent for refugees and 12 percent for hosts. 0.05 0 0.1 0.15 0.2 0.25 0.3 0.35 Elementary Occupations Craf/Related Trades Service/Sales Machine Operators Associate Prof. Clerical Support Professionals Share of Refugees Observed Predicted according to observables Figure 3.26: Refugee occupation concentration Source: World Bank Staff based on SESRE 2023. Jobs and Livelihoods 38 In Addis Ababa, refugee girls—like boys—are much less likely than host counterparts to work or attend school, and they are more likely to be unemployed or NEET. They are even less likely than refugee boys to be in school and more likely to be NEET (23 percent for girls relative to 15 percent for boys—Figure 3.28). In camps, refugee girls look more like their host counterparts regarding schooling and labor force participation. However, among those in the workforce, their relaxed unemployment rate is much higher (55 percent for female refugees and 36 percent for female hosts). Boys in camps have higher schooling rates (75 percent relative to 65 percent for hosts), reflecting their higher propensity to stay enrolled in primary or secondary schooling after the typical completion age, especially in South Sudanese camps where 84 percent

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Input: There were in total 1, 6 million refugees by November 2014. Data on the number of new ﬁrms and their ownership characteristics and value are provided by the Turkish Chamber of Commerce. 7 Data on total sales and gross proﬁts are obtained from the Turkish Ministry of Science, Industry and Technology. Other economic indi- cator variables, such as population and unemployment rates, are obtained from Turkish Statistics. Since Syrians usually have guest status rather than resident status during the period of analysis, they are not counted in oﬃcial statistics such as province population and unemployment rates. Turkey is oﬃcially divided into 81 provinces and that is the level of our analysis and variables throughout. The Chamber of Commerce provides data on the number of new ﬁrms and the num- ber of new foreign-owned ﬁrms at the provincial level. Enterprises deﬁned as ﬁrms do 11 Usage context: supporting mention, primary mention, background mention.

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Input: Survey of Refugees in Ethiopia (SESRE) contribute to the debate on policies? The Socio-Economic Survey of Refugees in Ethiopia (SESRE) is a representative survey of the refugee population in Ethiopia and their host communities, the first of its kind.9 Ethiopia made significant progress over the past few years in articulating more progressive and comprehensive refugee responses. In 2023, the GoE included new pledges and commitments made in the 2023 Global Refugee Forum, including a significant shift in its refugee management policies. This includes improving the socio and economic opportunities for refugees through an agenda to transform camps into human settlements and including refugees in national services for education, including secondary education and health (UNHCR, 2024). Systematically collecting high-quality data on refugees and their hosts in one survey is pertinent to inform the GoE’s roadmap and programs to address the development needs of refugees and hosts. The national household survey of Ethiopia–Household Welfare Statistics Survey (HoWStat)—excludes the majority of displaced populations (Internally Displaced People [IDPs] or refugees) from its sample of households. Thus, we have limited in-depth information on the socio-economic outcomes—including on poverty— for refugees across all camps in Ethiopia to compare with Ethiopian hosts. SESRE collected data from November

Socio-Economic Survey of Refugees in Ethiopia

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Input: Most importantly for the purpose of the analysis is the fact that the survey provides individual-level data on own schooling and parents ’ schooling for all adults in the sample, which is quite rare in household surveys from developing countries. Also, the survey provides the actual years of schooling completed and not only the highest educational degree attained, which allow observing the schooling variable with precision.

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

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Input: Without army protection most parts of the North, especially Kidal remain inaccessible to those working for the central and local government. 3 Armed bandits are active and IED explosions as well as violent attacks on the MINUSMA peacekeeping forces are regular occurrences. Under these circumstances, data collection is very difficult. INSTAT, the National Bureau of Statistics, has not been in a position to collect information from northern Mali since the beginning of the crisis. To our knowledge, our surveys implemented by a private survey entity, GISSE, are the only systematic and representative effort to collect data in north Mali since the crisis. They offer a unique database providing a crucial perspective that would otherwise not be reflected in academic analyses and policy level decision-making, and a perspective that is indispensable in any attempt at understanding the situation in Northern Mali. 4 Preceding the Accord on Peace and Reconciliation in Mali (Accord pour la paix et la réconciliation au Mali) (hereafter, the Peace Accord) of May and June 2015, four peace accords had been signed between the government and Toureg and Arab armed groups in 1 Kel Tamasheq (those who speak Tamasheq) is synonymous for Tuareq. 2 Francis David (2013): The regional impact of the armed conflict and French intervention in Mali. NOREF, Norwegian Peacebuilding Resource Centre. 3 Assessing Recovery and Development Priorities in Mali ’ s Conflict-Affected Regions. Draft Report of the Joint Assessment Mission for Northern Mali (January 2016), p. 15-16. 4 All data can be downloaded from www. gisse. org. Usage context: primary mention, supporting mention, background mention.

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Input:
Firms listed in the NBS registry without a contact telephone number were also excluded from the sampling
frame. Hence, all survey results should be interpreted as representative of more formal business activities.

To ensure that robust estimation results can be obtained for different subpopulations, the survey used a
dedicated sampling strategy. Based on information from the NBS, all registered firms were divided into
five distinct strata, depending on their reliance on transport systems. Ordered from low to high transport
reliance, these strata contain firms from the following sectors:

Direct asset losses are the most tangible impact of disasters on firms. In high-income countries, a range
of institutions, such as insurance companies or governmental organizations, collect data on direct losses
(for the United States, see, for example, Smith and Katz 2013). In developing countries, where insurance
markets and data collection are limited, less is known about the direct losses that firms incur. While
databases such as EM-DAT provide some data on aggregate direct disaster losses, few quantitative firmlevel studies have been conducted. One exception is De Mel et al. (2012), who analyze the impact of the

Firms incur a wide range of losses due to disasters, both in terms of direct damages and indirectly
transmitted costs. Based on the data collected for this study, Appendix B offers a full discussion of the
scale and type of firms' disaster losses.

The survey data reveals that flood risks are high throughout most of Tanzania and confirm that firms face
substantial recurring losses.

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Input: restricted to workers with completed secondary education. Among workers with completed secondary, 30 percent of refugees and 50 percent of hosts are in high-skill occupations (Figure 3.25). Among only women, these numbers are 20 percent and 50 percent, respectively. Instead, refugee men and women in Addis Ababa are over- represented in crafts and related trades (typically classified as medium-skill occupations). 0 20 40 60 80 100 Addis Hosts Addis Refugees Current Addis Refugees COB Salary (employment/casual labor) Crops/livestock Donations(NGO/gov) Remittances (local/international) Other (rental income, PSNP, pension) Percent 0 20 40 60 80 100 Percent Addis Male-Headed Addis Female-Headed Figure 3.21: Household primary income source Source: World Bank Staff based on SESRE 2023. Note: “COB” refers to livelihood strategies in their country of birth. a. Pre-post migration b. By gender of head Table 3.2: Labor force statistics Addis Hosts Addis Hosts Labor force participation rate (strict) 66% 46% Unemployment rate (strict) 12% 63% Labor force participation rate (relaxed) 72% 67% Unemployment (relaxed) 19% 75% Employment-to-population ratio 58% 17% Source: World Bank Staff based on SESRE 2023. Note: Labor force participation ratio is the share of working-age people who are engaged in the labor market, either employed or unemployed. Unemployment is the

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Input: FE remove the effect of individual-specific time-invariant characteristics so as the net effect of the predictor variable on outcome variables can be assessed, per the following equation: 𝑌 ௜ ௧ ൌ 𝛼 + 𝜇 ௡ + 𝛽𝑇௧ + 𝛾𝐷 ௜ + 𝛿ሺ𝑇 ∗ 𝐷ሻ ௜ ௧ + 𝜃ଶ𝐸ଶ ൅.. ൅ 𝜃 ௡ 𝐸 ௡ ൅ 𝜀 ௜ ௧ (3) where 𝐸 ௡ is entity n (i. e. the individual volunteer). Since they are binary (dummies), there are n-1 included in the model (i. e. 758 individual volunteers). 𝜃ଶ is the coefficient for the binary regressors (the 758 volunteers). Additionally, we propose dealing with attrition in two ways. First, we utilize the standard “ Manski Bounds ” approach (Horowitz and Manski, 2000) by imputing upper and lower bound estimates for missing data on estimated outcomes of interest at follow-up, where lower bound estimates take the lowest possible value and upper bound estimates take the highest possible value for individuals who could not be tracked over time. This allows us to provide the two extreme possible scenarios for estimated impacts had data been successfully collected for attritors. Second, we use the Inverse Probability Weighting (IPW) procedure to establish narrower bounds that might provide a better sense of whether there is a robust treatment effect. This entails first estimating a probit model that predicts the probability of data being observed (i. e. not attrition) using a set of covariates at

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Input: Due to the variations in weight and height ratios among children and adolescents according to gender and age, the benchmarks for determining nutritional status are specifically tailored to these factors. We adhere to WHO guidelines to calculate the standardized BMI values for minors. A BMI exceeding one standard deviation (SD) from the mean suggests overweight, while a BMI less than minus one SD indicates underweight. 16 Health status is assessed through a binary variable, assigned a value of one if the caregiver has reported any health issues such as disease or chronic pain, accidents, dental pain, surgical interventions, or preg- 14For the Colombian households the wealth index is measured with contemporaneous data. 15This procedure restricts the sample to the common support of the propensity score for being a forced migrant and weights observations for Colombian kids by a non-parametric function of the propensity score. This procedure has been shown to increase the estimate ’ s efficiency. 16Furthermore, a BMI greater than 2SD is indicative of obesity risk, and less than- 2SD signals a risk of severe thinness. 33

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Input:
Data on the structural and cyclical characteristics of national economies comes from the World Bank's World Development Indicator Database [9] and UNCTAD-STAT; [10] the figures on education are sourced from Barro & Lee (2013); [11] those on the real effective exchange rate (REER) are taken from Darvas (2012); [12] and metal- and oil-price figures are sourced from the IMF's Primary Commodity Prices database. [13] Referring to the original datasets will provide further details on the methodology and sources used.

We need first to describe inequality and poverty levels in the affected region. We define the poor as the individuals in the bottom quintile in terms of consumption or income. Therefore, the parameter �� is equal to 20%. To estimate �� and ��, we use the World Development Indicators database, which provides the income share of the bottom 20%. Figure 3 shows the result, highlighting the large variability - and lack of correlation - between inequality and national income level.

In this national-level analysis, and consistent with our focus on the socioeconomic drivers of resilience, we use a very simple methodology. We use the Global Building Inventory database from PAGER, by USGS, which provides a distribution of building types (buildings only, not contents) within countries across the world (USGS 2015). This typology has been developed to assess vulnerability to earthquakes but here we use it for all hazards.

UNCTAD-STAT
Primary Commodity Prices database
World Development Indicators database

Global Building Inventory database from PAGER

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Input: III THE VENREPS-KIDS STUDY In this section, we offer a detailed overview of the VenRePs-kids Study, covering its de- sign, implementation, the questionnaire utilized, and the primary outcomes that will be employed to evaluate the human development disparities between forcibly displaced children and adolescents and their peers in host communities. III. A Design Location. Our study is conducted in Medell ´ ın, Colombia ’ s second-largest city, following Bogot ´ a. Medell ´ ın was chosen for this study because it hosts the third-largest Venezue- lan migrant population in the country, trailing only Bogot ´ a and C ´ ucuta, as indicated by the 2018 population census data. Additionally, previous research has demonstrated that survey response rates among migrants in Medell ´ ın are notably high. For instance, a na- tionally representative survey of Venezuelan migrants conducted in 2018 — which was representative across Colombia — revealed that Medell ´ ın had the highest response rates among migrants, whereas Bogot ´ a recorded the lowest (Ib ´ a ˜ nez et al. 2022). This finding supports the decision to focus our study exclusively on Medell ´ ın, also considering the challenges and high costs associated with tracking a highly mobile population longitu- dinally in previous research efforts.

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Input:
The top 5 protection incidents reported in the region are homicide (30 per cent), assault and battery (29 percent),
extortion of property (16 per cent), destruction of properties (13 per cent), and looting (12 per cent). Also, those
protection incidents affected 99.88 percent of Internally displaced persons (IDPs), 0.11 percent of refugees, and 0.01
per cent of asylum-seekers. The protection incidents affected more males (53 per cent) than females (47 per cent),
and the protection incidents affected the age group (0 to 17), children, who represent 44 percent of all victims
reported in September 2022. In addition, the perpetrators of those protection incidents are armed groups (46 per
cent), host communities (26 per cent), others (23 per cent), and unknown (5 per cent). It is worth mentioning that 1.3
percent of the regional population, compared to September 2022 regional data, was affected by the protection
incidents reported in September 2022.

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Input: 10 consumption or expenditure is measured in per-capita terms and has implications for other indicators of well-being such as housing, rents, or crowding. The Demographic and Health Surveys (DHS), Multiple Indicator Cluster Surveys (MICS) and Living Standards Measurement Surveys (LSMS) are the most common household surveys used to produce comparative statistics on well-being across time and countries. The DHS and MICSs define household members as (i) usual residents or people who slept in the dwelling the previous night and who (ii) share living arrangements and (iii) share food (ICF International, 2012; UNICEF, 2013). The LSMSs define household members as (i) people who slept in the dwelling three or more months of the last 12 months and (ii) share food (Grosh and Munoz, 1996). 7 While the definitions differ, they are defined on similar concepts and are unlikely to lead to major differences in key household characteristics. The UNHCR has definitions for household that resemble the definitions used by MICSs and LSMSs but uses the concept of “ case ” as unit of observation. The UNHCR defines a case as: “ A processing unit similar to a family headed by a Principal Applicant. Usage context: primary mention, background mention, supporting mention.

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Input: 8 agreements that did not fully satisfied either party (Ndayirukiye and Takeuchi 2014). This tension related to land, and who has a claim to the land, can lead to social tensions in communities with higher levels of return. Figure 3 – Refugees in Tanzania in 2005 by province of origin in Burundi Note: The number in brackets is the number of refugees in Tanzania in 2005 which was originally from the given province in Burundi. This information comes from (UNHCR 2021b). The number in parenthesis is that number as a percentage share of the population of the provinces as estimated in 1990 Burundi Census. An important question for our hypotheses is the degree to which there is evidence of migration-related societal divisions in the country. There is no direct quantitative evidence on identity issues (i. e. returnees versus stayees), but we have data on attitudes towards emigration, remittances and return that can provide insights on these identities and even be a proxy for migration-related identity in some cases. Overall, attitudes towards emigration and return are mixed and show that there is scope for the existence of migration-related divisions. In Table 1 we report the share of respondents who agreed with different statements regarding emigration, remittances and return. Usage context: background mention, supporting mention, primary mention.

data on attitudes towards emigration, remittances and return

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Input:
`o` They also pushed for career rotation and continuous support for **education** as a foundation for
society. While both groups shared a commitment to youth empowerment, the female group
leaned more toward social and psychological well-being, whereas the male group prioritized
leadership, structure, and legal safeguards.

## **HEALTH AND DISABILITY**

**Health and disability**

A small percentage (7%) identify as having a disability [2] according to the
Washington Group classification. Within youth with disabilities, **males**

**constitute the majority** (72%) compared to females (28%).
Disproportionate impact of disability on young men should be the driver
of additional data collection to develop specific programs to address
their needs and exposure to risks.

**Person with disabilities by**

**gender**

**Male**

**72%**

 The majority of young people in northwest Syria, (84%), do not
face any health problems conditions. However, a significant 16%
reported facing health issues, with varying levels of access to
health services and medication.
 Regarding access to health services, the results indicate that only 47% of those with health problems,
conditions or disabilities have access to health services, while 53% do not.
 56% of youth with health problems, conditions or disabilities **do not have access to adequate medication** .

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[2] https://www.washingtongroup-disability.com/question-sets/

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Input: month placement and support phase in which the trainees were supported in their transition to self or wage employment. Upon recruitment, the participants are assigned to a"Job Skills (JS)"track or a"Business Development Services (BDS)"track. When possible, the participant's track preference was honored; however, the demand for the Job Skills track greatly exceeded the supply, so the remaining trainees were placed into the BDS track. In the first round of training, the proportion of Job Skills track places was limited to 35 % of the total training places available given the expectation that few wage jobs will be available in the Liberian job market. The Job Skills track provided training in six areas: 1) hospitality, 2) professional cleaning / waste management, 3) office / computer skills, 4) professional house / office painting, 5) security guard services, and 6) professional driving. These areas were determined based on independent labor market assessments, a review of the available market data, and input from EPAG ’ s private sector partners. All Job Skills trainees received training in entrepreneurship skills as well. The BDS training taught young women how to identify micro-enterprise opportunities based on an assessment of market needs, and how to grow and manage any existing businesses they already had. Usage context: background mention, supporting mention, primary mention.

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