Input:
**Table of Contents:**

**Background** ....................................................................................................................................... 3

**Overview of UNHCR’s Referral Guidelines** .......................................................................... 3

**Data Collection and Analysis** ...................................................................................................... 3

**Summary of Findings** .................................................................................................................... 4

**i.** **Demographic Characteristics of Medical Referrals in January – December**

**2016 (n= 34,571)** ............................................................................................................................... 5

Figure 1. Medical referrals by admission category and final outcome on discharge .......... 5

Figure 2. Medical referrals per month; January – December 2016 (n= 34,571) ................. 5

Figure 3. Frequency of referrals per unique patient; January – December 2016 (n=
23,296) ........................................................................................................................................... 6

Figure 4. Proportion of referrals by gender and age group (n= 34,571) ............................... 6

Figure 5. Proportion of referrals by nationality (n= 34,571) .................................................. 7

Figure 6. Proportion of referrals by referral hospital (n= 34,571) ......................................... 7

Figure 7. Proportion of referrals by referring clinic (n= 34,571) ........................................... 8

Figure 8. Number of JHAS Madina clinic referrals by nationality (n= 9,488) ................... 8

Figure 9. Zaatri and Azraq referrals per month; January – December 2016 (n= 19,473) . 9

Figure 10. Proportion of referrals by diagnosis at discharge ............................................... 10

**ii.** **Mortality** ................................................................................................................................... 11

Figure 11. Number and proportion of mortalities by age group (n= 94) ............................ 11

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Input: Table 1 provides descriptive statistics for the years 2011 and 2014. 18 Labor force participation is very low in Turkey, around 54 percent of the working-age population in 2011, though it has been rising. The reason is that female labor force participation is particularly low at about one-third. The majority of employment is private sector, around one-third of the working-age population, compared to 6 percent employed in the public sector. There are a large number of unpaid workers (7 percent) and unemployment is at 5 percent of the working-age population, an unemployment rate of about 10 percent. School attendance has been rising over the period, from 12 to 16 percent of the working-age population, and the fraction retired has been steady at about 5 percent. Correspondingly, educational attainment has been rising though still 13 percent of the working-age population has no formal education, 57 percent at least completed primary education but not high school, and high school completion has risen from 30 to 34 percent. 17 Of those who have an irregular workplace 60 percent are agricultural workers, 14 percent work in construction, 7 percent in transportation and 5 percent in retail and in manufacturing each, and 3 percent as household employees. 18 Note that in 2014 new regulations for the Household LFS were carried out within the framework of European Union criteria. Consequently, statistics are not necessarily entirely comparable across years. Since we do not use aggregate time-series variation for identification this does not affect our empirical strategy, see Section 3. For those interested, the Turkish Statistical Institute provides consistent time-series on their website.

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Input: MIS data extracted at 30 September showed that cumulative cash transfer disbursements had reached 78 percent of the annual target, with 14,822 households having received at least one payment. The MIS disbursement module flagged 312 records with payment anomalies, of which 287 were resolved through validation against the beneficiary registration database and 25 were referred to the compliance officer for further investigation. The MIS was updated to add a duplicate detection algorithm that screens new registrations against existing records before activation.

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

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Input: except biscuits. Refugee households still report lower quantities, even when valuing the food ration quantities indicated as sold in markets. Possible explanations for lower food quantities are that food rations are only received once a month, which may not coincide with the interview date. Moreover, SESRE asks what food people consumed (not based on a pre-set list of food items), not food received as aid. Refugees may sell more than indicated. Valuing quantities of food aid with prices from SESRE suggests that if UNHCR food aid quantities were received/reported by refugees, refugees’ food expenditures would be much more comparable to those of hosts. Using WFP food aid information, we found a picture similar to UNHCR’s. Quantities consumed in SESRE are lower than food aid, as reported by WFP, except for CSB+ and salt (See Annex E for details of the disparity in food aid between the admin data disparity SESRE report). Box 5.2: Disparity between refugee ration aid and reported consumption quantities 0 10 20 30 40 50 60 70 80 90 100 Hosts Refugees Hosts Refugees Hosts Refugees In Camp Addis Ababa Total Own production Market purchase Transfers/gifs Hosts Refugees Hosts Refugees Hosts Refugees In Camp Addis Ababa Total

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Input: 15 Source: Authors ’ calculations based on data from the High Frequency Surveys of Ethiopia (2017), Nigeria (2018), Somalia (2017), South Sudan (2017) and Sudan (2017). As the Sudanese sample surveys IDPs living in the Abu Shouk and El Salam camps, we must understand these deprivations with the background that these settlements were created as emergency and crisis responses rather than durable, long-term solutions (Sudanese Government ’ s Joint Mechanism for Durable Solutions 2019). Although Sudan does have a national electric grid that supplies electricity to the urban and peri-urban areas of the nearby city El Fasher, IDP communities living in the camps report limited connection to the city ’ s electricity supply, reflected in the high deprivations in the electricity and cooking fuel indicators. The ad-hoc construction of dwellings in the two camps explains why 71 % of the IDP households in Abu Shouk and 65 % in El Salam live in tukuls or other permanent mud or wood structures (Sudanese Government ’ s Joint Mechanism for Durable Solutions 2019: p. 50), both of which register as unimproved housing types. Usage context: supporting mention, background mention, primary mention.

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Input:
In the recent past, the number of persons affected by drought has been comparable to
that of victims of hurricanes and floods (146 million, on average, between 2000 and
2005 according to the EM-DAT). The latest report of the IPCC predicts increased
water shortages in Africa (74 to 250 million people affected in 2020) and Asia:
"Freshwater availability in Central, South, East and Southeast Asia particularly in
large river basins is projected to decrease due to climate change which, along with
population growth and increasing demand arising from higher standards of living,
could adversely affect more than a billion people by the 2050s." (Intergovernmental
Panel on Climate Change 2007a, 10). Case studies, however, paint a contrasting
picture. The effect of a lack of drinking and irrigation water on migration is actually
less sudden than that of the meteorological events mentioned in the previous chapter,
and only generates progressive departures.

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

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

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Input: Cross-sectoral programming designed to meet families ’ holistic needs would also increase the odds of maternal and child well-being, including increasing provision of cash transfers through BISP, expanding access to ECE programs, ensuring food availability and affordability for mothers, and implementing emergency-response programs for continuity of basic services in the context of floods and other disruptive disasters to protect vulnerable mothers and young children. Both direct interventions that provide mental health services and indirect interventions that reduce exposure to stressors within communities and households are approaches to alleviate mental health concerns among mothers of young children in the FCV setting of the current study. In addition to individual-level impacts, societal and economic impacts result from reduced maternal depression, anxiety and stress. For example, costing estimates from Pakistan suggest that there is a $ 16. 6 billion cost per cohort of unaddressed maternal mental health concerns (Bauer et al., 2024). Limitations The data collection coincided with a politically sensitive time in Khyber Pakhtunkhwa, inclusive of security concerns for enumerators, ongoing election campaigns, and occasional disruptions to data collection, which could have impacted the accuracy and consistency of data collected. Further, repatriation efforts being implemented during the data collection period led researchers to avoid self-report determination of refugee (documented and undocumented) status and rely on enumerator report using observable indicators as outlined above. This may have therefore impacted the accuracy of the data on identifying refugee households. There are also several measurement constraints to be considered. The tools selected to measure maternal mental health may not cover all relevant dimensions of symptoms and experiences specific to the region of Pakistan studied, even though tools were specifically selected based on previous adaptation, validation and use in the province. Usage context: primary mention, supporting mention, background mention.

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Input: violent conﬂict. Besley and Mueller (2015a) argue that foreign investors seem to know that growth volatility changes with strong executive constraints and therefore react signiﬁcantly to their adoption. In summary, the literature suggests that a lack of constraints on executive power at the country level could play a key role in building inequalities across regions and ethnic groups. In the absence of strong executive constraint, we expect regions populated by ethnic groups that have access to executive power to perform better relative to others due to ethnic favoritism. Conversely, excluded ethnic groups should experience relatively worse economic performance compared to other groups in the absence of such constraints. 46 To test these hypothesis we use data on ethnic groups ’ access to executive power and night light intensity from the GROWup Research Front-End (RFE Release 2. 0) dataset and executive constraint data from the Polity IV dataset. We use night light intensity as a proxy for economic activity at the ethnic group level. 47 Night light data has the beneﬁt of being available on a yearly basis and of being measured at the local level where there is poor availability of statistical data. Usage context: background mention, supporting mention, primary mention.

GROWup Research Front-End
Polity IV dataset

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Input: We focus on two policy actions: legalization (in the sense of providing legal work and residence permits to all migrants) and measures aimed at improving the quality of employment for highly educated Venezuelan migrants. 6. 1 The Eﬀects of Legalization Based on the EPEC survey, approximately 90 % of Venezuelan migrants in Ecuador lack legal status, in the sense that they are not authorized to work. This has important consequences for Venezuelan workers. As shown in Section 4. 3, lack of legal status is associated with a higher likelihood of informal employment (column 5 in Table 7). Inspired by Clemens et al. (2018), the goal of this section is to use the estimates of these eﬀects to simulate the consequences of providing legal work permits to Venezuelans on the quality of their employment (measured by informality) and, through this channel, on their productivity (measured by wages). The relevant information is collected in Table 10. We classify Venezuelan workers that lack legal status on the basis of their education level (primary, secondary or tertiary) and the quality of their employment (formal or informal). Based on the data in column 3 15 Usage context: primary mention, supporting mention, background mention.

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Input:
Using data from the Armenia Land Tenure and Area study - a study designed specifically for this analysis - we compare the implications of the use of a proxy respondent versus the recommended self-respondent approach and the use of aggregated land data versus parcel-level land data (recommended).

The ALTA study was implemented with the technical guidance of the lead author by the International Centre for Agribusiness Research and Education (ICARE) in partnership with the Statistical Committee of the Republic of Armenia (ArmStat) and with the financial support of the 50x2030 Initiative.

The paper is organized as follows: section II describes the land tenure system in Armenia, providing context for the results that follow; Section III describes the ALTA study design and data; Section IV discusses SDG indicator computation and methods; Section V presents the results; and Section VI concludes.

The sample of the ALTA study consists of 1,200 households, scientifically selected from 100 urban and rural enumeration areas (EAs) covering both agricultural and non-agricultural households.

In addition to the module on land tenure, the ALTA questionnaire included a brief set of modules capturing
individual socio-demographic characteristics, educational attainment, employment status, and agricultural activity. [6]
An additional focus of the ALTA study was the validation of measurement approaches to land area estimation. To
this end, both Arms 1 and 3 included a module on land area measurement that incorporated GPS and satellite
imagery-based parcel-level area measurement. A series of cognitive interviews were conducted to ensure that the
land tenure questions were translated as intended from English to Armenian, as well as to understand how the
interpretation of questions varied across individuals, with a view to understanding male versus female

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Input: Refugees Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese In camp Addis Ababa Total Health institutions (health center/hospital) Home Other Percent Figure D.10: Childbirth in health institutions (children under five years) Source: World Bank Staff based on SESRE 2023. Annexes 104 Hearing Walking or climbing steps Percent Refugees Eritrean Somali South Sudanese In Camp Addis Ababa Total Hosts Seeing Diﬀiculty with selfcare Communicating Remembering or concentrating Refugees Hosts Refugees Hosts Refugees Hosts Refugees Hosts Refugees Hosts 50 40 30 20 90 100 80 70 60 10 0 Figure D.13: Types of disability Source: World Bank Staff based on SESRE 2023. - 10,000 20,000 30,000 40,000 50,000 60,000 Hosts Refugees Addis Ababa Total annual rent expenditure Per adult equivalent rent expenditure Figure D.14: Rent expenditure (Refugees and hosts in Addis Ababa) Source: World Bank Staff based on SESRE 2023. 0 20 40 60 80 100 Eritrean Somali South Sudanese Addis Ababa Eritrean Somali South Sudanese Addis Ababa Eritrean Somali South Sudanese Addis Ababa Has hand washing place/item Water available Detergent available Hosts Refugees Percent Figure D.15: Hand washing facility Source: World Bank Staff based on SESRE 2023. Annexes 105 Table D.5: Labor force statistics by survey domains Eritrean Somali

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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:
composite measure for human capital. We extract real GDP and human capital data from Penn World

Table 10 (Feenstra et al., 2015), using the "rgdpna" series, which measures real GDP in constant 2017

schooling and returns to education (Inklaar and Timmer, 2013). We extract the population from World

Development Indicators (WDI).

#### **3.3 Sample Construction**

The baseline populations served by the East Road (within the buffer zones) were established by utilizing
WorldPop open source data. To estimate the number of people affected by rain event, however, a series
of models were run to simulate the locus of impacts for each rain event (3-, 10-, and 30-year events) and
their subsequent effects on access. Repeated events might affect the same people, and so, the cumulative
impacts over the lifetime of the road can be thought of as 'person-disruptions' - i.e., the sum of individual
disruptions. If, for example, an individual living on the East Road was cut off from access to hospitals three
times over the thirty-year period, this experience would account for three person-disruptions.

Using Global Positioning System (GPS) tracking records for the Malaita East Road from Atori to Dala, 5,856
road segments with gradient details were delineated and mapped using geographic information system
(GIS) mapping software. These segments were mapped for the current road and also used to model surface
conditions defined by the proposed upgrading projects.

Cost data for similar road projects also informed assumptions about per-unit (km) repair costs
for each type of road surface subject to various damage levels.

Global Positioning System (GPS) tracking records

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Input: However, should ASM respond to large-scale activities, either by increasing or decreasing activity in the close geographic area, we will end up estimating the impact of these sectors jointly. In a later stage, should the opportunity arise, we encourage researchers to try to disentangle the effects of small-scale and large-scale mining. 3 Data To conduct this analysis, we combine different data sources using spatial analysis. The main mining data is a dataset from InterraRMG covering all large-scale mines in Ghana, explained in more detail in section 3. 1. This dataset is linked to survey data from the DHS and GLSS, using spatial information. Geographical coordinates of enumeration areas in GLSS are from Ghana Statistical Services (GSS). 2 Point coordinates (global positioning system [GPS]) for the surveyed DHS clusters3 allow us to match all individuals to one or several mineral mines. We do this in two ways. First, we calculate distance spans from an exact mine location given by its GPS coordinates, and match surveyed individuals to mines. These are concentric circles with radiuses of 10, 20, and 30 kilometers (km), and so on, up to 100 km and beyond. In the baseline analysis where 2 The data was shared by Aragón and Rud (2013) 3 Both the DHS and GLSS enumeration area coordinates have a 1-5 km offset. The DHS clusters have up to 10km displacement in 1 % of the cases. Usage context: background mention, supporting mention, primary mention.

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Input: 60 80 100 Camp Hosts Female Camp 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 3.8: Female occupations Source: World Bank Staff based on SESRE 2023. Jobs and Livelihoods 31 0 10 20 30 40 50 60 Camp Hosts Male Camp Refugees Male Camp Hosts Female Camp Refugees Female Figure 3.11: Hourly earnings 0 5 10 15 20 25 30 35 40 45 Camp Hosts Male Camp Hosts Female Camp Refugees Male Camp Refugees Female Figure 3.10: Hours per week Source: World Bank Staff based on SESRE 2023. Note: Hourly earnings are past-month earnings in the main occupation in Birr divided by the typical hours worked in a month over the past year. Only refugees working outside of camps start to see earnings improve with schooling. Working outside the camp is associated with a 42 percent increase in earnings. Most importantly, the relationship between completing secondary and post-secondary schooling and wage earnings becomes significant only when the refugee sample is restricted to workers outside the camps (see Annex D, Table D.7). This indicates that refugees only benefit from education and are incentivized to invest in education

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Input:
lending operations database in each fiscal year.

In sections 2 and 3 all operations that are IDA financed are considered. This includes development policy

of outcome ratings provided by the World Bank's Independent Evaluation Group (IEG). The portfolio review

examines how the IDA portfolio has evolved since 2001, in terms of the number of projects, size of the portfolio,

Regression analysis comparing IEG outcome ratings of projects in FCS and non-FCS countries shows that

come rating from IEG (see Table 2). There are also no differential time series trends for this measure of outcome

stated project development objectives, as well as macro level factors, such as GDP growth and country policy and institutional assessment (CPIA) ratings.

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Input:
which collected heretofore unavailable expenditure data on each type of subsidized food

4. New 1997 Household Budget Survey

Egyptian food subsidy system.' [8] This study used expenditure data from the 1990/91

Household and Income Expenditure Survey (HIES), which was a large, nationally

and Statistics (CAPMAS).1 [9] One of the main problems with this 1990/91 HIES survey

Household and Income Expenditure Survey (HIES)

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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: Poverty remains widespread and social indicators are well below the average for Sub-Saharan Africa. Chad is ranked 173 among the 177 countries surveyed in the 2006 UNDP Human Development Report. The incidence of poverty (defined as the proportion of households with annual spending below what is necessary to meet minimal needs) is estimated at 55 percent according to a 2003 household survey; an estimated four-fifths of the population of about 8. 8 million is living on less than a dollar a day3. Of the population over 15 years old, more than 73 percent (and 76 percent of women) are illiterate. Access to potable water has improved over past years, but is still limited to one out of three people in 2005. Less than two percent of the population has access to electricity and only 1021 kilometers of roads has been paved on a surface area of over 1. 2 million square kilometers. As already mentioned, Chad has recently become oil producing country; however, the economy remains largely agricultural and pastoral. About 80 percent of the country ’ s population lives in rural areas and continue to make their living4 from agriculture and livestock. Cotton is the principal cash crop, employing about 300, 000 families. Usage context: background mention, primary 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: primary mention, supporting mention, background mention.

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

household survey data
household ‐ level data

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Input: reason to believe that the provision of services by donors and non-state actors could either strengthen or weaken citizens ’ deference to government. I will identify the conditions under which these two scenarios are likely to occur. On the one hand, citizens may be less likely to support the government with deference to its laws and regulations when they credit non-state actors or donors for service provision. The provision of services by donors and non- state actors is likely to prompt citizens to question why they should pay taxes to a government that is not providing them with anything in exchange. On the other hand, the provision of goods and services by donors and non-state actors might strengthen citizens ’ legitimating beliefs and their willingness to defer to governmental laws and regulations if citizens view their government as essential to leveraging and managing these external resources. I assess these competing hypotheses using multi-level analyses of Afro- barometer survey data. The sample, drawn from a continuum of developing societies in Africa, allows us to analyze associations between donor and non- state actor service provision and the sense of obligation to comply with the tax authorities. Third, I assess the relationship between the provision of ser- vices by donors and non-state actors and citizens ’ willingness to defer to two additional authorities, the police and courts. Usage context: background mention, primary mention, supporting mention.

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Input: Road data quality in the southern provinces is lower than in other regions due to the absence of electronic traffic count equipment on rural roads and the reliance on visual condition assessments conducted by untrained district public works staff. The project will support a road condition data quality improvement program under Component 3 that trains district engineers in standardized pavement condition index methodology and equips them with ruggedized tablets for electronic data entry. Improved road data quality is expected to reduce the cost of prioritization errors in future maintenance planning.

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Input:
and girls. Maternal and reproductive health services remain underdeveloped in some areas, struggling
to be fully effective due to a lack of material and financial support.

**5.2** **Social inclusion**

The most significant differences or restrictions in terms of socio-economic development affecting refugees
with particular characteristics are:

**a.** **Access to biometric identity cards and unique identifier number:** The continued lack of access to

legally recognized identity cards for refugees issued by the competent authority in Chad, ANATS, and
national identification numbers, challenges their inclusion into national system and limits their socioeconomic integration in the country.

**b.** **Access to civil registry civil status documents:** The low percentage of registered births, due to

significant deficiencies in the Civil Registration and Vital Statistics (CRVS) system in Chad, especially in
rural areas, exposes refugees born in Chad to the risk of statelessness.

R E F U G E E P O L I C Y R E V I E W F R A M E W O R K > **R E P U B L I C O F C H A D** 13

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Input:
There are different ways to arrive at a value for housing services consumed by nonrenters, which have different advantages and disadvantages (see Deaton and Zaidi, 2002). In POF, households that own their dwelling (even if still paying the mortgage) or that

_Temporal and spatial price adjustment._ To make the consumption aggregate and average costs per calorie
comparable across households, we adjust expenditure values temporally and spatially. POF was collected
throughout a full year and its reference periods go back up to 12 months. Figure 2 shows the temporal
variation of prices for different Brazilian states over the reference period of the survey. On average, prices
increased by 26.8 percent over the reference period - a monthly average of 1 percent. IBGE (2020)
provides temporal deflators in the publicly available data, which we use to deflate prices and the
consumption aggregate to express all monetary values in January 2018 values.

13 There are several differences between our consumption aggregate and other studies using POF data. In one of the
most recent ones (Oliveira et al. 2016), the authors aim to measure and analyze welfare, poverty (using the
administrative "poverty'' line equivalent to half a minimum wage), inequality, and vulnerability.

Midwest-Rural 0.997 0.671 0.933
_Source:_ Own calculations using POF 2017/18 data.
_Note:_ Prices in the urban Southeast are the reference prices. While we use household-specific price indices in our estimations,
for ease of presentation we calculated regional averages of household-specific indices and divided them by the
Southeast-Urban average.

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Input: Ethiopia–Household Welfare Statistics Survey (HoWStat)—excludes the majority of displaced populations (Internally Displaced People [IDPs] or refugees) from its sample of households. Thus, we have limited in-depth information on the socio-economic outcomes—including on poverty— for refugees across all camps in Ethiopia to compare with Ethiopian hosts. SESRE collected data from November 2022 to January 2023, from a nationally representative sample of 3,452 refugee households and their hosts. The SESRE covers all currently operating refugee camps of major refugee groups: Eritreans, South Sudanese, and Somalis, as well as the out-of- camp refugees of Addis Ababa and their respective host communities. The survey was aligned with the HoWStat methodology, allowing comparability between refugees and their host communities. The World Bank, Ethiopia’s RRS, Ethiopia’s Statistical Service, and UNHCR collaborated to implement SESRE10 and was the first of its kind, building on the “Skills Profile Survey 2017, A Refugee and Host Community Survey” conducted in Ethiopia in 2017. The SPS 2017 was conducted in refugee camps and host communities in four regions in Ethiopia. The survey was used to draw a profile for skills and potential opportunities for refugees and host 9 See Annex C for detailed information on survey design and methodology. 10 Financial

Ethiopia–Household Welfare Statistics Survey

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Input:
To mitigate issues arising from the time interval between the 2007 Population Census and EMDHS 2014, only

EMDHS at regional level. The table shows that measured undernutrition rates in EMDHS and the estimated rates

regression of z-scores is estimated in the EMDHS with addition of the SAE estimates. The regression includes the

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Input: Second, there are cases where the current study reports data by nationality, but the corresponding figure in the Trends in International Migrant Stock refers to the foreign born. This situation generally arises when a census does not report the number of foreign-born migrants on a bilateral basis. Examples include Austria and Côte d ‘ Ivoire. Third, differences in the years to which the data refer can generate large disparities. For example, this study uses the 1966 data for Australia, whereas Trends in International Migrant Stock reports data for 1970. Overall, however, the fact that the totals are remarkably close in every decade adds credence to the estimates here. IV. THE EVOLUTION OF GLOBAL BILATERAL MIGRATION The greatest strengths of the global migration matrices are their bilateral coverage, the number of decades covered, and the disaggregation by gender. These data are too rich for a full analysis of all movements between all pairs of countries. Instead, this section summarizes the major trends in the evolution of bilateral migrant stocks, based primarily on World Bank regions. 25 Global Trends The migration matrix for the 1960 census round reflects a realigning world in the postcolonial era. Over the 1960-2000 period, the composition of world migration 25 Appendix 1 details the World Bank regions: South Asia, East Asia and Pacific, Sub-Saharan Africa, Latin America and the Caribbean, Europe and Central Asia, and Middle East and North Africa. High-income Middle East and North Africa refers to the predominantly oil producing countries in the Persian Gulf (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) and to Israel. Usage context: background mention, supporting mention, primary mention.

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Input: and their hosts by: (i) understanding different dimensions of welfare, such as monetary poverty, inequality, multidimensional poverty, food security, and shocks; and (ii) understanding determinants of welfare and estimating the cost to meet basic needs through a combination of assistance and some economic inclusion of refugees into national systems. Chapter 6 aims to understand how the location of camps determines labor market outcomes, highlighting the importance of refugees’ location as part of the development strategy for refugees in Ethiopia. Chapter 7 looks at social cohesion by showcasing attitudes between refugees and hosts and the level of social integration of refugees. Chapter 8 highlights policy directions based on the conclusions of the report to maximize the benefits of hosting refugees while minimizing the costs. (vi) Differences in poverty estimation: The poverty measurement methodology is distinct for each survey with SESRE applying the same methodology as HoWStat. Despite the difference in methodology used in the Skills Profile Survey (SPS) and SESRE, we find similar patterns in some of the indicators common in both surveys among in camp refugees such as demographic composition, primary and secondary net enrollments, housing condition, access to basic infrastructures, employment and attitude of hosts toward refugees. Moreover, both

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

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Input:
6 However, this may reflect differences in rainfall or farming intensity.
7 We use two poverty maps based on the General Population and Housing Censuses of 1998 and 2009. The poverty
map for 1998 was developed by GREAT (Applied and Theoretical Economics Research Group) and combines the
1998 census and the household survey ELIM (Integrated Light Household Survey) of 2006.

household survey ELIM (Integrated Light Household Survey)

General Population and Housing Censuses of 1998 and 2009

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Input: 15 resulting in government forces recapturing rebel held territory, establishment of a rebel base or headquarters, rebel activity that is not battle related (e. g. presence or the killing of civilians), and territorial transfers. The dataset consists of 4, 145 battle events for the 1960 – 2004 period. In the present analysis, we use 2, 530 of these. The remaining events were dropped as they either were in countries not included in the analysis, or because information was missing for one of the key variables. Each conflict event is associated with geographic coordinates and a date of occurrence. This information allows for spatial and temporal modeling of conflict events. The dataset used in this article covers 14 countries in Central Africa. 6 of them had a conflict in the 1960 – 2004 period according to the Uppsala / PRIO Armed Conflict Dataset (Gleditsch et al., 2002): Angola, Burundi, Republic of Congo (Brazzaville), Democratic Republic of Congo (Zaire), Rwanda, and Uganda.

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

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Input: The study will conduct an ex-ante micro- simulation using pre-crisis household data (IHSES 2012) and macroeconomic projections for 2014 to gauge the distributional impact of the crises across groups (e. g. individuals and / or households, sectors, IDPs and host communities) and space (e. g. urban / rural, governorates).  The Economic and Social Impact Assessment for Kurdistan Region of Iraq [completed in 2015] provides an analysis of the impact of displaced people on access to and quality of service delivery across several sectors.  The Lebanon Economic and Social Impact Assessment of the Syria Conflict [completed in 2013] provides an analysis of the impact of displaced people on access to and quality of service delivery across several sectors.  The Bank and UNHCR undertook a welfare assessment of Syrian refugees living in Jordan and Lebanon [completed in 2016] focusing on welfare, poverty and vulnerability.

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

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

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

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Input: 29 should be entered immediately into the accounts; and (c) Payment must be recorded as soon as they are made. Budget implementation should be reviewed periodically to ensure that programs are implemented effectively and to identify any financial or policy derailment. The review of budget execution should cover financial, physical and other performance indicators. Development budgets are often beset by implementation problems because of insufficient implementation capacities and other factors such as delays in mobilizing external financing, overoptimistic implementation schedules or difficulties in importing supplies. It is thus important to have in place mechanisms for reviewing the most significant or problematic projects. These could consist of a regular monthly or quarterly review of projects within the line ministries and a midyear review involving line ministries and central agencies29. The government has taken steps to improve the tracking of budget expenditure until the intended destination, particularly investments spending, for which a tracking survey was entrusted in 2005 with the Ministry of infrastructures. In addition, the ministries took themselves certain internal initiatives, in particular in health and education sectors, but the action plans of these ministries were not updated as envisaged in 2005, and there are neither reliable benchmark, nor quantitative targets as regards improvement of the arrival of the expenditure at intended destination in these sectors. Usage context: background mention, supporting mention, primary mention.

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Input: 15% 25% 12% 71% Participation (relaxed) 30% 22% 54% 60% Unemployment (relaxed) 30% 57% 21% 82% Employment-to-population ratio 21% 9% 43% 11% 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. 0 20 40 60 80 100 Camp Hosts Male Camp Refugees Male Addis Hosts Male Addis Refugees Male Employed Unemployed, searching Unemployed, not searching Inactive not in school Inactive in school Percent Figure 3.28: Male youth work status Source: World Bank Staff based on SESRE 2023. Employed Unemployed, searching Unemployed, not searching Inactive not in school Inactive in school Percent 0 20 40 60 80 100 Camp Hosts Female Camp Refugees Female Addis Hosts Female Addis Refugees Female Figure 3.29: Female youth work status Source: World Bank

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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: Each respondent was presented with three vignettes, where key aspects of the sce- narios were randomly varied across respondents. These three vignettes were designed to probe the impact of diﬀerent pull and push factors on the refugees ’ return deci- sion, allowing us to go beyond the data limitations of the above analysis. That is, the vignettes not only explore the impact of security on return decisions, but also of employment prospects in both the country of asylum and Syria, the status of property in the home community, and the availability of ﬁnancial assistance. In particular, the ﬁrst vignette probes three questions: ﬁrst, whether the ability to 11According to this classiﬁcation, Jebel Saman, Deir-ez-Zor, Homs, Al Ma ’ ra, and Duma are high- conﬂict districts. 16 Usage context: supporting mention, primary mention, background mention.

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Input: 18 household socioeconomic information. In some cases, socioeconomic information is collected at the individual or household level but more often information is collected at the community level. It is extremely rare to have unit record data sets on IDPs, which explains why we found only 18 studies in the Econpaper repository as already documented. Recognizing the problem of scarcity and availability of information on IDPs, international organizations have set up in several countries coordination mechanisms to count IDPs usually coordinated by IOM, UN ‐ OCHA or the UNHCR. There are also global efforts to centralize this information on the part of organizations such as the UNHCR, UN ‐ OCHA, the international Displacement Monitoring Centre (iDMC) or the Joint IDP Profiling Services (JIPS). These efforts are making good progress on harmonizing counts of IDPs but remain short of establishing proper data collection systems that could deliver in the years to come unit data of quality for research. Hence, research on IDPs remains constrained by lack of data, lack of a blueprint on how to collect data and lack of an organization dedicated to IDP data collection. Usage context: background mention, supporting mention, primary mention.

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Input: Poverty remains widespread and social indicators are well below the average for Sub-Saharan Africa. Chad is ranked 173 among the 177 countries surveyed in the 2006 UNDP Human Development Report. The incidence of poverty (defined as the proportion of households with annual spending below what is necessary to meet minimal needs) is estimated at 55 percent according to a 2003 household survey; an estimated four-fifths of the population of about 8. 8 million is living on less than a dollar a day3. Of the population over 15 years old, more than 73 percent (and 76 percent of women) are illiterate. Access to potable water has improved over past years, but is still limited to one out of three people in 2005. Less than two percent of the population has access to electricity and only 1021 kilometers of roads has been paved on a surface area of over 1. 2 million square kilometers. As already mentioned, Chad has recently become oil producing country; however, the economy remains largely agricultural and pastoral. About 80 percent of the country ’ s population lives in rural areas and continue to make their living4 from agriculture and livestock. Cotton is the principal cash crop, employing about 300, 000 families.

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

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

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

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

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

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

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

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

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

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

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Input: In other settings, NGOs such as Rozan in Pakistan (Rashid, 2001), Profamilia in the Dominican Republic (Guedes et al., 2002), and the Musasa Project in Zimbabwe have trained law enforcement personnel on issues related to gender-based violence. Elsewhere, governments have collaborated with the United Nations to provide training and support for the police and judiciary. For example, ILANUD is a joint institute of the government of Costa Rica and the United Nations that works with governmental agencies throughout Latin America to improve the work of prosecutors, judges, lawyers, police and other professionals in criminal justice generally, and gender-based violence specifically (Villanueva, 1999; ILANUD, n. d.). Most of these initiatives have been evaluated using key informant interviews and pre and post questionnaires before and after training-if they have been evaluated at all. Nonetheless, training appears to be both constructive and urgently needed (Rashid, 2001; Villanueva, 1999). Other lessons learned include the finding that changing attitudes of law enforcement is a challenging, long-term process. The quality of the trainings ’ content and the skills of the trainer are essential. Training appears to be most effective when all levels of personnel (especially high-level officials) participate, and when training is backed up with changes throughout the institution, such as policies, procedures, adequate resources, and continual monitoring and evaluation. Special police stations or cells for crimes against women All-women police stations began in Brazil and were later tried in other countries in Latin America and Asia. As of 2003, for example, Nicaragua had 17 police stations for women and children (called

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Input: related to education, gender, and age. The results in Figure 3.26 show that refugees are under-represented in high-skill occupations and services and sales relative to what we would expect based on their age, gender, and education, and substantially over-represented in crafts and related trades. Among employee workers, OCP refugees also earn less than hosts, though the wage gap is smaller than for in-camp refugees. Annex D, Table D.9 shows that refugees in Addis earn 25 percent less than their hosts. Even after adjusting for demographic characteristics, occupation, and sector of work, this wage gap remains at around 19 percent. 0 20 40 60 80 100 Addis Hosts Male Addis Refugees Male Addis Hosts Female Addis Refugees Female - Employed Unemployed, searching Unemployed, not searching Inactive not in school Inactive in school Percent Figure 3.22: Work status by gender Source: World Bank Staff based on SESRE 2023. 0 20 40 60 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

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

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

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Input:
3 UNHCR Pakistan Monthly Protection Trends Report, May-Aug 2017, cites similar reasons for return to Afghanistan including the
following pull factors: reunion with family in Afghanistan, employment / livelihoods, no longer fear of persecution, UNHCR
assistance, happy to return and the following push factors: strict border entry requirements, uncertainty of POR card extension, no
overall protection value of POR cards, overall deterioration of security situation in Pakistan, arrest and detentions, denial of access
to services.
4 UNHCR Pakistan Monthly Protection Trends Report, July 2017, reflects similar means for persons to receive information on
repatriation, collected during VolRep Exit Interviews and Encatchment Center reports with Afghan returnees, stating they receive
information on Afghanistan from the Afghan community in Pakistan, UNHCR, and visits to Afghanistan.
5 Example provided of carpet weaving businesses returning to Afghanistan and thus resulting in a number of carpet weavers out of
work in Khyber Pakhtunkhwa.

UNHCR Pakistan Monthly Protection Trends Report

Encatchment Center reports with Afghan returnees

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

Labor Force Surveys
high-frequency phone surveys

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

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Input: some but not all of the high trust in Somali camps relative to other domains. 7.2 Social interactions Social and community integration is fundamental to refugees’ ability to improve their livelihoods, support systems, and economic integration. Having friends in the host country is a valuable resource for refugees; Ethiopian friends can provide valuable information, employer connections, assistance with language, and countless other types of social and economic support. This can also promote more positive attitudes between groups. Social integration has improved well-being, health, and educational achievement for refugee adolescents across various settings (Boda et al., 2023). 0 5 10 15 20 25 30 35 Eritrean Somali South Sudanese Addis Ababa All Refugees Family Friends Figure 7.12: Share with family or friends in Ethiopia Source: World Bank Staff based on SESRE 2023. 0 5 10 15 20 25 30 35 40 Age Under 30 Age 30-44 Age 45-64 Age Over 64 Female Male Figure 7.13: Share with friends in Ethiopia by demographic group Source: World Bank Staff based on SESRE 2023. Markets and Opportunities 69 Despite the generally positive attitudes described, social integration—measured by the friends and family refugees have in Ethiopia—is low. Only 7 percent of refugees report having family

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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

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