Input: This paper analyzes data from the initial wave of VenRePS-Kids, conducted from Oc- tober to December 2022, to outline key demographics and stylized facts about forcibly displaced children and adolescents. Initially, we examine the human development dis- parities of forcibly displaced Venezuelan children and adolescents in comparison to their Colombian counterparts. Our approach to human development is broad, covering physi- cal, cognitive, socio-emotional, and mental health aspects. Additionally, we complement our analysis by exploring differences in food security, social cohesion, and the economic status of parents. Although our analysis is descriptive, it represents a crucial initial step 2Venezuelan households are defined as those where both parents and their children have a Venezuelan nationality. Colombian households are composed of Colombian citizens only. 3 Usage context: background mention, primary mention, supporting mention.

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Input: (24 percent) with higher livestock ownership relative to other domains. Somalis are also more likely to work for private households, including household services, construction, and agricultural work. 0 10 20 30 40 50 60 70 80 90 100 Camp Hosts Camp Refugees Employed Unemployed, searching Unemployed, not searching Inactive not in school Inactive in school Percent Figure 3.2: Work status Source: World Bank Staff based on SESRE 2023. Table 3.1: Labor force statistics Camp- Hosts Camp- Refugees Labor force participation rate (strict) 52% 31% Unemployment rate (strict) 7% 21% Labor force participation rate (relaxed) 57% 43% Unemployment (relaxed) 15% 43% Employment-to-population ratio 48% 25% Source: World Bank Staff based on SESRE 2023. Note: Labor force participation ratio is the share of working-age people who are engaged in the labor market, either employed or unemployed. Unemployment is the share of people participating in the labor force who are not employed. The “relaxed” definition of labor force participation includes anyone who is available to work. The “strict” definition of labor force participation includes only those who are available to work and also actively searching for work. Employment-to- population ratio is the share of working-age people who are employed. 41 In Ethiopia, in-camp

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Input: The assumption of perfect implementation, however, is quite strong as interviewers have shown a preference for selecting respondents willing to participate in the survey (Alt, 1991), and a number of other studies found that data collected with random walk designs exhibit differences from known population statistics on gender, age, education, household size, and marital status (Bien et al. 1997, Hoffmeyer ‐ Zlotnick 2003, Blohm 2006, Eckman & Koch 2016). Probabilities of selection inherently cannot be calculated in a random walk sample design as no information is collected on how many structures are in the camp, or how likely it was that a given structure was the xth structure along any path. Random walk must then assume all structures have the same selection probability, implying constant sampling weights. Therefore, the only component of the weights for the random walk is the sub-sampling of households within a selected structure: 𝑤𝑤𝑖𝑖 ′ = 𝑁𝑁𝑗𝑗𝑗𝑗 𝑖𝑖. 2. 6. Comparison of Methods As mentioned above, stratified cluster samples with the canvassing of selected clusters is the most common sample design used to collect official socioeconomic statistics in the developing world, but in Usage context: supporting mention, primary mention, background mention.

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Input: Figure 1: Data and Descriptive Statistics: Clusters, Refugee Camps, and Conflicts Revised refugee diversity indices. We first use Afrobarometer data to construct standard indices of diversity, namely the EF and the EP indices (Bazzi et al., 2019; Esteban and Ray, 1994). The EF index describes the probability that two randomly selected individuals from a given location belong to two different ethnic groups (Alesina et al., 2003, 2016; Gomes, 2020b). The EF index can be defined as EFjt = Njt X e = 1 get (1 − get), (2) where Nj is the number of ethnic groups in cluster j at time t and get is the population share of 14 Usage context: supporting mention, primary mention, background mention.

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Input:
**Component 2 Update: Infrastructure Works**

Civil works under 12 of the 14 contracted sites are progressing on schedule. ESMF compliance audits conducted in March found that all sites met the LMP requirements for worker accommodation and wage payment, but two sites required corrective action on dust and noise management during construction. GIS-based photographic tracking of construction progress — using geotagged photos uploaded by site engineers — has been added to the activity monitoring dashboard, providing real-time visual verification of works completion to supplement the progress certificates issued by the supervising engineer.

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Input: of trade with government. Because the dataset used for this study is cross- sectional rather than longitudinal, I am unable to examine whether citizens adjust their beliefs and behavior to relative changes in service delivery. I was only able to test whether there are associations between the absolute service quality across neighborhoods, countries and ethnic groups and deference to the tax department, police and courts. Further, citizens may not be attributing goods and services to the gov- ernment. Rather, citizens may be attributing goods and services, such as roads, electricity grids, sewage systems, health care and education to vari- ous non-state actors including the following: the private sector; NGOs and community-based groups; churches, mosques and other religious institutions; traditional leaders; and, bilateral and multilateral donors. Survey questions on the Afrobarometer only indicate the presence or absence of services and infrastructure, and the quality of these services, but these questions do not probe respondents on who they believe are providing these services. Each of the indicators of perceptions of government performance is sig- niﬁcant at the p < 0. 05 level. Food security is positively associated with a willingness to defer to the tax department.

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

Ethnic Power Relations- Ethnicity of Refugees 2019

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Input: 12 One could think of Jordan ’ s growth of local supply of public basic and secondary schools as a progressive public investment in human capital that increases the human capital production for children of marginal parents in terms of income and educational attainment. Those are parents who would have chosen higher investment in the human capital of their offspring, but were constrained by the limited supply of schools in their subdistricts of residence and could not afford to send their children to more distant schools outside their jurisdiction or to provide them with homeschooling. However, the increase in public schools is expected to have less of an effect on richer or more educated parents, who are expected to provide education to their children regardless of the availability of schools in their subdistricts either by sending their children to distant schools or through homeschooling. On average, however, the increase in the local supply of public schools is expected to reduce the intergenerational correlation of educational attainment or enhance intergenerational educational mobility. III. DATA Two new and unique data sources are employed in the empirical analysis. First, the Jordan Labor Market Panel Survey of 2010, carried out by the Economic Research Forum in cooperation with the Jordanian Department of Statistics, is a rich source of information on all aspects of the Jordanian labor market (JLMPS 2010). Usage context: supporting mention, background mention, primary mention.

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Input: 16 { Tables 4 and 5 here} Among the first six categories that are based on raw census data, three categories (raw scaled, R & R not scaled, and R & R scaled) are constructed through the summation of bilateral raw numbers and disaggregations of some aggregate categories in the original censuses. Since these categories together constitute around 45 percent of migrants in each census round, the original bilateral portion of each cell was compared with the final number assigned to them after the various calculations as a check on accuracy. For each decade, therefore, the overall percentage contribution of the raw bilateral data to the total is calculated (table 6). 23 In each census round, at least 92 percent of all those categories are derived from the raw data. { Table 6 here} Simulating Missing Data Finally, to examine the reliability of the estimated missing census data and test the methodologies, several scenarios are assumed. All bilateral observations for a single year for four countries (Australia, United States, Switzerland, and Chile) in different parts of the world are deleted and the missing cells are filled using one of five methods. 24 The first simulation assumes that all bilateral data for 2000 are missing but that the total number of migrants is available. Usage context: supporting mention, primary mention, background mention.

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Input: 26 value of consumption flow of durable goods. 22 While monetary poverty can measure temporal resource holdings, multidimensional poverty, as a more comprehensive measure, includes chronic and exacerbating sources of poverty. This difference explains the existence of mismatches between individuals identified as monetary versus MPI poor, which are often more prominent in poorer countries (Evans et al 2020). This section examines these differences in the contexts of displacement. Table 9. Percentage of the sample in each poverty category: Rows sum to 100 % Non-poor by both measures Only Monetary Poor Only Multidimensional Poor Monetary and multidimensional poor Ethiopia 38 % 23 % 12 % 27 % N. E Nigeria 13 % 69 % 4 % 15 % Somalia 20 % 32 % 14 % 34 % Sudan 33 % 47 % 4 % 17 % Source: Authors ’ calculations based on data from the High Frequency Surveys of Ethiopia (2017), Nigeria (2018), Somalia (2017), South Sudan (2017) and Sudan (2017). This table presents the distribution of households in each of the categories in the columns. Thus, each row adds up to 100 %. South Sudan is excluded from this analysis as monetary data is not available for the country. Usage context: supporting mention, background mention, primary mention.

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Input:
assemble annual observations as follows for each grid square: the first 40 from the CRU

scores). We do this for both future periods, as well as for the historical CRU data (here

of rainfall and temperature for the past (from the benchmark CRU series that we have

table presents average R [2] scores for the bivariate relationships between the CRU

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Input: In settings with clearly distinguishable individual structures, these methods can also be reasonably accurate for the purposes of rapid estimation of displaced population (Checchi, et al. 2013). 101 The use of unmanned drones is also becoming more popular as the cost of this technology falls. This technique has been used by UNHCR to update its estimates of IDPs in Somalia ’ s Afgooye corridor (IDMC 2015) and by IOM to monitor disaster-induced displacement in Haiti, including the use of Unmanned Aerial Vehicles (UAVs) in collaboration with UNOSAT. (g) Open data initiatives. There are several initiatives to provide free and open data that enable Internet users to independently mine and analyze data and generate customized summaries, charts and visualizations. For example, the Bank has provided free, open access to its development data since the launch of its Open Data Initiative in 2010, however there is little open data on asylum-seekers, refugees and IDPs. JIPS has developed a web-based platform that allows users to explore, analyze and visualize profiling data online, and IDMC has 100 See http: / / www. flowminder. org /. 101 These methods are not effective in settings with connected structures, a complex pattern of roofs or multi-level buildings, as are prevalent in urban areas. Additionally, cloud cover and dense foliage can also obscure structures. Usage context: primary mention, background mention, supporting mention.

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Input: 13 Commission for Reception, Truth and Reconciliation (CAVR). 7 This information has been collected from deponents to the Commission ‘ s statement-taking process. 8 We make use of data on the number of killings that occurred during the war in order to derive patterns and variation of violence in Timor Leste over time and across space. We use this data to identify districts and years that experienced high and low violence-intensity, both at the start of the occupation and following the withdrawal of Indonesian troops in 1999. This allows us to estimate both the impact of the first years of the conflict and the impact of the last wave of violence in 1999. 4. 1. Identification strategy: The impact of violence on school attendance in 2001 We first investigate the short-term impact of the 1999 violence. The empirical questions being addressed are: (i) whether the violence in 1999 imperiled school attendance9 and school grade deficit, and (ii) whether different channels of exposure to conflict – displacement and house destruction – affected boys and girls and different age groups differently. 4. 1. 1. Primary school attendance and grade deficit rates in 2001 We make use of information in TLSS 2001 collected at the individual and household levels on displacement and house destruction to identify conflict-affected individuals. Usage context: supporting mention, background mention, primary mention.

data on the number of killings that occurred during the war

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Input: 9 3. 1 Data Sources We use three different types of data to verify our estimates and determine how sensitive they are to changes in definition and the year of the survey. Two sources are nationally representative, but date from 2001 or before, the third is data from a census of households carried out by the authors in 2003 as part of a project on educational choice. The first source is the “ long ” form of the population census in 1998, which is a large sample-based survey with information on enrollment. This survey is representative at the level of the district and region (rural or urban) and provides comprehensive coverage of the entire country. 7 We use this data to examine enrollment patterns across districts. The second type of data, based on household surveys, are different rounds of the Pakistan Integrated Household Survey (PIHS) carried out in 1991, 1998 and 2001. While the data is not as extensive as the census, it contains detailed household information on schooling and income, and has been used extensively by researchers both in Pakistan and the United States. Finally, we use the census of schooling choice among households that our research team conducted in August 2003 (referred to as the project on “ Learning and Educational Achievement in Punjab Schools ”, or LEAPS). Usage context: supporting mention, primary mention, background mention.

census of schooling choice among households

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Input:
**Appendix C: Robustness to DHS Cluster Geocoding Uncertainty**

The standard DHS jitter algorithm displaces cluster centroids by up to 5 km (urban) or 10 km (rural). To assess sensitivity of our results to this measurement error, we implement a simulation in which each DHS cluster centroid is displaced 1,000 times by a random draw from the DHS jitter distribution, and the treatment indicator is recomputed after each displacement. We report the median coefficient and the 5th and 95th percentile bounds across simulations. The simulated bounds are narrow relative to the estimated confidence intervals, indicating that DHS cluster geocoding uncertainty does not substantially bias our estimates.

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Input: 4 to 32 percent (see Table A1 in appendix). The total number of internally displaced people (IDP) outnumbers the stock of refugees in SSA and in the world but overall has followed a similar trend compared to the number of refugees (by country of origin). 1 Major civil wars in Central Africa mainly explained the peak in 1993 and 1994 and the increase at the end of the 1990s. Figure 1. Refugee population by origin, 1990 ‐ 2013 Note: Authors ’ aggregation based on UNHCR statistical population online dataset, accessed in September 2014. Data from 2007 to 2013 include people in refugee ‐ like situations. Persons in refugee ‐ like situations include “ groups of persons who are outside their country or territory of origin and who face protection risks similar to refugees but for whom refugee status has, for practical or other reasons, not been ascertained ” (UNHCR 2014: 39). Refugees in Africa seem to have mainly remained in Africa. Although SSA also hosts refugees from other regions, the closeness of the ‘ blue ’ and ‘ red ’ lines in Figure 2 ‐ representing the number of refugees originating from and hosted in SSA ‐ is an indication that most refugees cross borders within Africa. Usage context: primary mention, background mention, supporting mention.

UNHCR statistical population online dataset

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Input: 0 10 20 30 40 50 60 70 80 90 100 Percent Worse Same Better Figure 5.8: Perceived changes in household living standards Source: World Bank Staff based on SESRE 2023. Note: The survey asks how the household living standard has changed compared to last year and the last five years. a. Last 5 years b. Last 1 year Refugees’ Aspirations 48 scale44 gap between refugees and hosts is higher for in-camp refugees, the gap is relatively narrower for Addis Ababa refugees. The average food insecurity scale for in-camp refugees is “8” and for their hosts it is “4” out of 10; that is, in- camp refugee households experienced about eight food insecurity events while host households experienced about 4 in the past year. Consistent with other welfare indicators discussed, food insecurity tends to be more severe among in-camp refugees than their hosts or OCP refugees. In-camp refugees have less diverse diets and poor food consumption status compared to their hosts. The average household dietary diversity score—the number of food groups consumed out of twelve—is 7.5 for hosts and 6.5 for refugees (Figure 5.10a). Overall, the average dietary diversity score is also lower for in-camp refugees than their hosts. The

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Input: The model includes ϐixed effects for grade, school, and language spoken. 14 The results are presented in Table 3. We then narrow our focus to foreign students who joined Italian schools after February 2022, speciϐically comparing Ukrainian refugees to other newly arrived foreign students. This approach allows us to examine how Ukrainian refugees compare to other foreign students who entered the education system around the same time. By restricting the sample to these two categories of students, we estimate the following regression: 𝑌𝑌𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 = 𝛽𝛽0 𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑒𝑒𝑖𝑖 + 𝐸𝐸𝐸𝐸𝐸𝐸𝑆𝑆𝑖𝑖 + 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑟𝑟𝑖𝑖 + 𝑓𝑓𝑔𝑔 + 𝑓𝑓𝑠𝑠 + 𝑓𝑓𝑙𝑙 + 𝜖𝜖𝑖𝑖𝑖𝑖𝑖𝑖 (2), with variables as deϐined in (1), and results presented in Table 4. Our analysis also aims to explore potential mechanisms that could explain results derived from equations (1) and (2). Using the administrative data, we investigate whether being placed in a smaller class inϐluences school achievement in the sample of Ukrainian refugees. The results are presented in Table 5. We then draw on ϐindings from the survey data to unpack and analyze how Ukrainian refugees feel in Italy, the challenges they face, and their aspirations. 4. Results 4. 1. Integration challenges faced by Ukrainian refugees in Italy Low enrollment and substantial dropout rates At the end of the 2021-2022 school year, the enrollment rate of Ukrainian refugee children in Italian schools was low. In the months following Russia ’ s full-scale invasion of Ukraine in 2022, 3, 320 Ukrainian refugees were enrolled into Italian secondary schools. This ϐigure constitutes 24 % of the 14, 106 Ukrainian refugees aged between 11 and 18 years who sought temporary protection as of 14 This variable is included to account for the potentially greater ease of learning experienced by students who speak languages that are considered closer to Italian. Usage context: primary mention, supporting mention, background mention.

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Input:
approximated by wealth measured by the EMDHS asset index; and e)mothers' education. Note that the alternative

The asterisks indicate the significance level: *** p<0.01, ** p<0.05, * p<0.1. Standard errors in parentheses. Regressions take sample
design and household weights into account by using Stata's svy command. Data: EMDHS 2014.

2007 Census. The 2007 census has two formats - a long and a short format. The long format is richer in terms of

The Ethiopian census has both a short and a long form, and to increase model fit, the models use the long

observed in Ethiopia before, based on other data sets [30]. SAE results in addition to these variables are highly

EMDHS
EMDHS 2014
2007 Census
Ethiopian census

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Input: Typically, registers have evolved over time (from parish records, for example). They were never developed specifically to record international migration information, and they vary considerably across countries. For example, the laws under which individuals are classified as migrants and the conditions under which they are inscribed or deregistered differ greatly (Bilsborrow and others 1997). The Raw Data The Global Migration Database is a vast collection of destination country data sources detailing migrant stocks from numerous origin countries and regions (United Nations [2008]). Compiling and maintaining the underlying primary sources require herculean efforts to scour the key census collections of the world and enter the data manually. In total, the database comprises records from some 3, 500 separate censuses from more than 230 migrant destination countries and territories, by sex and age. Usage context: supporting mention, background mention, primary mention.

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Input: The LMP appended to the ESMF specifies that all contractors must submit workforce management plans prior to mobilization, detailing recruitment procedures, wage payment schedules, and the mechanism through which workers may raise concerns without fear of retaliation. Contractors employing more than fifty workers are required to establish a worker accommodation standard compliant with IFC Performance Standard 2. Compliance with the LMP will be verified through quarterly site inspections conducted jointly by the PIU's E&S officer and a representative of the national labor inspectorate.

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Input: Management Information System (EMIS) (UNHCR, 2020), and a separate chapter on refugee education is included in the annual education statistics report of the MoE. The GoE included expanding primary and secondary education for refugees in the national five-year Education Sector Development Programme VI (ESDP), covering 2020 to 2025, but little progress has been made. Box 2.1: Education system for refugees in Ethiopia 0 20 40 60 Percent 80 100 Hosts Refugees Hosts Refugees Hosts Refugees In camp Addis Ababa Total No education Incomplete primary Complete primary Complete secondary Complete post-secondary Figure 2.7: Education level (18 years and above) Source: World Bank Staff based on SESRE 2023. 0 20 40 60 80 100 Hosts Refugees Hosts Refugees Hosts Refugees In camp Addis Ababa Total No education Incomplete primary Complete primary Complete secondary Complete post-secondary Percent Figure 2.8: Youth (15 to 24) education level Source: World Bank Staff based on SESRE 2023. Sociodemographic Profile 14 OCP refugees attended education outside of Ethiopia and have relatively better educational attainment. One reason why OCP refugees have higher educational attainment compared to other refugees (especially other Eritreans) could be related to being relatively better off in their countries of origin (qualification for OCP requires having

SESRE 2023
Management Information System

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Input: the intensity of conflicts, and iv) population density in refugee host countries by region. Appendix B presents the list of variables along with description and summary statistics. 5. Empirical strategy To estimate the impact of refugee inflow19 on host community ’ s livelihood strategy choice, we use the following basic econometric model: 𝑌𝑌𝑖𝑖 = 𝛼𝛼 + 𝛽𝛽𝑅𝑅𝑅𝑅𝑖𝑖 + 𝛾𝛾𝑋𝑋𝑖𝑖 + 𝜈𝜈 + 𝜀𝜀𝑖𝑖 (1) Where, 𝑖𝑖 indexes a household, 𝑌𝑌𝑖𝑖 is an outcome variable of interest (livelihood diversification or commercialization of agriculture), 𝑅𝑅𝑅𝑅𝑖𝑖𝑖𝑖 is the measure of refugee inflow, i. e., the refugee population (average of 2017 and 2018) in the nearest refugee camp weighted by the inverse of distance of the household to the refugee camps, 𝑋𝑋𝑖𝑖 is a set of household controls, 𝜈𝜈 is kebele fixed effects, and 𝜀𝜀𝑖𝑖 is the error term. Several variables, from the DRDIP data set, were used as controls in our model.

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Input: Protection monitoring data from the last four cycles indicate that freedom of movement restrictions remain the most frequently reported protection incident, accounting for 34 percent of cases. The Protection Monitoring Tool was updated in cycle 5 to include an additional question distinguishing between formal government-imposed restrictions and informal social barriers to movement, following a recommendation from the protection analysis technical advisor. This change improved the actionability of protection monitoring findings for both advocacy and programmatic response teams.

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Input:
the World Bank's Poverty and Inequality Platform (PIP). PIP is managed jointly by the Data and

Research Groups in the World Bank's Development Economics Division. It reports both poverty

measures and inequality measures, including the Gini Index for 168 countries from 1968 to 2022. The

Gini index is based on primary household survey data obtained from government statistical agencies

alternative dataset that provides inequality measures. Specifically, we use the Standardized World

Income Inequality Database (SWIID). [5] The SWIID maximizes the comparability of available income

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Income Study database.

Data on natural disasters is from the EM-DAT database maintained by the Centre for Research

Poverty and Inequality Platform
Gini Index
Income Study database
EM-DAT database

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Input: Individual characteristics Age, sex, education, language skill, years in exile SESRE Household characteristics Gender of household head, household size, head education level, access to electricity, productive asset ownership, food insecurity experience SESRE Community characteristics Community economic development status Predominant land cover in the community SESRE Local Factors Remoteness Distance to towns and cities, distance to the nearest international border Ethiopian shapefile and Refugee geospatial from ESS Local labor market LFPR, unemployment rate, the share of wage employment, the share of employment by economic sector LMS, 2021 Market access Market accessibility index Ethiopia transport network layer, 2020 (ERA) & gridded population (GPWv4) Notes: For logistic regression, we assume local factors are exogenous in the model as refugees do not select their location. Since refugees’ residential location is not self-selected, they do not choose their respective camps to maximize their utility. Instead, they come across the border and are either assigned to camps close to where they crossed or a new camp is established. Our model compares refugee employment status by local factors in the hosting Zones and community: where subscripts denote : individual and : camp. refers to local factors; represents personal and presents household characteristics; refers to the characteristics of

Ethiopian shapefile
gridded population (GPWv4)

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Input: These may include skills on how to write a CV, prepare for job interviews, business and entrepreneurial skills to start a business, etc. In this regard, the mechanism for improving social cohesion values appears to have come from inter-community volunteering activities, rather than improvements in soft skills. (c) IMPACTS ON LABOR MARKET OUTCOMES While the NVSP was designed primarily to improve social cohesion values among participating Lebanese youth, it was also hoped that engaging them in volunteering activities, coupled with soft skills training, would enhance their employability and thus increase their chances of employment. At baseline, half of the selected and non-selected volunteers were active and searching for a job. Among them, 49 percent reported being unemployed, 31 percent wage employed, 13 percent employed in unpaid jobs, and 7 percent self-employed (see table 1). Those active volunteers were older in age than the rest of volunteers who reported being inactive in the study ’ s sample (with an average age of 21 and closer to labor market insertion). One year later, it appears that many of 19 Our interpretation that offered soft skills are likely too basic for this pool of volunteers is provided given the scale that we used in the questionnaire to test their knowledge on soft skills. We cannot rule out the possibility that had we used a different scale, we might have found an impact, either negative or positive. Usage context: supporting mention, primary mention, background mention.

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Input: 17 Revealingly, in Betts et al. ’ s (2013) survey of refugees in Uganda, 96 % of all interviewed households in the capital and 70 % outside the capital said they owned and used a mobile phone. They use this mobile phone to communicate with customers and suppliers, to get market information and to transfer money. Half of the urban refugees and 11 % of rural refugees also have access to the Internet. 4. Refugees As a Burden? As pointed in Section 2, most refugees in SSA are hosted in neighboring countries. Most of these hosting countries are likely among the least developed countries. It has been argued that these refugees may constitute an additional burden in terms of economic development in hosting countries (Mabiso et al. 2014). UNHCR (2014: 17) implicitly recognizes that potential burden by suggesting that the ratio of the size of the country ’ s hosted refugee population to its average income level can provide a proxy measure of the burden of hosting refugees. Usage context: supporting mention, background mention, primary mention.

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Input: area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location. Area stratifi- cation reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analyzed. ” Afrobarometer provides geocoded data for 6 rounds, which correspond to the 1991 – 2016 period, with the information on an individual ’ s ethnicity available from round 3 (corresponding to 2005 – 2006). We therefore restrict our analysis to the 2005 – 2016 period. The selection of countries is driven by data availability. Among the 33 countries with available Afrobarometer data, we exclude Botswana, Cape Verde, Lesotho, Madagascar, Mauritius, Sao Tome and Principe, South Africa, and Swaziland, for which no data is available on refugee camps or from the EPR-ER. We also exclude Sudan since the question on individual ethnicity is not asked in this country ’ s survey. Usage context: primary mention, supporting mention, background mention.

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Input:
decreased satisfaction. For example, using the German Socio-Economic Panel Survey (SOEP),

Two studies that use the German SOEP data (D'Ambrosio and Frick, 2007 and 2012) find that

using a set of European panel surveys concludes that absolute income is more important than

Current global counts rely on combining each country's total food balance with information on distribution patterns from household consumption expenditure surveys. Recent research has advocated for calculating hunger numbers directly from these same surveys.

details about how household surveys are designed and
how these data are then used. Using a survey experiment
in Tanzania, this study finds great fragility in hunger
counts stemming from alternative survey designs. As a
consequence, comparable and valid hunger numbers will
be lacking until more effort is made to either harmonize
survey designs or better understand the consequences of
survey design variation.

German Socio-Economic Panel Survey (SOEP)

household consumption expenditure surveys

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Input: Another way to view the connection between low return on education and youth frustrations is that the rapid intergenerational mobility in education has failed to yield similar mobility in either income or social status. This delinking between educational and occupational mobility has been documented for Egypt by Binzel and Carvalho (2013). While there is no similar work on Jordan, this article contributes to this agenda by documenting the first step in this process, which is the link between public investment in schooling and the educational mobility across generations. 1. This is based on version 2. 0 of the Barro-Lee dataset for educational attainment among the total population 15 and older. Usage context: supporting mention, background mention, primary mention.

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Input: In principle, individual registration of IDPs is not used to determine the ‘ status ’ of an IDP, since IDPs have the same rights and entitlements as other citizens and do not need to apply or be granted a special legal status. 66 Rather, registration of IDPs can provide a basis for: (a) establishing the number, location, and key demographic characteristics of displaced populations; (b) providing protection and assistance; (c) keeping track of family relationships; (d) preventing fraudulent access to scarce humanitarian assistance; (e) facilitating the issuance of temporary identity cards to replace lost personal documentation (Brookings 2008); and (f) providing social security benefits. 67 Full IDP registration by international organizations is not 62 By the end of 2014, individual refugee registration was the source of about 77 percent of the data on refugees; estimation accounted for 13 percent of data, combined estimation and registration for 5 percent and other sources for 5 percent (UNHCR 2016). 63 UNHCR may undertake registration activities when national governments do not have the capacity to do so. 64 Additional data can also be recorded such as education and occupation. 65 Insufficient budgetary resources, staff, training or materials. 66 Countries with national legislation that provides a legal status for IDPs are an exception to this international standard. 67 The scope of data collected depends on the objectives of the registration exercise, for example in Kenya, registration of individuals displaced by the 2007 and 2008 post-election violence excluded ‘ integrated ’ IDPs, i. e. those who had Usage context: supporting mention, primary mention, background mention.

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Input:
Nassar, R., J. Mastrogiacomo, W. Bateman-Hemphill et al. 2021. Advances in quantifying
power plant CO2 emissions with OCO-2. Remote Sensing of Environment. 264: 112579.

Nordhaus, W., A. Azam et al. 2006. The G-Econ Database on Gridded Output: Methods and
Data. Yale University.

Ye, X., T. Lauvaux, E. Kort, T. Oda, S. Feng, J. Lin, E. Yang and D. Wu. 2020. Constraining
fossil fuel CO2 emissions from urban area using OCO-2 observations of total column CO2. JGR
Atmospheres, 125(8).

<!-- PAGE 41 -->
**Appendix: Mobilizing OCO-2 Data for the Stakeholder Community**

In this paper, we have shown that a relatively simple tracking model can provide useful information
about changes in local CO2 concentration anomalies for areas of interest. However, we recognize that
most stakeholders do not have the requisite hardware and software for mobilizing the OCO-2 data
directly. Accordingly, the World Bank's Development Economics Vice Presidency (DEC) has
established an open web facility with the following features. We believe that it will contribute to the
global effort to reduce CO2 emissions.

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Input: 14 3. Refugees as Agents of Their Own Destiny 3. 1 The Composition of Africa ’ s Refugee Population and Its Consequences One of the first elements that catch the eye in Figure 6 is the difference in the composition of the refugee population in Africa compared to the rest of the world. The share of children and women among refugees is higher in Africa than elsewhere, in particular East and West Africa stand out here. This is, at least partly, a consequence of Africa ’ s younger, general population, but other forces could be at work as well, e. g. higher mortality of adult males in Africa or adult males staying behind or being separated from the rest of the household. It does mean however that, relative to other areas, more attention should be going to the needs and capacities of women and children in Africa. This means, for example, adaption of and increased supply of schooling and health services. Figure 6. The composition of refugees by age and gender, 2013 Source: Note: UNHCR statistics (UNHCR 2014). Asia excludes Australia, Japan and New Zealand. Americas exclude Canada and the United States. These percentages have been calculated by country when demographic data are available for at least 30 % of the total.

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Input: For a detailed definition see section 4 Household size Number of people included in the case records of each PA in Individual ProGress dataset Wage Income 1 if the household receives income from employment and / or daily or irregular work Income from remittances 1 if the household receives income from remittances Income per capita Raw sum of household income from all sources; work, pension, assets in Syria transfers, donations, other organizations'humanitarian aid, and other divided by household size Male Adults Number of males above 18 (inclusive) in the household Marital Status Categorical variable. The classification includes married PAs with spouse in the household, married PAs without spouse in the household, widowed, single or engaged, and divorced or separated. Proportion of female Number of female divided by the household size Location Categorical variable for 11 Governorates / cities. Ajloun City, Aqaba, Balqa, Irbid Jerash, Karak, Maan, Madaba, Mafraq, Tafilah, Zarqa. In Camp 1 if the household is located in a refugee camp Poverty before UNHCR and WFP assistance 1 if household expenditure before UNHCR plus WFP assistance is below the poverty line (JD50) Poverty before UNHCR assistance 1 if household expenditure after WFP assistance but before UNHCR assistanc is below the poverty line (JD50) Source: Authors ’ elaboration. Usage context: primary mention, background mention, supporting mention.

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Input:
**4.1 Identification Strategy**

Our identification relies on variation in distance from each DHS cluster to the nearest gold mine, interacted with an indicator for whether the mine was actively extracting gold in the year the DHS cluster was surveyed. The key assumption is that, conditional on district fixed effects, year fixed effects, and a set of community-level controls, mine-induced variation in local economic activity is uncorrelated with unobserved determinants of household welfare. We test this assumption by examining whether DHS cluster characteristics predict mine proximity after controlling for the fixed effects.

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Input: with Disabilities in Addis Ababa. Briefing Note. UNICEF. (2019). Birth Registration for Every Child by 2030: Are WE on Track? New York. UNICEF. (2021). Education in South Sudan. Briefing Note. Vemuru, V., Sarkar, A., and Woodhouse, A.F. (2020). Impact of Refugees on Hosting Communities in Ethiopia: A Social Analysis. World Bank Group. Verme, P., and Schuettler, K. (2021). The Impact of Forced Displacement on Host Communities: A Review of the Empirical Literature in Economics. Journal of Development Economics, 150, 102606. Walelign, S. Z., Wang Sonne, S. E., and Seshan, G. (2022). Livelihood Impacts of Refugees on Host Communities. Wieser, C., Dampha,N.K., Ambel, A.A., Tsegay, A.H., Mugera, H.K., Tanner, J. (2020). Monitoring COVID-19 Impact on Refugees in Ethiopia : Results from a High-Frequency Phone Survey of Refugees (English). Monitoring COVID-19 Impact on Refugees in Ethiopia Washington, D.C.: World Bank Group. Whitaker B.E. (2023). Border Proximity and Attitudes Toward Free Movement in Africa. The Afro Barometer Working Papers No. 200. Woldehanna, T., Hoddinott, J., and Dercon, S. (2008). Poverty and Inequality in Ethiopia:1995/96 – 2004/05. May. World Bank (2017). Forcibly Displaced: Toward a Development Approach Supporting Refugees, the Internally Displaced, and Their Hosts. Washington, D.C: World Bank. https://doi.org/10.1596/978-1-4648-0938-5. World Bank. (2019). Informing

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Input: Migration and Economic Mobility in Tanzania: Evidence from a Tracking Survey Kathleen Beegle The World Bank Joachim De Weerdt EDI, Tanzania Stefan Dercon Oxford University, UK We thank Karen Macours, David McKenzie, and seminar participants at the Massachusetts Avenue Development Seminar, Oxford University and the World Bank for very useful comments. All views are those of the authors and do not reflect the views of the World Bank or its member countries. Usage context: supporting mention, primary mention, background mention.

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Input:
Acknowledging the need for change, the South Sudanese Government signed the UNCRPD in February 2023. However,
substantial steps remain, including ratifying the optional protocol, establishing a national monitoring mechanism, and
effectively realising and implementing the principles of the UNCRPD.

Moreover, the African Union Policy Framework and the Plan of Action on Ageing has emphasised the need to recognize the
rights of older persons and to eliminate all forms of age discrimination to ensure that those rights are protected under
appropriate legislation. However, many African countries, including South Sudan still need to take up such initiatives to cater
for the protection of older persons.

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Input: The sample households are located within varying distance from the nearest refugee camp (approx. 67 to 76, 665 meters) (see Figure 3). 12DRDIP aims to improve access to basic social services, expand economic opportunities, and enhance environmental management for communities hosting refugees through providing funding for community driven projects. Usage context: supporting mention, primary mention, background mention.

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Input: REFodet = αod + γe + τt + β1Conflictot − 1 + β2Conflictet − 1 + β3Distanceed + ϵodet, (5) where REFodet is the stock of refugees of ethnic group e from country o in country d at year t. As we have data on yearly refugee stocks and would like to estimate the changes in these stocks over time using a gravity model, we include origin – destination fixed effects αod so that identification is based only on changes in stock over time (Zylkin, 2019). 20 We also include time τt and ethnic group fixed effects γe. Here we obtain data on the ethnicity of refugees from Murdock ’ s Atlas, which provides a map of ethnographic regions for Africa and the historical homelands of refugees (Murdock, 1967). To match ethnic groups across datasets, we again use LEDA21 to link data on ethnicity from Murdock ’ s Atlas with data on ethnicity from the EPR-ER dataset and, later, with data from Afrobarometer.

Afrobarometer
LEDA21
EPR-ER dataset
Murdock ’ s Atlas

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

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Input: 21 Table 6: Percentage of displaced individuals deprived in selected indicators by gender Ethiopia South Sudan Sudan Male Female Male Female Male Female Years of schooling 55 78 * * * 36 63 * * * 32 46 * * * School attendance 16 19 * * 21 29 23 23 Early marriage 3 13 * * * 8 75 * * * 6 50 * * * Unemployment 7 5 * * * 2 0 * 3 3 Legal id 45 46 48 74 * * * 10 10 Source: Authors ’ calculations based on data from the High Frequency Surveys of Ethiopia (2017), Nigeria (2018), Somalia (2017), South Sudan (2017) and Sudan (2017). Asterisks indicate statistical significance of mean differences between male and female at 1 % * * *, 5 % * * and 10 % * levels. Returning to patterns of household headship, Figure 5 breaks down the variation in censored headcount ratios among refugee households in Ethiopia, depending on the gender of the household head. Usage context: supporting mention, primary mention, background mention.

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

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Input: The ESMF screening form requires the subproject proposer to answer a series of yes/no questions covering potential impacts on biodiversity, cultural heritage, land acquisition, labor rights, community health, and flood risk. Responses trigger a risk classification that determines the level of environmental and social documentation required. ESMF screening is completed electronically through the MIS's subproject pipeline module, and all completed screening forms are reviewed by the PIU E&S officer within five working days of submission.

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

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Input: Protection monitoring in settlement areas revealed that the most common protection incidents relate to intra-community disputes over land boundaries and natural resource access, followed by documentation denial and cases of gender-based violence. Protection monitoring findings are disaggregated by sex, age, and legal status of the affected individual and shared with the national protection cluster monthly. Patterns emerging from three consecutive protection monitoring cycles are escalated to national authorities through formal dialogue letters drafted by the protection cluster coordinator.

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Input:
<!-- PAGE 5 -->
tracks ownership of state business entities with at least 10 percent stake in over 90 countries, including
Romania. The first part of the paper examines whether the degree of ownership and control levels of SOEs
matter for differences in performances-in terms of employment, average wages, assets per worker,
investment, and (labor) productivity-between SOEs and POEs over the 2011-2019 period.

**that justifies an SOE presence** . The taxonomy was developed by Dall'Olio et al. (2022b) in conjunction
with the BOS database. It classifies 4-digit NACE industries into three broad sectors (competitive, partially
contestable, and natural monopoly) based on the economic rationale-the intrinsic features and associated
market failures-that justifies SOE presence in an industry (see Table 2). Other NACE codes are excluded
from the sector classification of SOEs because firms in those industries provide public goods (e.g., public
administration and defense and activities of extraterritorial organizations). In contrast, others are
characterized by externalities (e.g., education and human health activities).

3.2 World Bank Global BOS Database
**The World Bank BOS database maps the footprint of the state within the corporate sector and across**
**economic activities based on a uniform definition** . The BOS dataset tracks all corporations where
national or subnational governments have an ownership stake of at least 10%, either directly or indirectly
(Dall'Olio et al. (2022a)). In this dataset, corporations are business entities that are (a) capable of generating
a profit or other financial gain for their owners, (b) recognized by law as legal entities separate from their
owners and with limited liability, and (c) set up for purposes of engaging in market production.

BOS database
World Bank BOS database
BOS dataset

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Input: GIS-enabled monitoring of road rehabilitation subprojects allowed the PIU to track physical progress at the segment level using georeferenced inspection records uploaded by field engineers. Each road segment was assigned a unique GIS identifier linked to the MIS contract record, allowing financial and physical progress to be reconciled in a single dashboard view. The GIS monitoring layer was shared with the national road authority and the Ministry of Public Works to support their own infrastructure maintenance planning.

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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, background mention, primary mention.

KAP (knowledge, attitudes and practices) survey

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Input: The MHPSS technical working group convened three times during the reporting period to review the integration of psychosocial support into primary health care delivery. Discussions focused on staff caseload thresholds, supervision ratios for community-based MHPSS workers, and referral criteria for cases requiring clinical psychiatric intervention. The working group endorsed revised MHPSS training modules and recommended that implementation partners adopt standardized intake forms to enable consistent tracking of service utilization across sites.

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Input: The information was provided to the family either by a resident of the village or from family members who remained in their village in Syria. As part of this survey, we also collected information on the vulnerability of the sur- veyed refugees using the subset of common questions from the VAF and VASyr surveys. Since the data for this survey was collected through a third party unaﬃliated with the UNHCR- and, thus, any decision to allocate assistance- we would expect answers on income, food security, and poverty coping strategies to be more truthful. These data provide important contextual information on the correlations between income, food security and employment status. Overall, our ability to put together a comprehensive data set with key dimensions 17 Usage context: supporting mention, background mention, primary mention.

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Input: There is one limit to our approximation in Equation 4. The ethnic composition of refugees in each year t for a given origin – destination pair of countries obtained from the EPR-ER database is assumed to be homogeneous across camps of the same origin – destination pair of countries for the refugees at year t. This may seem to be a strong assumption; however, the risk of misallocating refugees is reduced as the annual variation in the EPR-ER is generated by just a few dominant groups for a given origin – destination pair and the geographical distribution of refugees by country of origin is highly influenced by the proximity to their countries of origin. 16 As can be seen from panel A of Table B. 2, in refugee-hosting areas, on average, both EF and the EP seem to increase quite significantly when they are revised by incorporating the number of refugees in an 80-km buffer: the mean value of the standard EF index is 25. 58 %, while the mean value of the revised refugee EF index is 37. 90 %. The mean value of the standard EP index is 10. 11 %, while the mean value of the revised refugee EP index is 14. 07 %. Usage context: primary mention, supporting mention, background mention.

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Input:
set that satisfies this requirement is the World Value Survey (WVS) spanning the years from   1990 to 2011, that is, a period covering about 20 years.

in the WVS regarding immigrants are quite different from those of the ESS. Moreover, they are   not available for all years, so we end up with only two countries from the Europe area: Spain

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Input: These tariff rate modifications are essential for this analysis as suggested by the substantial differences between the tariff rates available in the GTAP 8 database, especially those implied for Jordan, Iraq, Lebanon, and Syria (Figure 1), and the updated tariff rates, presented by country, product, and source in Appendix Tables B1-B6. Since the GTAP tariffs attributed to Jordan, Iraq, Lebanon, and Syria are composite rates, they do not correspond to the actual trade profile of these countries. Therefore, the new tariff rates differ from the GTAP ones both because of differences in the tariff lines and trade composition. By contrast, the tariff information on Egypt and Turkey in the GTAP 8 database represents relatively accurately existing preferences (Figure 1). 3. Simulation design The pre-war efforts for deeper trade integration in the Levant are reflected in the pre-simulation analysis. Starting from the newly constructed database, the pre-simulation analysis implements the deep trade initiatives discussed by the Levant countries prior to the onset of the Syrian war in 2011. The context for these reforms and the shocks associated with each of these reforms are presented in section 3. 1.

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Input: In aggregate, we expect to observe a negative relationship between the percentage of the population that reports displacement, but at the individual level we expect that experience with hosting may, in certain circumstances, be positively associated with perceptions of social cohesion, regarding perceptions of relationships and solidarity. 4 Displacement and Social Cohesion: Survey Evidence To empirically evaluate the relationships between hosting displaced populations and social cohe- sion, this paper analyzes a series of surveys of civilian adults conducted in eastern DRC. 8 Each survey uses a multi-stage cluster sampling strategy capturing all territoires9 in North Kivu, South Kivu and Ituri provinces. The ﬁnal sampling units are randomly selected adults above the age of 18 to avoid bias toward men and / or heads of households. Multiple attempts are made over the course of one day to contact selected respondents and if necessary, appointments are made for in- terview. Surveys are enumerated by Congolese college students or professionals and interviews are conducted by members of the same gender and ethnicity as respondents to minimize enumerator- induced response bias. Further methodological details have been published (Vinck, Pham, Bindu, Bedford & Nilles 2019) elsewhere and additional details and sample size calculation are detailed in Appendix. Usage context: background mention, primary 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. Usage context: primary mention, supporting mention, background mention.

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Input:
They can be viewed and downloaded at [https://doi.org/10.48529/2ZH0-JF55](https://doi.org/10.48529/2ZH0-JF55) or, currently, [https://microdata.worldbank.org/index.php/catalog/4218.](https://microdata.worldbank.org/index.php/catalog/4218) The citation is Andr´ee (2021). 6There are also country-specific data gathered by FSNAU (Somalia) and CLiMIS (South Sudan). More recently, the International Food Policy Research Institute has piloted gathering high frequency prices in several countries. 7For instance, estimates have also been developed for Papua New Guinea in collaboration with IFPRI in a separate pilot project.

For example, maize, sorghum, millet, wheat, vegetable oil, to name a few common food items, are also tracked in the World Bank Commodities Price Data (The Pink Sheet) that is used to construct the World Bank Food Price Index used to track international food price developments.

Using detailed data on expenditures from a 2017/18 household budget survey and caloric information from the Brazilian Table of Food Composition, calorie intake is assigned to more than 1,400 items to estimate the cost per calorie for a representative group of the population.

World Bank Food Price Index
Brazilian Table of Food Composition

country-specific data gathered by FSNAU
household budget survey

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Input: 17 Figure 10: Children aged 7-12 attending school (%) Source: Listening to Displaced People Survey, 2014 and 2015. 5. Challenges Faced by Returnees The results suggest that returnees were less affected by the crisis than IDPs and refugees. This is reflected in data on asset and livestock ownership, but also in the information pertaining to exposure to violence. Returnees reported fewer victims; fewer returnees reported to have lost income as a consequence of the crisis; more of their children were able to continue schooling; and relative to IDPs and refugees, fewer perceived being poorer in June 2014 than before the crisis. Returnees are also the group that feels most secure, that has high levels of trust in the Malian army and police and that has a positive attitude towards most government policies. 88 88 97 79 76 78 99 88 92 55 74 72 91 98 92 96 100 85 90 91 96 90 86 87 87 95 89 76 75 90 94 92 97 86 73 98 Bamako Gao Timbuktu Kidal Niger Mauritania IDPs Returnees Refugees 14-Aug 14-Oct 14-Nov 14-Dec 15-Jan 15-Feb

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Input: An alternative version of the database that has been mapped to the United Nations (2006, 2009) Trends in International Migrant Stock database is available from the authors. These data are standardized over time in terms of the years to which they refer. { Table 3 here} Calculating Missing Gender Splits Although common in the underlying data, bilateral migration data disaggregated by gender are sparser than aggregate migrant totals (see table 1). An important contribution of the current work is in estimating the gender breakdown of all migrants in destination countries in the global migration matrices. Similar to the allocation from aggregated categories in the Global Migration Database to specific origins in the master list, two measures are used for calculating gender splits; they are described in appendix 5. Combining Migrant Definitions Only a single definition of a migrant (foreign born or foreign citizen) can be applied to each destination country in the final matrices. Switching definitions over time 17 The subregions used for the disaggregations are the 21 UN regions (see http: / / unstats. un. org / unsd / methods / m49 / m49regin. htm, with the countries of Oceania aggregated into a single subregion. They do not match the large World Bank regions used in the analysis in section IV. 18 While this propensity measure is clearly inappropriate, less than 1 percent of all migrants and observations are assigned on this basis. This method is included so that every migrant in the underlying data is accounted for.

Trends in International Migrant Stock
Global Migration Database

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Input: 80 100 Addis Hosts Male Addis Refugees Male Addis Hosts Female Addis Refugees Female Self-employed Employee Public NGO/RRS Private household Unpaid Percent Figure 3.23: Work type by gender Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 90 100 Addis Hosts Male Addis Refugees Male Addis Hosts Female Addis Refugees Female Elementary occupations Machine operators/assemblers Craf/related trade workers Skilled agricultural workers Service/sales workers Clerical support workers Tech/associate professionals Managers/professionals Percent Figure 3.24: Occupation Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 90 100 Addis Hosts Male Addis Refugees Male Addis Hosts Female Addis Refugees Female Elementary occupations Machine operators/assemblers Craf/related trade workers Skilled agricultural workers Service/sales workers Clerical support workers Tech/associate professionals Managers/professionals Percent Figure 3.25: Occupation among completed secondary or more Source: World Bank Staff based on SESRE 2023. Jobs and Livelihoods 37 These results indicate that the OCP model is not ideal for refugees’ labor market inclusion. Few refugees primarily enroll through an existing formal employer; thus, the OCP is mainly open to refugees with networks that can support them with remittances, and this makes these households less likely to work

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Input: Page 28 of 51 Figure 20: Part-time employment by age groups. (Early 2000s / Mid-2010s) Source: Own calculations based on Household surveys Figure 21: Temporary employment by age groups. (Early 2000s / Mid-2010s) Source: Own calculations based on Household surveys A less clear picture is observed in the case of temporary employment. Indeed, in the four countries where temporary employees are identified, we observe different dynamics in the age profile. On the one hand, Kyrgyzstan and Turkey do not evidence significant changes in the age profile of temporary workers in the last 10 / 15 years. On the other hand, Georgia and Armenia present changes in the age profile but in opposite directions. Armenia shows today a higher share of the older groups within temporary employees while Georgia evidences a younger profile of temporary workers. Finally, analyzing the composition of non-standard employment by gender, we have a heterogeneous picture by types of non-standard employment in the levels but with a similar trend (Figure 22 and 23).

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Input:
In 42 % of interviewed families, two children were attending school in displacement,
followed by families with three kids attending schools (35 %) and four kids attending school
(29 %). 16 % of families have one child at school, while in 10 % of families five children
attend the school in displacement.

Five families have one elderly in their families, and eight families have two. 11 families were
having at the time of interview a pregnant or lactating women present in their family.

Most of the interviewed IDPs currently live in Peshawar district (38 %), whole breakdown of
locations is provided below.

_Graph 1: Current location of IDPs originating from Shalozan Tangi_

**IV.** **Main findings of the Return Intention Survey**

**A.** **Displacement timing and trends**

Only two of the interviewed persons came from areas of origin in less than 18 months,
others were in displacement for a longer period. For most of the interviewed persons (62 %)
the **reason for displacement** was sectarian violence, followed by reason of military
operations (29 %) and lack of livelihood opportunities due to the conflict (3 %).

4

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Input:
**Coordination and advocacy.** In response to the significant conflict-driven internal
displacement that has occurred, UNHCR has begun scaling up protection coordination in
areas where new IDP responses are now underway. UNHCR and partners are also taking
pragmatic approaches to address the mixed nature of displacement flows, i.e. refugees
and IDPs. Protection Sector coordination platforms have been established in White Nile,
Kassala, Gedaref, Madani, and Wadi Halfa. Additionally, in areas where protection sector
coordination platforms were already present, outreach to protection partners planning to
initiate responses in new areas affected by conflict and displacement is underway. In
addition, since the outbreak of the conflict on 15 April, UNHCR-led Protection Sector has
issued nine flash updates titled ‘At a Glance: Protection Impacts of the Conflict’. These
weekly updates, primarily based on desk review of secondary data, highlight the severity
of the protection impacts experienced by the civilian population as a result of the conflict.
The specific protection concerns around the intensity of the violence and its intercommunal
dimension in Darfur were underscored in dedicated Darfur Protection of Civilians Advocacy
Notes. These have included two regional-level advocacy notes and one focused
specifically on West Darfur. Flash updates were also issued in relation to the attacks on
Kutum and Tawila in North Darfur. Finally, key advocacy messages related to urgent
protection of civilians’ priorities were drafted in preparation for the high-level pledging event
to support the humanitarian response in Sudan on 15 June, in collaboration with the Global
Protection Cluster.

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

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

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Input: Using Afrobarometer ’ s geocoded surveys, we focus on clusters as our unit of observation. 10 Our sample consists of 7, 547 such locations and 76, 518 individuals in 23 countries in Sub-Saharan Africa. “ The sampling universe normally includes all citizens age 18 and older. As a standard practice, they [we] exclude people living in institutionalized settings, such as students in dormitories, patients in hos- pitals, and persons in prisons or nursing homes. ” (Afrobarometer, https: / / afrobarometer. org / surveys − and − methods / sampling − principles) Since the sampling frame is based on recent censuses, with the aim of representing all citizens of voting age in a given country, the Afrobarometer samples are unlikely to include refugees. Note also that “ the sample design is a clustered, stratified, multi-stage, 8We explain the construction of theses indices in Section 4. 2. 9We test the robustness of our results with a smaller (40 km) and a larger (120 km) radius in Section 5. 3. This choice of buffer size assures us that between 75 percent and virtually all refugee camps fall within a cluster buffer. Other studies relying on Afrobarometer data construct buffers ranging from 25 km (e. g., Michaelopoulos and Papaioannou (2011), investigating ethnic-specific pre-colonial institutional structures) to 100 km (e. g., McGuirk and Burke (2020a), analyzing the impact of food-price shocks on conflict). 10Afrobarometer is a pan-African research network conducting public attitude surveys on democracy, governance, the economy, and society in African countries that are repeated on a regular basis (Afrobarometer, 2020). 10 Usage context: supporting mention, background mention, primary mention.

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Input: services or institutional support Lack of freedom or mobility Lack of community/family networks Insecurity or discrimination Figure D.16: Top 3 difficulties with being a refugee by survey domains Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 90 100 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Self-employed Employee Public NGO/RRS Private household Unpaid Percent Figure D.18: Type of work by survey domains Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 90 100 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Employed Unemployed, searching Unemployed, not searching Inactive not in school Inactive in school Percent Figure D.17: Work status by survey domains Source: World Bank Staff based on SESRE 2023. 0 20 40 60 80 100 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Elementary Occupations Machine Operators/Assemblers Craf/Related Trade Workers Skilled Agricultural Workers Service/Sales Workers Clerical Support Workers Tech/Associate Professionals Managers/Professionals Percent Figure D.19: Occupation by survey domains Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 90 100 Eritrean Somali South Sudanese Inside the camp Outside the

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

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Input: 14 3. ANALYSIS Has the increase in Syrian refugees impacted the welfare and socioeconomic conditions of the host community? Summary statistics in the previous section showed clear trends of increasing poverty among recent migrants throughout the country, both near the Syrian border and across rest of the country. While the poverty rates of recent migrant households spiked in 2013, poverty of host community households maintained a relatively constant level in the whole country. From these trends, it appears that there at least has not been an increasing trend in poverty among the host community over the latest years. The empirical model is shown in Equation 1. Regressions are estimated at the NUTS2-year level and using data from only the years 2011 and 2013. The dependent variable of interest is the host community poverty rate by region and year, where the poverty rate is based on spatially deflated imputed household income. Unlike the computation of the poverty rates, “ recent migrant ” information is not used for the analysis. Only the host community poverty rates are calculated using the LFS and the number of Syrians are taken from government sources.

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