Input: this way, profiling of IDP situations aims to underpin advocacy, protection and assistance activities as well as support the achievement of durable solutions by informing joint strategies between government, humanitarian and development actors. Profiling provides an overview of displacement-affected populations through the collection and analysis of minimum core data (number of IDPs, disaggregated by location, age and sex) and where possible additional quantitative and qualitative data (causes of displacement, patterns of displacement, protection concerns, humanitarian needs, vulnerabilities, and aspirations and prospects for durable solutions). Profiling may utilize data collection techniques at individual, household and community levels, often combining population estimation methods, a review of secondary data, focus group discussions, household surveys and key informant interviews targeted specifically at forcibly displaced populations (UNSD 2014). 70 Profiling methods focus on displacement situations, rather than only on displaced populations, and therefore includes comparisons to conditions in the host population. IDMC estimates that humanitarian profiling data forms the basis for 18 of their 60 country estimates and around 63 percent of their annual estimates (IDMC 2015), with the largest volume of data on conflict-induced internal displacement provided by OCHA followed by IOM. There are several practical challenges associated with IDP profiling exercises in displacement situations. Insecurity or terrain may impede access to displaced populations in conflict-affected or hard to reach areas.

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Input: The other source of micro data for Jordan during the pandemic is the COVID-19 MENA Monitor (CMM) data (OAMDI, 2021). This data was collected over three waves in February, June and August 2021 through a phone survey. It also has retrospective data on individuals ’ employment 6 Defence order number 6 stipulated, early April, that institutions subject to the labor law must allow their employees who were dismissed or whose services were terminated since the beginning of the pandemic to return to their work < https: / / www. jordantimes. com / news / local / pm-issues-defence-order-no-6-stipulating-labour-rights- under-defence-law >. 7 Additional data was collected between February and March 2021 from refugee camps. Usage context: background mention, supporting mention, primary mention.

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Input:
<!-- PAGE 10 --> ##### **3 District Expenditure Data** The financial data used are the District budget data for the years from 2001 to 2012 (Fiscal  Year of January-December every year).

They were derived from the Regional Financial In formation System (Sistem Informasi Keuangan Daerah, SIKD) of the Ministry of Finance.  The district expenditures are available for 12 different sectors/functions (such as agriculture,  health, education, etc.) and for four economic classifications (personnel, goods and services,  capital, and other).

- floods, earthquakes, volcanic eruptions and the 2004 tsunami - that are combined with  nightlight data - used as a proxy for economic activity - to construct an index that estimates  the impact on districts and provinces.  More specifically, the nightlight data used provide a normalized annual light value ranging  from 0 (no light) to 63 (maximum light) and are from the Defense Meteorological Satellite  Program (DMSP) satellites.

Raschky (2014) and Michalopoulos & Papaioannou (2014). In our case, the nightlight data  have been employed as a weight for the economic impact of disasters.  Floods are modeled through a combination of remote sensing images and GIS-modeling  using the Geospatial Stream Flow Model (GeoSFM).

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Input: recently introduced the first version of their Global Internal Displacement Database (GIDD) that allows users to explore, filter and sort IDMC ’ s data to produce graphs and tables, and export underlying data. 102 Such platforms need to incorporate safeguards to protect the privacy and confidentiality of individuals ’ data. UNHCR and Statistics Norway are currently leading an initiative to improve forced displacement statistics with the participation of national statistical agencies. This process began with the presentation of the “ Report on Statistics on Refugees and IDPs ” at the 46th session of the UN Statistical Commission in March 2015, 103 followed by an international conference in Turkey in October 2015. 104 The conference set in motion a process for national statistical agencies to collaborate to develop a set of recommendations that both countries and international organizations can use to improve data collection, reporting, data disaggregation, and overall quality, including the preparation of International Recommendations for Refugee Statistics (IRRS). Progress on this agenda was discussed at the 47th session of UNSD held in New York in March 2016, where it was recommended that the expert group should also include IDPs in its scope of work (UNSD 2016). 105 The current initiative is focused on refugees, asylum-seekers and IDPs but would ideally be extended to host communities and returnees.

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Input:
Comparing our results with the World Bank poverty lines used for global poverty monitoring, by
expressing them in 2011 purchasing power parities (PPP), we find that the total poverty line of R$455 is
equivalent to approximately US$6.10 a day, and hence in the range of upper-middle income countries. [17]
Moreover, it is very much in line with the societal poverty line one would obtain for Brazil using POF
2017/18 data. [18] The food poverty line of monthly R$258 is equivalent to a daily US$3.46 in 2011 PPP,
above the international poverty line of US$1.90 per person per day.

In Brazil, poverty monitoring is not based on POF. Instead, another survey - the Pesquisa Nacional por Amostra de Domicílios Contínua (PNADC), which collects information on income instead of consumption - is used.

Developing approaches to use the poverty line estimated here for regular poverty monitoring with the income aggregate based on PNADC is beyond the scope of this paper; however, related work has shown that very

18 The societal poverty line defines someone as suffering from societal poverty if they live on less than $1 plus half of what the median person in their country consumes (see Jolliffe and Prydz, 2017). With median consumption per capita per person per day from POF 2017/18 expressed in 2011 PPP US$ being 10.18, the societal poverty line would be US$6.09 in 2011 PPP per person per day for Brazil.

Pesquisa Nacional por Amostra de Domicílios Contínua (PNADC)

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

Database of the Global Administrative Areas

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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 %.

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Input: Gender Perceptions- Violence (IPV) The standardized total score of ﬁve questions regarding norms for inti- mate partner violence (IPV) from the Demographic and Health Survey (DHS) (The important decisions in the family should be made only by the men of the family. How often would you agree? The wife has the right to express her opinion even when she disagrees with what her husband is saying. How often would you agree? A wife should tolerate being beaten by her husband in order to keep the family together. How often would you agree? A husband has the right to beat his wife. How often would you agree? It is more important to send a son to school than it is to send a daughter. How often would you agree?). Financial Well-being Savings Response to the question “ How much money do you currently have in savings? ” During the collection surveys (midlines) this question instead asked “ How much money did you save in the past week? ” Borrowing Total amount of money the household has borrowed. Economic Decision Making Risk Preference Measured using incentivized responses to the multiple price list deci- sions adapted from Holt-Laury and Sprenger (2002).

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

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

Trends in International Migrant Stock
Global Migration Database

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Input: Quality Metrics A standard Measure in the assessment of a sampling designs is the Root Mean Squared Error (RMSE) and calculated as: 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅 = ∑ 𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑠𝑠𝑠𝑠𝑠𝑠 1000 𝑠𝑠𝑠𝑠𝑠𝑠 = 1 1000 = ൥ 1 1000 × ඥ (𝑌𝑌 ෠ − 𝑌𝑌) 2 𝑌𝑌 ൩ × 100 Expressed here as percentage deviation from the population mean Y and calculated for each parameter of interest. Equation.. is only the empirical representation though and a result of rearranging the definition of the Mean squared Error, 𝑀𝑀𝑀𝑀𝑀𝑀൫𝑌𝑌 ෠ ൯ = 𝐸𝐸൫𝑌𝑌 ෠ − 𝑌𝑌൯ 2 = 𝐸𝐸 ൣ ൫𝑌𝑌 ෠ − 𝑌𝑌෨൯ + ൫𝑌𝑌෨ − 𝑌𝑌൯൧ 2 = 𝐸𝐸 (𝑌𝑌 ෠ − 𝑌𝑌෨) 2 + 2𝐸𝐸൫𝑌𝑌 ෠ − 𝑌𝑌෨൯൫𝑌𝑌෨ − 𝑌𝑌൯ + ൫𝑌𝑌෨ − 𝑌𝑌൯ 2 And decomposing it into 𝑀𝑀𝑀𝑀𝑀𝑀൫𝑌𝑌 ෠ ൯ = 𝑉𝑉𝑉𝑉𝑉𝑉൫𝑌𝑌 ෠ ൯ + 𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 (𝑌𝑌 ෠) with 𝑌𝑌 ෠, 𝑌𝑌෨ and 𝑌𝑌 being the estimate from the sample, the mean of this estimate and the true value in the population respectively. Var is the corresponding variance, and Bias the resulting bias component, which is defined as: 𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 ൫𝑌𝑌෨൯ = 𝑌𝑌෨ − 𝑌𝑌 Usage context: background mention, primary mention, supporting mention.

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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

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Input: We have constructed two different variables that try to account for the degree of severity of the conflict. 10 The first variable identifies individuals belonging to households that were displaced due to the 1999 wave of violence (all members displaced). The second variable identifies individuals in households that report having their house completely destroyed by the violent attacks in 1999. The TLSS 2001 contains also useful retrospective information on school attendance and grade attained across three different academic years: 1998 / 99, 1999 / 00 and 2000 / 01. We are 7 Commission for Reception, Truth and Reconciliation & Benetech Human Rights Data Analysis Group. ― Human Rights Violations Database. ‖ 9 February, 2006. Website: http: / / www. hrdag. org / resources / timor-leste_data. shtml. 8 There may be potential sample biases in the statement taking procedure given the voluntary nature of the process. It is possible that those living in more remote or mountainous areas, those living far away from the areas where the statements were taken, the sick, old and disabled and those with no access to the media or means of mass communication have a lower probability of being part of the sample. By contrast, those more active in local communities are more likely to have provided a testimony. Usage context: supporting mention, background mention, primary mention.

Human Rights Violations Database
TLSS 2001

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Input: and purchase goods at better prices. In Ethiopia, refugees’ locations differ vastly in terms of proximity to resource and economic hubs. About 37 percent of refugees live within 10 kilometers of the nearest Woreda city and another 43 percent live within 10 to 20 kilometers. Zone capital cities are farther away, but almost half (45 percent) of in-camp refugees live within 20 kilometers of the nearest Zone capital city (Figure 6.1a). Borders seem farther, with 18 percent of refugees living within 30 46 Labor Force and Migration Survey 2021. Markets and Opportunities 58 kilometers of the nearest border. When defining mutually exclusive location categories to measure proximity to resource hubs, we see that 44 percent of refugees live closest to the nearest Zone capital city. Another 28 percent live closest to a Woreda City, which is not a Zone capital city. About 11 percent live close to a border but not the Zone capital or Woreda city, and 17 percent of in-camp refugees live in remote areas far from a Zone capital city, Woreda city, or a border. When looking at accessibility, as defined by a market accessibility index, more than one-third of the refugees are located in areas with

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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 10099 Situations of forced displacement create unique challenges for social cohesion because of the major disruption of social dynamics among both displaced persons and host communities. This paper uses a sequential mixed method approach to analyze the relationship between hosting displaced persons and perceptions of social cohesion in eastern Democratic Republic of Congo. First, participatory research methods in focus groups empowered participants to pro-duce a locally driven definition of social cohesion. The results from these exercises inform the quantitative assessment by dictating measurement strategies when analyzing original surveys.

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

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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:
-- PAGE 12 --> For the decomposition analysis of emissions intensity, we obtain annual country-level total passenger and freight transport traveled by road and rail from the World Road Statistics and the International Transport Forum databases.

The level of urbanization, and the value added from agriculture, manufacturing, and service sectors are all obtained from the World Bank World Development Indicators database.

Data on country-level BRT systems are obtained from global BRT database.

Diesel and gasoline prices are compiled from fuel price documentation from the Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH (GIZ).

Farm data were collected by conducting a face-to-face survey among a

World Bank World Development Indicators database

fuel price documentation from the Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH

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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: than 500, 000 refugees, together accounting for half of all refugees and people in refugee-like situations (excluding Palestine refugees). Major refugee hosting countries are typically the neighbors of countries of origin. For example, Syria ’ s neighbors (Turkey, Lebanon, and Jordan) together accounted for 27 percent of total refugee numbers; Afghanistan ’ s neighbors (Pakistan and the Islamic Republic of Iran) together accounted for 16 percent; and Somalia ’ s and South Sudan ’ s neighbors (Ethiopia, Kenya and Uganda) together accounted for 11 percent. Some countries (Lebanon, Jordan and Turkey) are hosting a particularly large share of refugees relative to their population (see Figure 10). 45 However, in all other countries, the number of refugees as a percentage of the population is 3 percent or lower, and most often below 1 percent. Figure 7: Top 15 Host Countries as a Share of Total Refugees and Asylum-Seekers 1991 – 2015 Source: UNHCR Statistical Online Population Database Note: Includes refugees, people in refugee-like situations and asylum-seekers. Excludes Palestinian refugees under UNRWA ’ s mandate. 45 Nauru is a special case since the Australian government funds the offshore processing center where refugees and asylum-seekers intercepted at sea are detained pending determination of their status.

UNHCR Statistical Online Population Database

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

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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: Having returned (early) to Northern Mali did not always lead to a stable condition either: the transition probabilities from returnee to IDP or to refugee are 1. 1 % and 0. 2 % respectively. As we can see from Figure 1, the majority of the sample is Songhai and Kel Tamasheq (almost everybody identified themselves as Muslim). There are clear differences in migration decisions between ethnic groups. The reaction of most of Arab and Kel Tamasheq origin was to leave the country, while most Songhai people preferred to go south, to Bamako, or, by the time of our survey, had already returned to Northern Mali. In fact, as pointed out in (Etang-Ndip et al., 2015), IDPs and returnees have a similar ethnic composition because 94 % of returnees in our sample were IDPs. Far fewer returnees in the sampled cities of Gao, Tombouctou and Kidal returned from refugee camps in the neighboring countries for the simple reason that most refugees used to live in towns and villages outside the regional capitals of Northern Mali. Displaced Refugee Returnee Total Tamasheq Arab Songhai Peulh Bella Other Analytic weights used Source: LDPS 2014-15 Figure 1: Ethnic composition

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Input: Notably, while we cannot rule out that time outside due to employment may play a role (e. g., fresh air may boost one ’ s mood), our time-use data indicates that the average refugee already spends at least three hours outside per day, with no measurable diﬀerence between employed and cash arms. As we are powered to detect changes of at least twenty minutes for each activity, our results suggest that large substitutions away from unsavory activities are unlikely to be driving the improvements in psychosocial well-being, insofar as the respondent recalls. 1718 We also investigate whether those who were more idle prior to being employed beneﬁt more from employment. We ﬁnd no impact along this margin, suggesting that the elimination of boredom per se is not the driving force behind the psychosocial value of employment (Appendix Table A10). 17Most respondents do not track their day by time, making collection of reliable time use data challenging (though recent literature documents the broader unreliability of such data). We piloted a variety of strategies, and settled on asking respondents how much time they spent on a set of activities in the previous day. Usage context: primary mention, background mention, supporting mention.

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Input: The report focuses on intent-to-treat (ITT) estimates, measuring the impact of offering volunteering opportunities and soft skills training independently of actual take-up. 9 We estimate the following individual-level intent-to-treat regression: 𝑌 ௜ ௧ ൌ 𝛼 + 𝜇 ௡ ൅ 𝛽𝑇௧ + 𝛾𝐷 ௜ + 𝛿ሺ𝑇 ∗ 𝐷ሻ ௜ ௧ + 𝜀 ௜ ௧ (1) where 𝑌 ௜ ௧ is the outcome of interest for respondent i in period t, 𝑇௧ is a post-treatment year binary variable, 𝐷 ௜ is a binary variable for being assigned to the treatment, and 𝜇 ௡ is a fixed effect for NGOs. 𝛼 represents the baseline average for the outcome of interest for non-selected youth. 𝛽 is the difference in after-and- before intervention in outcomes for non-selected youth. 𝛽 ൅ 𝛿 is the difference in after-and- before intervention in outcomes for selected youth. 𝛾 is the difference in 9 Due to some procurement delays that caused a big time-lag between baseline data collection and actual NGO project implementation, many of the volunteers who belonged to selected NGOs and who were randomly selected to participate in the impact evaluation study dropped out after their baseline data were collected and were replaced by other volunteers. Project monitoring data reveal that 23 percent of volunteers assigned to treatment did not actually end up participating in the NVSP. Given the relatively high number of non-compliance, we are unable to perform Local Average Treatment Effects (LATE) analyses to understand the impact of participating in NVSP on outcomes of interest.

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

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

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

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Input: Eritrean refugees26 and 41 percent of Somali refugees have better usage of out-of-camp healthcare services compared to South Sudanese (5 percent). Overall, in- camp refugees with chronic27 illnesses tend to receive treatment in health institutions located outside of camps compared to those with non-chronic diseases (Figure 2.17b). Refugees receive follow-up treatment for tuberculosis and antiretroviral therapy (ART) for HIV/AIDS in camp health facilities and also get treatment for common illnesses such as asthma, diabetes, hypertension, epilepsy, and mental issues. OCP refugees spend more on health compared to hosts. OCP refugees can no longer rely on international aid sources for healthcare, and do not have health insurance. However, OCP refugees who get out-of-camp residency permits due to health problems receive medical services free of charge under the urban assistance program. UNHCR is working with the GoE tow include OCP refugees in the Community Based Health Insurance (CBHI) Scheme. Of the total refugee households living under OCP, 10 percent moved to Addis Ababa to access basic social services, such as education and health. Thus, some refugees from the above may receive medical services free of charge. Based on SESRE data, most OCP refugees (58 percent) rely primarily on private healthcare services, while

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Input: due to armed conﬂict but for more idiosyncratic reasons. We check robustness of this approach in two ways: (i) using all of the refugee stock observations available in the data set, and (ii) computing refugee ﬂows as the positive time diﬀerences in refugee stocks from year to year (setting negative time diﬀerences to zero). The results are robust to these two alternatives. 5 10 15 20 Number of refugees (million) 1987 1992 1997 2002 2007 2012 2017 Year Figure 1: Global refugee population, 1987-2017 Note: This ﬁgure plots the global stock of refugees. The data on bilateral distance and contiguity come from CEPII. The distance vari- able refers to the great circle distance between the most populated cities of each country in the pair. The contiguity indicator is equal to one if the two countries share a land border. Figure 1 charts the global refugee population over time. The sharp increase in the number of refugees over the past decade is evident. Such refugee movements can have signiﬁcant impacts on the destination countries. Usage context: primary mention, supporting mention, background mention.

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Input: Following the approach used for the Global Costing of Refugee Inclusion, successful inclusion is defined as earning sufficient income to be no longer poor and to consume more than the (international) poverty line. This definition opens two tracks for investigation: first, how much aid would be needed if the policy objective were to bring refugee consumption up to the poverty line. The answer to this question is found by identifying the poverty gap for refugees. This opens the second track which explores the factors that determine, or at least that are associated with, the size of the poverty gap. The note is organized as follows. The next section discusses data and presents some key descriptive statistics on refugees and host communities in Uganda. This is followed by a methodological section discussing how own income and aid are complements and how an analysis of poverty gaps informs about the need for assistance. This is followed by two analytical sections. The first identifies refugee poverty gaps, and assistance needs for refugees with distinct characteristics. The following section estimates how much has been saved by including refugees in the economy and explores how more could be saved. Conclusions follow. 2 The poverty numbers in World Bank (2019) are based on the official poverty line adopted in Uganda in 1997. There was a need to update this line as it was too old and producing a very low poverty rate. For example, using this line produced a national poverty rate of about 21 percent in 2019 / 20 compared to more the than 40 percent international poverty rate using the USD 2. 15 2017 PPP daily poverty line. In order to address this criticism, the poverty line was revised by the Uganda Bureau of Statistics in 2021, but it is not available for the 2018 Refugee and Host Communities Household Survey used in this note. Instead, we are using the international poverty line throughout. Usage context: supporting mention, primary mention, background mention.

2018 Refugee and Host Communities Household Survey

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Input: This distinction is also applied to foreign students, with those entering the system after February 2022 referred to as “ Migrant post-Feb 2022 ” and others referred as “ Migrant pre-Feb 2022 ”. 7 Administrative data from MoE. The Ministry data includes information for all students who enrolled at any point during the academic year. 8 This information covers academic year, grade, gender, birth date, birthplace, citizenship. They also include school-speciϐic information such as the name and identifying code of the institution where the student is enrolled. Furthermore, the dataset includes a variety of school outcome variables, including grades in English, Italian, Mathematics, overall GPA calculated as the average across all subjects, behavior scores from grade 9 to grade 12, guidance council evaluations from lower secondary school, records of absences, late entries, and early exits. Given the timing of this study, data for academic year 2022-23 are the most complete. For academic year 2022-2023, school enrollment data at the provincial level was provided for 4, 269, 348 enrolled students across the 8 years of Italian lower and upper secondary school, encompassing both public and private institutions. The dataset includes nearly all students in the country irrespective of their citizenship. 9 Table 1 shows the distribution of the different groups of students by grade. In the 7 For ease of reference, we refer to non-Italian and non-Ukrainian students as migrants. However, we acknowledge that some of these students may be refugees or displaced students. 8 At the time of writing this paper, both MoE and INVALSI data were not fully available and, as such, only the information on enrollment was used for the academic year 2023-24. 9These numbers do not include students enrolled in Provincial centers for adult education (CPIA). See footnote 5. Usage context: primary mention, background mention, supporting mention.

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

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Input: 21 Distance from Rebel Group Headquarters We coded the location of the headquarters of the rebel groups participating in the conflicts under study, and calculated the distance from each square to the most proximate rebel group headquarters (we do not know a priori which rebel group or government that will act in a particular square). As the `distance from capital'variable, it was coded as the distance in terms of squares and log-transformed. Border Square We coded squares as border squares if a national border runs through it. Such squares belong to more than one country and are not straightforward to code. We coded national- level information for border squares according to the following rule: A border square was considered to belong to the country that was most frequent among the eight neighboring squares. In tie cases, we assigned nationality randomly between the tied countries. Interaction country-square population This variable was created to test the population settlement pattern hypothesis. It is an interaction between population count at a location (square) as a portion of the country's total population. Road type Road type is a variable by ESRI that is available in the Digitial Chart of the World Data. It is a high resolution dataset at 1: 1, 000, 000 scale and consists of arcs which indicate road mass.

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Input: The MIS platform was procured through a competitive process and is hosted on servers maintained by the Ministry of Finance's Information Technology Department. The MIS uses role-based access control, with read-only access granted to Bank task team members to facilitate real-time supervision. Data backup procedures run automatically every four hours, and full system backups are stored off-site in compliance with government data security regulations. User access logs are retained for three years and are available for review during audit exercises.

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Input:
race or ethnic group as the majority (ESS). _Education_ is the average number of years of full-time education completed (ESS).   _Age_ is the median age of all respondents (ESS). All summary statistics use design and population size weights.

The estimates are small area estimations
based on the 2014 Demographic and Health Survey and

the latest population census. It is shown that small area
estimations are powerful predictors of undernutrition, even
controlling for household characteristics, such as wealth and
education, and hence a valuable targeting metric.

**Keywords:** Child malnutrition, Small Area Estimation, Demographic and Health Survey, Targeting, Ethiopia

2014 Demographic and Health Survey
Demographic and Health Survey

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Input: itative exercise empowered focus group participants to guide the research and conceptualization. The results from these exercises then dictating the deﬁnition and measurement strategy for social cohesion in the quantitative assessment. The participatory research strategy was based mainly on structured focus group discussions. The project conducted consultations in seven territoires with the objective to develop localized understandings of what elements were important to social cohesion in eastern DRC. Participants were selected from civil society and the public sector. 96 individuals participated in these exercises (Table 1), 55 % of whom were men and 45 % of whom were women. 6 Location (Groupement) Date Number Participants Goma City 06 Oct 2017 11 Bukavu City 13 Oct 2017 13 Nyabibwe (Kalehe) 12 Oct 2017 14 Ishungu & Lughendo (Kabare) 12 Oct 2017 15 Kamisimbi (Walungu) 16 Oct 2017 18 Wassa (Walikale) 20 Oct 2017 12 Biiri (Masisi) 03 Nov 2017 13 Table 1: Descriptive Information on Focus Groups The focus group discussions began with an open discussion on social cohesion designed to ascertain participants familiarity with the concept. The facilitator further asked participants to write down words or concepts participants related to social cohesion. These words were written on individual post-its, which were then posted on a wall. Usage context: primary mention, supporting mention, background mention.

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Input: In principle, the positive attitudes among many hosts towards refugees, the high degree of cultural similarity between groups, and the willingness of refugees to be engaged in their community are all promising signs for social integration. Yet, even in the Somali domain, where cultural similarity and host attitudes are greatest, more than two-thirds of refugees do not have an Ethiopian friend, and more than half do not find social interactions with hosts easy. Better employment outcomes for refugees with Ethiopian friends indicate the benefits of facilitating social integration for refugee livelihoods and economic integration. 0 5 10 15 20 25 30 Age Under 30 Age 30-44 Age 45-64 Age Over 64 Female Male Discrimination/harassment in past year Victim of crime in past 2 weeks Figure 7.20: Discrimination and harassment by demographic group Source: World Bank Staff based on SESRE 2023. 0 5 10 15 20 25 30 35 Eritrean Somali South Sudanese Addis Ababa All Refugees Discrimination/harassment in past year Victim of crime in past 2 weeks Figure 7.19: Discrimination and harassment Source: World Bank Staff based on SESRE 2023. 72 A ddressing the challenges refugees face in Ethiopia requires a concerted effort to promote their self-reliance, economic integration, and

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Input: Between outreach and baseline, one full survey round was collected due to potential survey fatigue and on the understanding that nothing of importance would likely change in such a short period. Basic demographic information, such as age, gender, marital status and employment status were collected at outreach. At baseline, additional indicators were collected, relating to the behavior, attitudes, opinions and personalities of the participants. The only exception to this is data on optimism, which were collected at both outreach and endline. This allowed us to test whether or not the intake decision had effects, even before the training began. Endline data were collected between July 2018 and November 2019 and repeated the combined outreach and baseline surveys and experiments. Variables: We collected a range of survey and experimental indicators in order to assess our key research questions and associated hypotheses: 6 Economic and life optimism: We collected two survey questions about optimism at outreach, baseline and endline. These questions ask individuals to rank their expectation that their life and economic situation will be better in one year than it is now. Answers are 4 In addition, data were collected from Palestinian Refugees in Lebanon (PRL). Usage context: primary mention, background mention, supporting mention.

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

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Input: impression of the state ’ s role in development and give credit to the state for helping to leverage external resources. Citizens are also likely to give the state credit where mechanisms to voice complaints about non-state actors exist and where bureaucrats are able to eﬀectively respond to complaints. Under these conditions, non-state service provision is likely to strengthen the ﬁscal contract. 5 Data and Methods I explore the relationship between external service provision and deference to government using Afrobarometer survey data from 19 Sub-Saharan African countries (see Table 1). Africa is an especially good place to examine these issues because of the large amount of variation both within and across African countries in the extent to which non-state actors, donors and other states are active in service provision and the extent to which governments are relatively eﬀective and fair. Government responsiveness, corruption and reliance on non-public resources vary considerably among localities with consequences for citizen understanding of and relationship to government (Gibson and Hoﬀman, 2005). This project relies on the fourth round of Afrobarometer data that surveys Africans ’ views towards democracy, economics, and civil society with random, stratiﬁed, nationally representative samples.

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

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Input: Expenditure). In the calculation, values for the measuring poverty rate (P) and design factor (deft) 1.5, the expected Relative Standard Error (RSE) of 4.63%, and finally, an adjusted Response Rate of 99% at a 95% Confidence level used to represent the expected precision is acceptable at the domain level. To select a representative sample from this population, first, the initial sample size was determined by using the following scientific formula: where the deft is the design factor defined as the ratio between the square root of standard error using the given sample design and the standard error resulting from a simple random sample used. Based on the above scenario, total sample size =3,456 Households, and EAs = 288 . An equal allocation method was used to ensure that the survey precision was comparable across domains, where 36 EAs were selected from each domain. Based on a fixed sample take of 12 households per cluster, Equal Allocation formula Where: = total number of sample households and = Number of sample households allocated to stratum Table C.1: The distribution of sampled and surveyed households by domains EA HH Sampled Covered Sampled Covered Eritrean refugee domain 36 36 432 432 Somalian refugee domain

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Input:
**Table 6: Flood Hazard Classification and Infrastructure Design Standards**

| Return Period | Design Standard Required | Additional Measures |
|---|---|---|
| < 10-year zone | Standard design | None |
| 10–50 year zone | Elevated foundation | Drainage upgrade |
| 50–100 year zone | Flood-proofing required | Emergency access route |
| > 100-year zone | Avoid siting | Relocate |

Flood hazard maps were provided by the national meteorological and hydrological service. All school and health facility sites were verified against the 100-year flood hazard boundary before final design approval.

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Input: 1 Introduction Company owners and managers make two decisions with important implications in the labor market: what skills are demanded and who to hire. On the demanded skills, a driver of trends in employment is the changing demand for soft skills (Heckman and Kautz (2012), Weidmann and Deming (2021)). However, we know relatively little about what kinds of soft skills employers value in modern entry- level jobs (Heller and Kessler, 2022). On the decision of who to hire, it is in the best interest of companies to hire based on workers productivity. However, several studies have documented the existence of labor market discrimination in a wide range of contexts (Bertrand and Duflo (2017), Neumark (2018)) and it remains unclear how discrimination operates throughout the hiring process and how the existent empirical evidence on discrimination is linked to economic theory (Bertrand and Duflo, 2017). We conducted a correspondence study in 2023 using a large online job platform to assess demand for soft skills in the context of hiring discrimination in Malaysia. Malaysia is a particularly interesting setting because it is an upper-middle-income economy, home to multiple ethnicities representing large shares of the population, and previously documented gender gaps in labor force participation and wages. Usage context: background mention, primary mention, supporting mention.

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

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

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


Input:
Table 3 shows summary statistics for a select group of baseline characteristics, as well as a

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land owners in all countries in sub-Saharan Africa for which survey data are available

generally lasts 35-40 days. During this time, rainfall data is collected daily at a designated weather

The data set consists of the entire set of BASIX's purchasers of rainfall index insurance from 2005-2007,

that season. The BASIX data covers 42 weather stations, and includes a total of 19,882 customers from

entire set of BASIX's purchasers of rainfall index insurance

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

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

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


Input:
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

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

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

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


Input: 19 As property prices in the worst affected areas reduced the most, low income households responded by moving into low-rent housing being offered in these locations. On the other hand, middle income households moved away to avoid risk, and the wealthy, for whom insurance and self-protection was the most affordable, did not change where they lived. Poor people “ sort ” into low rent locations – which are often at higher risk to natural hazards. The problem is particularly acute in developing countries where there is a divide between the formal and informal markets for land. While formal developments may respect land use regulations, informal settlements are often located in hazard prone locations, such as on hill slopes, close to river banks, or near open drains and sewers. In Dhaka for example, informal settlements are developing across the metropolitan area, with many residents lacking basic public services and in locations at risk from flooding. In fact, most informal settlements do not have access to a public toilet within 100 meters, and 7, 600 households in 44 slums live within 50m of the river (World Bank 2005, Dhaka Urban Poverty Assessment). For the city of Bogotá, we use the same database discussed earlier to examine if poor people are at greater risk from natural hazards – particularly earthquakes. Usage context: background mention, supporting mention, primary mention.

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

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

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


Input:
**Annex 1**

**Demographics information.**

 This report is based on the information provided by 2176
young Syrians, between 18 – 23 ages, living in 34
different sub-districts within the governorates of Aleppo
and Idleb in Northwest Syria, covering 225 communities,
and 106 IDPs camp sites. 47% identified as IDPs and 53%
as part of the host community.

**Are you from the Host community or**

**IDPs?**

**Internally**

**displaced**

**person …**

**Host**

**Community**

**53%**

 In terms of marital status, the results showed a close split

between married (48%) and single (49%).
 With a representative number of respondents (at least 200) as widows and same amount for divorced.
Adding a layer of complexity and needs probably related to management of loss, livelihoods, and social
stigma.

**Marital status of interviewee**

**48%** **49%**

Married Single Widow Divorced Seperated

**16**

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

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

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


Input: The study: (i) compares the socio- economic profile of refugees with that of the Syrian population before the crisis and with the hosting populations of Jordan and Lebanon; (ii) provides a welfare and vulnerability assessment of Syrian refugees including a poverty profile, the socio-economic characteristics of higher poverty and where pockets of deep poverty are located; (iii) analyzes key drivers of welfare and poverty; and (iv) models monetary and non- monetary vulnerability.  In Lebanon, Jordan and Iraq, the Bank is leading an initiative to evaluate the socio-economic impact of the regional crises on the welfare of Syrian refugees and host communities in neighboring countries [ongoing]. Data on living conditions, access to services and economic opportunities, coping strategies and economic status are to be collected via a specialized household survey and a sub-component of the survey will be carried out on a semi-annual basis to continue to monitor and adapt support as needed.  A recent Bank paper, “ Turkey ’ s Response to the Syrian Refugee Crisis and the Road Ahead ” [completed in 2015] assessed the impact of Syrian refugees on host areas in various sectors. It found that the presence of Syrian refugees is placing a strain on municipal services, housing rental markets, social relations, and education services for Turkish households. Usage context: background mention, supporting mention, primary mention.

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

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

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


Input: -0.000* -0.001*** -0.001*** -0.000 0.000 -0.000 0.001 (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.001) Educ: < Primary - - - - - - - - Educ: Primary -0.028 0.058*** 0.127 -0.042* 0.077** -0.104 -0.172 0.121 (0.020) (0.021) (0.107) (0.022) (0.032) (0.069) (0.122) (0.361) Educ: Secondary 0.115*** 0.506*** 0.700*** -0.045 0.460*** -0.200** 0.098 0.849*** (0.031) (0.046) (0.100) (0.045) (0.107) (0.080) (0.212) (0.311) Educ: Post-sec 0.231*** 0.716*** 0.812*** 0.004 0.493*** -0.073 0.222 0.528** (0.024) (0.037) (0.078) (0.117) (0.121) (0.149) (0.367) (0.232) Years in Ethiopia 0.009*** 0.001 0.001 0.003 0.006 (0.003) (0.002) (0.004) (0.012) (0.015) Work outside camp 0.352*** (0.128) Region fixed effects Yes Yes Yes Yes Yes Yes Yes Yes Restrict to workers outside camp Yes N 3321 1626 494 3,069 830 975 238 73 Source: World Bank Staff based on SESRE 2023. Note: Columns 2 and 5-6 are restricted to working respondents. Columns 3 and 7-8 are restricted to employees. High-skill occupations include managers, professionals, and associate professionals. Ln Earnings is the log of monthly earnings winsorized at the 1st and 99th percentiles. All other models are linear probability models. Standard errors clustered at the EA level. * p < 0.10, ** p < 0.05, *** p < 0.01 Annexes

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

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

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


Input: 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 11055 The paper examines the early integration of Ukrainian refugee students into Italy ’ s education system following the Russia ’ s invasion of Ukraine in 2022. Using administrative and survey data, the study presents enrollment trends, academic performance, and barriers to educational integration. Findings from the analysis indicate that Ukrainian refugees face lower enrollment rates, higher absenteeism, and lower test scores than other students, particularly in subjects requiring language proficiency. Despite these challenges, teachers often recommend Ukrainian refugee students for advanced educational tracks, thus revealing their optimism about the potential of these students. Usage context: background mention, primary mention, supporting mention.

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

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

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


Input:
8 Flood return periods of 5, 10, 20, 50, 75, 100, 200, 250, 500 and 1000 are included in the Fathom data product.

We leverage a unique large-scale experiment on consumption measurement in Iraq designed for the Iraq Household and Socio-Economic Survey (IHSES) in 2012.

[1] In recall interviews, households are typically asked to report on food _consumption_ during the specified period and 1The World Bank's Living Standards Measurement Study (LSMS) survey finder includes a list of household consumption and expenditure surveys: of almost 90 surveys from more than 25 countries, more than 75 use recall.

(2017) compare recall questions on food spending from the Canadian Food Expenditure Survey to data from expenditure diaries.

The availability of repeated diary-recall measurements of food spending or acquisition is not unique to our setting, the Consumer Expenditure Surveys in the United States and the Canadian Food Expenditure Survey being notable examples.

Iraq Household and Socio-Economic Survey

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

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

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


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

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

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

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


Input: seekers. 81 There are several challenges associated with using central population registers to estimate refugee and asylum-seeker populations, including: consistency of the definition of refugees with the definition in the 1951 Convention and 1967 Protocol; difficulty and cost of establishing and maintaining a population register (UNSD 2014); and confidentiality safeguards. Compilation of statistics on forcibly displaced populations Several international organizations are involved in the compilation, analysis and dissemination of statistics on forced displacement including UNHCR, 82 Eurostat, IDMC, OCHA, International Committee of the Red Cross (ICRC), 83 WFP84 and IOM. Each of these actors has their own thematic focus and specific objectives, and applies their own methodologies. Asylum-seekers and refugees UNHCR is the principal organization responsible for the compilation, analysis and dissemination of data on asylum-seekers and refugees. UNHCR maintains a publicly available statistical online database85 with data for the period 1951-2014 on refugees (including people in refugee-like situations), asylum-seekers (pending cases), returned refugees, IDPs protected or assisted by UNHCR, returned IDPs previously protected or assisted by UNHCR, stateless persons and others of concern to UNHCR, disaggregated by country of origin and asylum. 86 Data are also provided on demographics, location, asylum-seekers (refugee status determination and monthly data) and resettlement. Usage context: primary mention, supporting mention, background mention.

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

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

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


Input:
_UNHCR
 Discussion
 Paper
 –15
 June
 2013_

from
 the
 temporary
 shelters
 in
 Thailand
 to
 their
 place
 of
 origin,
 the
 majority
 of
 whom
are
 single
 males
 who
 stated
 that
 they
 had
 returned
 to
 assess
 the
 security
 situation
 and
start
 re-‐establishing
 their
 livelihood
 before
 the
 return
 of
 other
 family
 members.
 The
dimensions
 of
 this
 spontaneous
 return
 movement
 have
 been,
 so
 far,
 negligible.

While
 the
 dimensions
 of
 IDP
 return
 movements
 remain
 extremely
 difficult
 to
 assess,
some
 37,000
 IDPs
 are
 estimated
 by
 the
 The
 Border
 Consortium
 (TBC)
 to
 have
 returned
home
 or
 resettled
 in
 surrounding
 areas
 between
 August
 2011
 and
 July
 2012 [3] .

If
 the
 current
 trend
 of
 political
 and
 socio-‐economic
 reforms
 continues
 and
 as
 larger
political
 events
 draw
 closer,
 such
 as
 the
 ASEAN/AEC
 agenda
 with
 Myanmar
 as
 Chair
 in
2014,
 a
 national
 census
 in
 2014,
 and
 national
 elections
 in
 2015,
 then
 the
 momentum
 to
translate
 cease-‐fire
 negotiations
 into
 peace
 agreements
 may
 increase.
 This
 may
 lead
 to
an
 increase
 in
 the
 number
 of
 spontaneous
 returns
 and
 the
 possibility
 of
 sudden
demands
 upon
 UNHCR
 to
 facilitate
 the
 voluntary
 repatriation
 of
 refugees.

**2.2.
 Protection
 environment**

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

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


Input: As explained in section 4, the HRVD dataset contains data on the number of human rights violations occurred since the start of the conflict in 1975 until its end in 1999 for each district. The types of violations recorded are killings, deaths due to deprivation and disappearances. We use only the number of killings to identify years and districts affected by the conflict. We exclude the deaths due to deprivation because the districts in which this occurred may very likely not be those where the conflict was most intense, but were simply places were the victims were hiding as a consequence of escaping from the troops, and died for starvation. In addition, since killings are less likely to affect entire families than deaths due to deprivation, there is a lower underreporting bias attached to the former measure relative to the latter one (Silva and Ball 2006). We also exclude disappearances as, according to HRVD data, they do not show enough time and geographical variation in order to identify individuals more or less exposed to the conflict. We believe that the number of killings proxies quite well the intensity of the conflict across time and space as their occurrence largely tracked the movements of the Indonesian military operations. The other two types of violations do not seem to show the same pattern (Silva and Ball 2006). For the same reason, we believe that it proxies quite well the destruction of houses and infrastructure and the displacement of people given the way in which the last wave of violence occurred (i. e. the scorch-earth technique employed by Indonesian troops as they moved towards West Timor).

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

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

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

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

protection data collected through Project 21

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

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

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