Input: Geospatial data from the national land registry, including parcel boundary polygons, ownership classification codes, and historical transaction records, were reviewed during project preparation to assess land tenure risks in the areas earmarked for infrastructure works. The geospatial data revealed that 23 percent of subproject sites intersected with unresolved customary land claims, triggering the preparation of individual resettlement plans for the affected sites. Geospatial data will be updated following the completion of land demarcation activities planned under Component 1.

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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Input: standard ﬁxed or random eﬀect approach is not suﬃcient to ensure correct inference; clustering standard errors by individual is necessary. This is what we do. Having described how the dependent variable is constructed, we turn to regressors. We begin by describing how we construct an estimate of g E [yhs | zh], the level of income (or consumption) yh s that a migrant with characteristics zh can expect to earn in district s. To construct such estimate, we use the 1995 / 96 NLSS data. The reason for using the 1995 / 96 data instead of the 2002 / 3 NLSS survey is to avoid reverse causation, i. e., migration causing a change in income patterns. Migrants are unlikely to be able to accurately predict the evolution of incomes in each district over time. Income and consumption levels observable before migration are thus a reasonable starting point. Usage context: supporting mention, background mention, primary mention.

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Input:
<!-- PAGE 3 -->
**Estimating a Poverty Line for Brazil Based on the 2017/18 Household Budget Survey** **[+]**

**Keywords:** poverty lines; food poverty line; basic needs; household budget survey; Brazil

2017/18 Household Budget Survey
Household Budget Survey

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Input:
effects is Calahorrano (2011). Using panel data for Germany between 1999 and 2008, she finds   that immigration concerns decrease over the life-cycle.

similar to Calahorrano (2011). However, given the lack of comparable panel data surveys for a   large group of countries, we use pooled cross-sections from the European Social Survey (ESS)

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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: background mention, primary mention, supporting mention.

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Input: The descriptive characteristics of foreign-born and host community households are still comparable, and therefore allow for comparisons between 2013 and 2014. It is possible to make some inferences on welfare changes by looking at changes in host community employment rates and labor market characteristics. Overall, this paper finds no negative effects on host community welfare from an increasing population of SUTPs. As other authors have stated, the influx of SUTPs has had both positive and negative impacts. It seems on average, the host community has been strong and adaptive, and not negatively impacted. This is not to disregard that real strains do exist in some regions where the SUTP population is very large. Nor do these results undermine findings of displacement effects in the labor market that certain types of workers are experiencing. However, on average nationally, we do not see a systematic decline in the welfare of the host community between 2011 and 2013. The remainder of the paper is organized as follows. Section 2 outlines the data availability and technical issues. Section 3 discusses descriptive statistics of the foreign-born and host community. Section 4 explores the impact of the foreign-born population on host community welfare. 1. DATA AND TECHNICAL ISSUES Data Sets Data availability limits which data set can be used to identify the foreign-born population and geographic location while measuring poverty. The Turkish Statistical Institute (TUIK) has been conducting three nationally representative surveys annually since 2005; the Household Income and Consumption Expenditure Survey (HICES), the Survey on Income and Living Conditions (SILC) and the Labor Force Survey (LFS). However the HICES, which is the national survey that is used to measure official poverty, 5 UNCHR, 2013pg 13 6 UNHCR (22 November 2013), UNHCR (15 September 2014) 7 UNHCR (22 March 2013), Erdogan (2014), pg 14 8 This technical issue will be discussed further later in the paper. Usage context: supporting mention, background mention, primary mention.

Household Income and Consumption Expenditure Survey

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Input: Papaioannou, 2016; Berman et al., 2017; Harari and Ferrara, 2018; Eberle et al., 2020; McGuirk and Burke, 2020b). As a further robustness check, we also use data on conflict incidence and intensity from the UCDP, which uses a more conservative definition of conflict. The UCDP dataset is manually curated and compiled with automated computer assistance (Sundberg and Melander, 2013). The UCDP defines an armed conflict event as “ an incident where armed force was used by an organized actor against another organized actor, or against civilians, resulting in at least one direct death at a specific location and a specific date ” (Pettersson et al., 2020). We extract daily event observations from the UCDP dataset if the location of the actual event is exactly known, the event location is within a radius of less than 25 km around a known point, or at least the administrative district where the event happened is known. As pointed out by Eberle et al. (2020), the UCDP events are more likely to capture violence between large-scale and more structured groups. Table B. 2 shows that on average, conflict events seem to occur more in refugee-hosting areas. This is of course not a causal interpretation but a simple correlation. Usage context: background mention, supporting mention, primary mention.

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Input:
The novelty is that a new, more spatially and temporally detailed data set for nightlights, the Visible Infrared Imaging Radiometer Suite (VIIRS) product from the National Oceanic and Atmospheric Administration (NOAA), following the work of Elvidge et al. (2017), is employed. In addition, settlement layers have been used to remove nightlight cells with zero population to reduce the impact that "empty" cells could have on the analysis.

This paper utilizes a newer nightlight data set, the VIIRS Day/Night Band (DNB) provided by
The Earth Observations Group (EOG) at NOAA/NCEI. The data are produced following the
methodology of Elvidge, et al.

The VIIRS data have a number of advantages over the widely used, but now discontinued,
Defense Meteorological Satellite Program (DMSP). Firstly, they have a higher resolution,
450m by 450m compared to 1km by 1km for the DMSP.

The WorldPop data sets have been used to identify settlement areas in Myanmar and Vietnam
(WorldPop 2013) (Worldpop 2016). These data sets have a spatial grid cell resolution of
approximately 100 meters at the equator and estimate the number of persons per square.

\n<!-- PAGE 13 -->\nFor Indonesia, the Philippines and Thailand high resolution settlement layers from Facebook Connectivity Lab and Center for International Earth Science Information Network - CIESIN - Columbia University was used.

Visible Infrared Imaging Radiometer Suite (VIIRS) product from the National Oceanic and Atmospheric Administration (NOAA)

Defense Meteorological Satellite Program (DMSP)

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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.

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Input: 11 There may be grounds for skepticism about these estimates for madrassa enrollment. Since the data were collected prior to 2001, geopolitical changes after September 11 could have led to greater madrassa enrollment. In addition, the household-based survey faces the usual problems of accurately estimating a low-probability event — although enrollment is less than 1 percent in these surveys, the sampling error is large (see Bauman, 2001, for a description of similar problems in estimating home-schooling in the United States). Finally, while the census of populations does not face the problem of small samples, it is not that recent (1998) and some may have reservations regarding the quality of government data. 10 The LEAPS census of schooling choice conducted in 2003 provides a rough check on these numbers (see appendix for details). This census was conducted in three districts of Punjab and villages were chosen randomly based on the criterion that each village must have at least one private school. Typically, this means that the villages lies somewhere between fully urban and fully rural populations and are not representative of the districts that they are in. Estimates from the LEAPS census show that as a percentage of enrolled children, the numbers in two of the three districts are slightly higher than those of the population census. Usage context: primary mention, supporting mention, background mention.

census of populations
household-based survey

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Input: 8 as self-confidence, responsibility, and respect. Additionally, the curriculum includes workplace readiness skills, such as interviewing and time management. SECTION 2: STUDY TIMELINE & DATA A quasi experimental impact evaluation design was embedded into the NVSP. As mentioned before, the NVSP received 38 applications from eligible NGOs. Per well-developed selection criteria, 8 the highest 22 ranked proposals were selected to receive funding. Each of the 38 proposals included a list of 50 youth (the minimum number of youth set by the NVSP) who would benefit from the project if selected for funding. However, as mentioned before, the 22 selected projects benefited a total of 1, 296 youth, exceeding the set target of 1, 100 volunteers. Of the 50 volunteers included in each of the 38 proposals, 22 youth per proposal were randomly selected to participate in the impact evaluation study. Therefore, the initial sample size of the study comprised a total of 825 youth: 473 youth who served as the treatment group (representing the 22 selected NGOs that received NVSP funding) and 352 youth who served as the comparison group (representing the 16 non-selected NGOs). However, two NGOs refused to participate in the study once informed that their proposals had not been selected for funding. Usage context: background mention, primary mention, supporting mention.

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Input: 2 1. INTRODUCTION Refugees pose a massive moral, political and economic challenge for potential host countries. 1 The scale of the challenge is larger than ever, with 60 million people forcibly displaced by conflicts across the world (UNHCR, 2014). War in Syria has produced more refugees than any other conflict of the past two decades: around 4. 6 million have fled the country, with an additional 7. 6 million internally displaced. 2 About 2. 5 million Syrians have found refuge in Turkey, making it the largest refugee-hosting country worldwide. This paper combines newly available data on the distribution of Syrian refugees across Turkey and the Turkish Labour Force Survey to assess the impact on Turkish employment and wages. The large majority (85 percent) of Syrians have left the refugee camps and entered the Turkish labor market. 3 They are overwhelmingly employed informally, since they were not issued work permits. This makes their arrival a well-defined supply shock to informal labor, and a particularly good context in which to test the predictions of basic economic theory. We instrument for refugee flows using travel distance between 13 origin governorates in Syria and 26 Turkish subregions (338 origin-destination pairs). This allows us to also control for distance from the Syrian border, and thus any confounding factors that are correlated with proximity to Syria. Usage context: background mention, supporting mention, primary mention.

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Input:
Since 2006, Rwanda is divided into 30 districts, which are the main service-delivery units. All
household surveys are representative at the district level, but there is no information on districtlevel economic growth. Estimating district-level growth based on nightlights is however
complicated by the low intensity of lights: Four districts did not emit any observable lights at all
during 2000-2011, and ten districts only have nonzero observations towards the end of the 20002011 period. As a result, we can only estimate nighlights-based GDP growth for 16 districts.

Notes: Dependent variable is the natural log of GDP in constant LCU. All specifications include country and
year fixed effects. Robust standard errors clustered by countries in brackets. ***: significant at 1%-level; **:
significant at 5%-level; *: significant at 10%-level. Data source: NGDC (2014) and WDI (2014).

In Column (3) we replace lights observed from space by data on electrical power consumption (in kilowatt hours, obtained from the World Development Indicators). As data on electricity consumption are only available for 22 countries in SSA, the number of observations drops from 966 to 425 (not all 22 countries have data for all 21 years). We find a strong and statistically significant association between electricity consumption and GDP in the reduced sample (elasticity of _0.37_ ). The coefficient is however considerably smaller than the one estimated between night lights and GDP ( _0.58_ ). This may potentially be explained by the relatively high use

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Input: 15 4. 1. 2. Empirical strategy In order to make use of the retrospective information on school attendance provided in the dataset, we have constructed what we have called an ‘ ad hoc panel ’, whereby we exploit the time-variation of the variables of interests (age, attendance status and grade attained by the respondents) by reshaping the cross-sectional structure of the TLSS 2001 dataset. In this way, we are able to obtain observations for each individual over three academic years. All key education variables are time- variant, while other individuals and households characteristics are time-invariant. Within these three years, we focus our analysis on individuals that were of primary school age (between 7 and 12 years old) in each year. In practice, we keep all children aged at minimum 7 years old in 1998 and at maximum 12 years old in 2000. As a consequence, our panel data contains children aged 8-11 years in 1999, the year of the violence. 11 Since we are interested in looking at different effects across groups of individuals, we have split the sample between boys and girls and between younger children (aged 8-9 in 1999) and older children (aged 10-11 in 1999). Usage context: primary mention, background mention, supporting mention.

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Input: 27 Source: Listening to Displaced People Survey, 2014. 7. Conclusion The 2012 crisis in northern Mali led to widespread displacement. The welfare of the displaced – and those who returned – is monitored by combining a baseline survey with structured monthly follow-up interviews carried out by mobile phone. This innovative approach allows tracking changes in welfare with high frequency – even for those who returned to areas that are insecure and inaccessible to enumerators. After 6 rounds of follow-up interviews attrition rates are very low (more than 99 % response rate), demonstrating that it is possible to collect robust and representative data from hard-to-reach, conflict-affected populations. The results show that those who fled were better educated, better off and less affected by violence than the average population in the North. Those who fled lost significant amounts of durable goods (20-60 %) and livestock (50-90 %); many of their children ended up being taken out of school and their welfare (measured subjectively and by the number of meals consumed) declined considerably. Over time, the impact of the crisis on welfare has lessened and by February 2015 the majority of eligible children of the displaced were going to school and levels of employment and number of meals consumed were at pre-crisis levels.

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Input: 2 1. Introduction The most common sampling approach for cross-sectional household surveys in the developing world is a stratified two-stage design (Grosh and Munoz, 1996). Following stratification based on administrative boundaries, clusters are selected in the first stage with probability proportional to size from a national census-based frame. In the second stage, a canvassing operation is conducted in the selected clusters to compile an updated list from which households are randomly selected. While this methodology is straight forward to implement in the field and reliably produces unbiased estimates, there are several downsides. The first downside is cost. The World Bank ’ s Living Standards Measurement Study team, which provides technical assistance on large-scale household surveys around the world, estimates the field listing operation increases the overall budget for data collection by 25 percent. Due to confidentiality concerns, the data collected during a field listing operation, typically the name of the household head and address or location description of dwellings, does not have any analytical applications beyond as a component of the weight calculations. 2 At a time when typical survey costs are in the USD millions, reducing a significant cost component will increase the financial sustainability of data collection. The second drawback to the traditional design relates to timeliness. Usage context: background mention, primary mention, supporting 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

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

Armed Conflict Location and Events Dataset

conflict event data
geographically disaggregated data

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Input: prior to the pandemic, a period characterized by less distinct time trends in the labor market. Since the focus of the paper is on the impact of COVID on labor market stock and dynamics, we also restrict the sample of interest to include only prime-aged working adults (aged 20 to 59). The dataset contains standard variables expected of a labor force survey, including those denoting employment, unemployment, and inactivity. It also contains information on the intensive margin of the labor supply, including hours worked and full-time and part-time status. Information on employment sector, industry, contract status, health insurance coverage, and mode of work (distinguishing between employees and self-employed, for example) is also available, allowing us to construct indicators of formality and to differentiate different modes of employment. Information on occupation is also available, but only at the level of 2-digit ISCO-08 classification. This information is enough to distinguish between white- and blue-collar occupations but it is not enough to observe additional relevant pandemic-related job characteristics such as the degree of contact with the public. 3. 2 Descriptive statistics Figure (1) tracks the evolution of labor market stocks in the West Bank and Gaza respectively over time. Usage context: primary mention, supporting mention, background mention.

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Input: Beneficiary assessments completed during the project preparation phase established that the primary constraint to economic inclusion among the target population was lack of legal work authorization, cited by 74 percent of respondents, followed by limited language proficiency in the dominant national language (58 percent) and absence of recognized educational credentials (51 percent). These beneficiary assessments were conducted through a combination of individual household interviews and focus group discussions with community representatives, using a standardized protocol developed with the Ministry of Labor.

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Input: In households with more than two children, one child from each age group was chosen through a random selection process to participate, ensuring a broad representation of experiences within the study ’ s scope. Sampling frame. We use the 2018 population census data as a sampling frame for the Colombian sample. It allowed the identification of residential blocks and households with children in the desired age range. With this source of information, it was possible to identify the number of households and residential blocks with children and adoles- 7Although Colombia only grants nationality to children of Colombian nationals, it follows a jus sanguini principle, the Colombian government has introduced reforms, such as the the program Primero la Ni ˜ nez to give Colombian nationality to children of Venezuelan parents born at times when diplomatic relations between Colombia and Venezuela were cut and hence, it was not possible to apply for a Venezuelan nation- ality for this minors in Colombia. 15

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Input: 5 interviewed (i. e., on the premises when the enumerators began their interviews) were included in this survey. Enumerators selected households within the catchment area randomly. Among households with an age-eligible child present (i. e., 0-35 months or 36-72 months), enumerators explained the purpose of the study and invited the target child ’ s primary caregiver to be interviewed. Respondents were supported to withdraw their consent anytime during or after the interview and such cases were dropped from analyses. For children 0-35 months of age, assuming a minimum power level of. 8 and an alpha of. 05, the study design predetermined that the minimum desired detectable difference in average ECD Z- score measured by the Caregiver Reported Early Development Instrument (CREDI) was a 0. 2 standard deviation (SD) difference, which has been shown to be the average difference between urban and rural Pakistani children assessed using the CREDI (Hentschel et al., 2024). For children between 36 and 72 months of age, assuming a minimum power level of. 8 and an alpha of. 05, the study design predetermined that the minimum detectable difference in average ECD score (measured by the AIM-ECD score) is a 0. 23-point difference (the difference between males and females in Hentschel et al., 2024). Usage context: supporting mention, primary mention, background mention.

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Input:
**awareness sessions (90%), community networks (53%) protection analysis (44%). The** main gap remains
on specific strategies to mitigate impacts on **the safety, evacuation routes and well-being** .
 According to the survey findings, a significant majority of respondents (77%) indicated **that there are**

**currently no organizations**, institutions, agencies, or entities offering tailored and specialized activities or
services specifically designed for youth in northwest Syria.

 79% of the respondents believe some groups within youth are facing **disproportionate impacts** :

Young parents, the only segment of this
population groups with some level of access to
services and programs, was not identified by
respondents as one of the groups at heightened
risk. The attribution of 15% to **young people**

**belonging to minorities** is relevant finding,
considering that, it is a high percentage for a
small group. **IDPs** as the second group exposed
to higher impact represents a need to better
understand the specificities of the risks faced by
them; also, relevant to see that adolescent men
seem to face increased risks than adolescent
women. Absence of data on the particularities
of these risks faced by both genders limits the
accuracy of the programmatic response.

Those that belong to minorities

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Input:
**SOUTH SUDAN** | October 2023

#### **PROTECTION RISKS**

Persons with disabilities in South Sudan share a history of exclusion and are generally considered to be non-equal members of
society. Today, persons with disabilities still have few opportunities to improve their socioeconomic status, integrate into
society, or demand rights and recognition by society and the government, despite recognition of their rights under the
Transitional Constitution of South Sudan, 2011, as amended in Article 30. They continue to face significant social and political
exclusion and are among the most marginalized in society. Awareness of disability issues among key decision-makers and the
public is low, negative social attitudes and structural discrimination prevail, and persons with disabilities have limited access
to essential services and employment. [ix] According to a survey conducted by Ministry of Gender, Child, and Social Welfare in
2011, in Central Equatoria, Eastern Equatoria and Jonglei states, 89% of persons with disabilities are unemployed. [x]

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Input: Similarly, regional representation of the sample was found to be in line with actual regional distribution of the population in the north. 16 The code of the day is the sum of the two figures of the date, i. e. if it ’ s the 25th of August the code of the day is 2 + 5 = 7. The enumerater will chose house number 7 as a starting point. Arab 3 % Tamashek 32 % Songhai 45 % Peulh / Foulbe 7 % Other ethnicities 13 % Figure 2: Ethnic composition of the North, 2009 Census Arab 5 % Tamashek 36 % Songhai 49 % Peulh / Foul be 7 % Other ethnicities 3 % Figure 3: Ethnic composition of sample Usage context: background mention, supporting mention, primary mention.

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Input: List of acronyms CAR Central African Republic DHS Demographic and Health Surveys DRC Democratic Republic of Congo DTM Displacement Tracking Matrix FCS Fragile and Conflict-affected Situations GIDD Global Internal Displacement Database GIS Geographic Information Systems IASC Inter-Agency Standing Committee ICRC International Committee of the Red Cross IDMC Internal Displacement Monitoring Centre IDPs Internally Displaced Persons ILO IOM International Labour Organization International Organization for Migration IRRS International Recommendations for Refugee Statistics JIPs Joint IDP Profiling Service LSMS Living Standards Measurement Study MICS Multiple Indicator Cluster Surveys NGOs Non-Governmental Organizations NRC Norwegian Refugee Council OCHA Office for the Coordination of Humanitarian Affairs of the United Nations Secretariat OAU Organization of African Unity ODA Official Development Assistance OECD Organisation for Economic Co-operation and Development SDG Sustainable Development Goal SKOPE Somalia Knowledge for Operations and Political Economy SuTPs Syrians under Temporary Protection UAV Unmanned Aerial Vehicle UNDP United Nations Development Programme UNHCR United Nations High Commissioner for Refugees UNITAR United Nations Institute for Training and Research UNOSAT UNITAR ’ s Operational Satellite Applications Programme UNRWA United Nations Relief and Works Agency for Palestine Refugees in the Near East UNSD United Nations Statistical Commission WFP World Food Programme Usage context: supporting mention, primary mention, background mention.

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

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Input:
Data Sources: proGres v4 (PRIMES) hosts the data of refugees and asylum-seekers in 11 countries. In South Africa, the data are managed by the
government. In Angola, DRC, Zambia and Zimbabwe, some portions of the data are external. For IDP data, the source of DRC’s IDP figure is the OCHA;
the sources in Mozambique and Zimbabwe are the Displacement Tracking Matrix (DTM) of the IOM; and the source in the Republic of Congo is the
government, the Ministry of Social Affairs and Humanitarian Action (MASAH).

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

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Input: A UNESCO report written during the height of Liberia ’ s second civil war reported that Liberia had one of the lowest gender parity scores globally, and girls were disproportionately represented in the number of out-of-school children in Liberia. This disruption in education presaged lifelong consequences for this cohort of women (Kirk, 2003). In 2007, the literacy rate for adult men was 55 % and women was 41 %-- the number lowering to 26 % for rural women (OECD et al., 2009). In 2001 an education law was enacted making primary education free and compulsory, however, as of 2006, primary school enrollment in urban areas was 63. 7 % for girls and 33. 1 % for girls in urban areas (Woodon, 2012). Liberia also scores in the bottom eight countries that reported women having fewer than half of the years of education as men (Klugman, 2010). Five years after the war ended, women ’ s labor force participant was high, with women accounting for 54 % of the labor force. However, women were disproportionally represented in the informal sector (CWIQ, 2007). According to data from the 2017 Women, Peace, and Security Index, Liberia still has a number of gaps to fill particularly related to education, financial inclusion, legal discrimination and intimate partner violence (WPS, 2017). Usage context: supporting mention, background mention, primary mention.

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Input: using the Washington Group Short Set on Disability. 11 Sharing a home is common, likely as an economic coping mechanism, with on average of 1. 3 families living in the same house. Housing quality is low, with most houses in some state of disrepair or incomplete construction. Table 1 also illustrates descriptive statistics for the treatment versus control households to as- sess balance across groups, where the third column presents a mean difference test. Respondents across the study arms are largely balanced by age (with an average age of 34 years), marital status (84 % married), and incidence of a disability (Panel A). There is a slight imbalance in the share of respondents who are female, with the proportion slightly higher in the control group. Moreover, average household size is just above ﬁve members, with nearly three children on average, and these are balanced between treatment and control, as is the number of families per residential unit (Panel B). Refugee households in the sample face challenging and precarious housing conditions, but these characteristics are generally balanced across groups (Panel C). For example, only 66 % of households have access to piped water, 22 % have functional windows, and 44 % completed ﬂoors. Usage context: background mention, supporting mention, primary mention.

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Input: List of acronyms CAR Central African Republic DHS Demographic and Health Surveys DRC Democratic Republic of Congo DTM Displacement Tracking Matrix FCS Fragile and Conflict-affected Situations GIDD Global Internal Displacement Database GIS Geographic Information Systems IASC Inter-Agency Standing Committee ICRC International Committee of the Red Cross IDMC Internal Displacement Monitoring Centre IDPs Internally Displaced Persons ILO IOM International Labour Organization International Organization for Migration IRRS International Recommendations for Refugee Statistics JIPs Joint IDP Profiling Service LSMS Living Standards Measurement Study MICS Multiple Indicator Cluster Surveys NGOs Non-Governmental Organizations NRC Norwegian Refugee Council OCHA Office for the Coordination of Humanitarian Affairs of the United Nations Secretariat OAU Organization of African Unity ODA Official Development Assistance OECD Organisation for Economic Co-operation and Development SDG Sustainable Development Goal SKOPE Somalia Knowledge for Operations and Political Economy SuTPs Syrians under Temporary Protection UAV Unmanned Aerial Vehicle UNDP United Nations Development Programme UNHCR United Nations High Commissioner for Refugees UNITAR United Nations Institute for Training and Research UNOSAT UNITAR ’ s Operational Satellite Applications Programme UNRWA United Nations Relief and Works Agency for Palestine Refugees in the Near East UNSD United Nations Statistical Commission WFP World Food Programme Usage context: primary mention, background mention, supporting mention.

Global Internal Displacement Database
Demographic and Health Surveys
Geographic Information Systems
Multiple Indicator Cluster Surveys

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Input: These surveys are part of a long-term data collection effort by the research team (Vinck & Pham 2014) and were collected separately from the focus group discussions. The focus group discussions thus did not directly inﬂuence the design of the surveys, but rather directed the analysis strategy of the surveys that our team has collected at regular intervals in eastern DRC. The survey data are analyzed in two ways. First, 11 surveys collected between 2017 and 2021 8Eastern DRC is a site of ongoing violence, raising a number of ethical, methodological, and practical concerns about collecting data. We discuss the ethical protections we implemented when collecting this survey data in the Appendix, Section B. 9Territoires are sub-provincial administrative units. Additional details on the structure of administrative units are available in the Appendix, Section A. 1. 21

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Input: higher for refugees than hosts, both for in-camp and for out-of-camp refugees (Figure 5.9). While the food insecurity Refugee and host communities could differ in multiple dimensions over and above consumption. The Multidimensional Poverty Index (MPI) explores this multiple deprivation, capturing differences across three dimensions of well-being: health, education, and living standards (Alkire et al., 2021). MPI provides a general picture of the extent of deprivation. In this context, deprivation in education is assessed using school attendance for school-age children and years of schooling among adults. Health is proxied by the presence in the household of a stunted child or death of a child in the last 12 months before the survey. Living standards are assessed by access to electricity, improved water, sanitation, cooking fuel source, housing, and economic assets. The MPI ranges from 0 to 1, with 1 representing a high level of deprivation. It is the product of two partial indices: the headcount ratio (H) and the intensity of poverty (A) i.e. (MPI = H*A). The headcount ratio is the share of poor people in the population, while the intensity shows how much deprivation poor people experience on average. A cut-off point of 0.33 is used for the

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Input: Most papers with few exceptions use standard OLS estimators or some of its variants (Table 2). Two papers use general equilibrium models (Bodvarsson, Van den Berg, and Lewer 2008; Hercowitz and Yashiv 2002) and two papers simply compare means between treated and non-treated groups resulting in simple difference estimations (Card, 1990 and Alix-Garcia and Bartlett, 2015). [Table 2] The unit of observation varies depending on the data at hand. Most studies rely on household survey data where individuals or households are the unit of observations and most studies include some regional dimension (more frequently administrative areas). Where longitudinal or panel data are available time is also included. Other choices for unit of observations include skills or education level, various types of population groups (based on gender, age etc.), and, in a few cases, economic sectors, industry or labor market segments. The use of fixed effects varies. Some papers use the full set of parameters depicting units of observation (for example, household, region and time fixed effects in equations where the unit of observation is constructed using household, region and time). Other papers use subsets of these parameters whereas other papers introduce variables that are not used to identify the unit of observation. Usage context: primary mention, supporting mention, background mention.

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Input: In this sense, it is necessary to take into consideration that all indicators of prevalence of NSE and its profile will be limited to a subset of this kind of workers. 4. 1 Latin America and the Caribbean This section focuses on the Latin America and the Caribbean region, where a set of 9 countries, that we consider representing the different realities of the region in an exhaustive way, was analyzed. Specifically, the analysis was conducted for Argentina, Brazil, Bolivia, Chile, El Salvador, Mexico, Peru, Dominican Republic and Uruguay. 5O * NET is the successor of DOT (Dictionary of Occupational Titles) which is no longer updated. O * NET was launched in 1998 on the basis of the BLS Occupational Employment Statistics codes. In 2003, it was changed to SOC which implies that the consistent measures of task content are calculated from 2003. Usage context: supporting mention, background mention, primary mention.

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Input: 3 five methods, it was not possible to consider non-sampling error. This paper goes a step further by using simulations to describe the sampling error and a field experiment in an IDP camp in South Sudan to measure the total survey error of each design compared to a census, allowing for the disaggregation of the total error into sampling and non-sampling components. In addition, we attempt to separate the components of non-sampling error linked to the sample method from those common across all methods, such as interviewers selecting larger households and other issues in properly implementing the household survey protocols. The next section briefly describes each method and highlights the literature as it relates to the relevant selection methods. Section 3 describes the data set and protocols for each method included in the experiment, followed by Section 4, which discusses implementation issues. Section 5 reports the results of the analysis, and section 6 concludes with further discussion of the overall performance and areas for future research. 2. Description of Methods This paper compares five alternatives of second stage selection (satellite mapping, segmentation, grid squares, “ Qibla ” (or “ walk north ”) method, and random walk) to a human canvassing operation.

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Input: The SEIS income module collects data on four income sources: formal wage employment, self-employment net earnings, transfers from households in the country of origin, and humanitarian cash assistance. Households reporting income from all four sources are rare (fewer than 3 percent of the SEIS sample), and the total household income variable is dominated by humanitarian cash assistance in the early post-displacement period. As the length of stay increases, the SEIS data show a gradual shift from cash assistance dependency toward self-employment income, consistent with the livelihood integration trajectory documented in the qualitative literature.

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

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Input: percentage points less overall and 34 and 18 percentage points less in Eritrean and Somali camps, respectively. There is little benefit to working outside the camp to reduce aid reliance in South Sudanese households. On the other hand, years spent in Ethiopia are only associated with a gradual decrease in dependence on donations, with only a 1 percentage point reduction for every year spent in the country. The lack of employment outcomes contrasts with other refugee-hosting countries in East Africa, highlighting the lack of labor market access for Ethiopian refugees. Evidence suggests that refugees 0 5,000 10,000 15,000 20,000 25,000 Camp Hosts Camp Refugees Figure 3.19: Value of productive assets among households with non-farm business 0 0.05 0.1 0.15 0.2 0.25 Camp Hosts Camp Refugees Figure 3.18: Household has non-farm business Source: World Bank Staff based on SESRE 2023. Productive assets include the subset of assets with production value, such as farm tools and water pumps, sewing and building equipment, and commercial cars. Outliers are treated, and values are adjusted for inflation. 0 20 40 60 80 100 Camp Hosts Camp Refugees Current Camp Refugees COB Other (rental income, PSNP, pension) Remittances (local/international) Donations (NGO/gov) Crops/livestock Salary (employment/casual labor) 0

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Input:
The SIRRV question on road building clearly notes to exclude "rehabilitation." 10 Later, after discussing our estimation methods, we ascertain that this holds for almost all communes when we predict the counterfactual kilometers of rehabilitated roads in the absence of the project.

Additional corroborating evidence comes from available SIRRV data on other

(iii) ** and * indicate significance levels of 5 and 10%. (iv) Average commune household consumption is predicted using a consumption model calibrated to the 1998 VLSS.

The dataset for this analysis comes from an extensive economic survey involving over 9000
farmers in ten African countries: Burkina Faso, Cameroon, Egypt, Ethiopia, Ghana, Kenya,
Niger, Senegal, South Africa and Zambia. Data was gathered from Zimbabwe but the livestock
observations had to be dropped because of the turbulent conditions in this country during the
survey period. The data was collected for the GEF project studying the impact of climate change

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

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Input: 20 between 1948 and 1965, with increases in the percentage of adults with religious education in the cohorts born after this date. There is also wide geographical dispersion in the prevalence of madrassa education in Pakistan. Although all districts report that less than 2. 5 percent of children in the relevant age group (children between the ages of 5 and 19) are going to madrassas, the Pashto speaking belt that borders Afghanistan stands out in terms of the popularity of madrassas as an educational choice. The notion that the madrassa movement coincided with resistance to the Soviet invasion of Afghanistan is supported by the 1998 data from the population census. The increase in the stock of religiously educated individuals starts with the cohort that came of age in 1979 (the year of the Soviet invasion of Afghanistan) and the largest increase is for the cohort co-terminus with the rise of the Taliban. Combined with the fact that the largest enrollment percentage in Pakistan is in the Pashtun belt bordering Afghanistan, this suggests events in neighboring Afghanistan influence madrassa enrollment. Is there something intrinsic about Pashtun sensibility or tribal culture that leads to higher madrassa enrollment? The differentiation of the Pashtun and non-Pashtun districts does not extend to Pashtun and non-Pashtun households in the LEAPS data. Usage context: primary mention, supporting mention, background mention.

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Input: If many people migrate to a speciﬁc location, such as the capital city, this is likely to aﬀect wages, incomes, and access to amenities in that location. 7 This would generate a potential endogeneity bias due to the fact that incomes and amenities in that location result in part from the decision of many migrants to locate there. To eliminate this bias, we use past data to estimate the income regression. More precisely, let T be the period for which we have income information and T + t the period at which we 5The dropped observation corresponds to the location of origin M h ii which, as explained earlier, we do not include in the analysis since including M h ii would mean de facto including the decision of whether to migrate or not. 6McFadden (1974) has shown that, in multiple choice problems of the kind studied here, the application of logit estimation is justiﬁed if (1) the errors in each latent choice equation follow the extreme value distribution and (2) errors are independent across choices. See Train (2003), Chapter 3 for a detailed discussion. The estimation of models with correlated errors across choices requires either multiple integration or the use of Bayesian estimation techniques relying on Gibbs sampling. With a choice of over 70 possible destinations, multiple integration is out of the question. Gibbs sampling remains a possibility but would require extensive programming. We choose instead to keep the logit approach but to correct the standard errors for possible correlation in errors across choices. In our case the possible eﬃciency gain achieved by Bayesian methods does not appear to justify the programming cost. 7The eﬀect could be negative — e. g., congestion — or positive — e. g., agglomeration externalities. 10 Usage context: background mention, supporting mention, primary mention.

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Input:
ASPIRE does not cover all countries in the world. To expand the set of countries in this study, we proceed as follows. First, we estimate an econometric model that explains the share of income from transfers, for poor and nonpoor people in each country by the share of GDP spent on social protection at the national level (from the International Labour Organization), an indicator of government effectiveness (from the Worldwide Governance Indicators), and whether the country used to be in the Soviet Union. (Other explanatory variables we tested include World Bank income category of the country, region, and GINI coefficient, but they turn out to have no explanatory power.) This provides an estimate of income from transfers in 26 additional countries (from 98 using only ASPIRE data).

Diversification also comes from financial inclusion. We use the fraction of the population with savings at a financial institution, from the Global Financial Inclusion Database (FINDEX, 2015). The Findex database provides these values for the bottom 40% and for the top 60%, which we use for poor and nonpoor people respectively. We assume that the fraction of income that is diversified increases by 10% for people who have bank accounts.

Rather, we proxy the ability of a country to borrow with sovereign credit rating, using the average (long-term) rating of from three agencies: S&P, Moody's and Fitch.

Our study takes advantage of newly available panel data from the Indian Human Development Survey (IHDS), which includes a question asking households to estimate the daily average duration of outages.

Worldwide Governance Indicators
Global Financial Inclusion Database
Indian Human Development Survey (IHDS)
ASPIRE data
Findex database

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Input:
- Promote meaningful participation of persons with disabilities in humanitarian action, seek advice and collaborate with
national and local organizations of persons with disabilities in coordination structures and build their capacities.

- Prioritize the integration of disability inclusion and Mental Health and Psychosocial Support (MHPSS) services into the
overarching humanitarian response framework. This involves incorporating MHPSS elements into needs assessments and
program planning.

- Encourage the recruitment of persons with disabilities as staff at all levels of humanitarian organizations, including as
front-line workers and community mobilizers.

- Enhance age, gender and disability disaggregated data collection and analysis to develop risk mitigating measures and
appropriate indicators and use them to monitor the inclusion of persons with disabilities in all phases of humanitarian
action. When possible, collect data and information on the risks, barriers and needs of persons with disabilities,
particularly in remote regions that are difficult to access.

- Address the attitudinal and other barriers within the humanitarian community and perceptions of disability as an
‘additional complexity’ in an already complex context, and include it from the onset as part of human diversity.

#### RISK 2 Gender-based violence

**PROTECTION SECTOR AND PARTNERS**

age, gender and disability disaggregated data

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

UNHCR Statistical Online Population Database

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Input: The 2024 survey data revealed that 62 percent of enrolled cooperatives had adopted at least one new post-harvest management practice introduced during the training-of-trainers workshops conducted in Year 1. Among cooperatives that adopted improved storage techniques, average post-harvest losses declined from an estimated 28 percent of harvested output to 14 percent, representing an annualized value retention gain of approximately USD 340 per metric ton of stored produce. These findings will be used to calibrate the economic rate of return estimates in the project's completion report.

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: 36 7. Conclusions To make progress in promoting equality and improving the living standards of the population in Uganda, it is necessary to understand the effect of Uganda ’ s fiscal policy on inequality and poverty. This report uses the internationally comparable CEQ methodology to assess the individual and combined effects of taxes and public social spending, based on the microdata from the UNHS 2016 / 17 household survey. The main objective is to provide considerations for policy makers in terms of which fiscal instruments or, more specifically, which mix of fiscal instruments can contribute to reduce poverty and inequality. Overall, our results show that Uganda ’ s fiscal system is modestly equalizing. As a whole, taxes and transfers in 2016 / 17 reduced inequality by approximately 3. 23 Gini points. This result is comparable to Ghana, moderately lower than in Kenya and Tanzania, and much lower than the result observed for South Africa. The largest contributive factor to this equalizing effect is direct taxation (personal income tax or PAYE), followed by the education in-kind transfers (net transfers). This is not surprising, given the size of these fiscal interventions as a proportion of pre-fiscal income and their progressiveness. Direct transfers and social protection programs more generally contribute to the redistributive effect and are simulated as highly concentrated among the poorest households. Usage context: primary mention, background mention, supporting mention.

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Input:
Nevertheless, we believe that this analysis provides suggestive   13As mentioned earlier, this is per capita income for the three months prior to the ENIGH survey.

CADENA now offers weather index insurance   for a variety of perils (e.g., drought, flood, hail), as well as area-based yield index insurance, which   2Subsidies from the federal government depend on the marginality index of the insured municipality, as computed by CONAPO.

Note. The data used to created this table comes from the 2010 census. % Illiterate is defined as the number of
illiterate individuals over the age of 15 divide by the total population over 15.

**Karlan,** **Dean,** **Robert** **Osei,** **Isaac** **Osei-Akoto,** **and** **Christopher** **Udry**, "Agricultural

Decisions after Relaxing Credit and Risk Constraints," _Quarterly_ _Journal_ _of_ _Economics_, 2014,

In addition, this study computes environmental risks at the commune level [2] to relate it to household information based on the Vietnam Household Living Standard Surveys (VHLSS) for 2010, 2012, and 2014. Benefiting from the panel

Vietnam Household Living Standard Surveys (VHLSS)

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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.

national identification documents
population register

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Input: refugees’ social integration (ReDSS, 2018). Box 7.1: Socio-political tensions in the Gambella Region Figure 7.3: Host response to “Refugees are good people” by gender Source: World Bank Staff based on SESRE 2023. Figure 7.4: Host response to “Would you feel comfortable having a refugee as a neighbor?” by gender Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 90 100 Male Female Male Female Male Female Male Female Eritrean Somali South Sudanese Addis Ababa Strongly agree Agree Disagree Strongly disagree Percent Markets and Opportunities 66 Most hosts do not think they have experienced adverse effects from refugees. However, a sizeable minority are concerned about the effects on employment, inflation, security, and deforestation in their communities, with significant differences across domains. The most consistent perceived effects are economic competition and price increases. Across domains, 29 to 39 percent of hosts think they have experienced either wage or employment competition due to refugees.50 Beliefs that refugees have increased prices are especially prevalent in the Eritrea and Addis Ababa domains (70 and 81 percent, respectively), possibly reflecting concerns over housing costs in Addis Ababa. Other studies have shed light on this phenomenon in more detail.

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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.

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Input:
weather policy, this is deemed a rainfall shock. As the quality of the rainfall data is related to the

11The APHRODITE weather data provides information about how many local weatherstations contributed to a
certain rainfall reading. Since some of the rainfall observations are likely to be more accurate than others, I weight
them according to accuracy. If there are no rainfall stations contributing to the APHRODITE data within a .75 _[o]_ x.75 _[o]_

When the regressions are run with the village characteristics from the 2005 Indian census, the coefficients of interest do not change significantly. Also, most village-level characteristics had insignificant coefficients, with the exception that a more literate population

While the BASIX data set does not offer the opportunity to test the direct effects of a cash payment

Robust standard errors in parentheses Obervations weighted by quality of rainfall data

APHRODITE weather data
2005 Indian census
BASIX data set

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Input: the West Bank and Gaza. Out of all the estimated coefficients for each period for both outcomes (job loss and job gain), we only find a negative effect on job gain in 2019Q4, which is very small in magnitude (1 percentage point). Taken altogether, the results presented in this section bolster our confidence that we are correctly identifying the effects of the pandemic shock on labor market outcomes. Figure 12: Placebo effect on labor market flows Notes: The figure shows the output of a placebo test with a set-up analogous to Figures 6 and 9. We perform the same regression as specified in Equation (2). Our sample includes data from 2018Q2 to 2020Q1 and assumes that the pandemic started in 2019Q2. Therefore, the post-pandemic period refers to the quarters between 2019Q2 to 2020Q1. The analysis is restricted to men aged 20-59. 7 Conclusion This paper examines the effect of the pandemic on labor markets in the West Bank and Gaza using quarterly labor market data provided by national labor force surveys. With a focus on men ’ s labor market outcomes, this paper sheds light on how labor markets in the West Bank and Gaza adjusted to the COVID-19 shock examining adjustments at the extensive (employment) and intensive (hours of work) margins. Usage context: supporting mention, primary mention, background mention.

national labor force surveys
quarterly labor market data

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Input: their earnings on household expenses than men. Most of these studies have focused on adult women, specifically married women with children. It is not known whether the same holds true for young women, who may have other spending priorities, have less experience in managing households, and have younger children. Given the large increases in employment and earnings documented above, the EPAG program serves as a good setting to examine these types of spillovers. The evaluation included detailed interviews with the heads of the household in which EPAG participants were residing. The purpose of the household questionnaires was precisely to examine the hypothesis that investing in young girls would benefit her household. A secondary hypothesis was that EPAG participation may change gender-related attitudes in the participants ’ households. Household data was collected for 1601 out of the 1622 individuals who were interviewed at both baseline and midline; this same sample of 1601 individuals serves as the basis for both the individual and household level analysis in this paper. The estimated impact of the program on a broad range of household outcomes is summarized in Tables 8 and 9. Panel A of Table 8 examines the household size.

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Input:
The final steps consist of setting a threshold for when a stream flow is strong enough  to flood the basin and then weighting this with the nightlight data and aggregating up to a  district level.  5  <!-- PAGE 8 --> The earthquake index is constructed from computer generated contour maps by the US  Geological Survey (USGS) of earthquake intensity data, commonly used as potential dam age proxy (De Groeve _et_ _al._, 2008; GeoHazards International and United Nations Centre  for Regional Development, 2001; Federal Emergency Management Agency, 2006).

The  data are then combined with the nightlight data and aggregated up to district level.  Finally, the 2004 Christmas tsunami has been modeled following a method where Heger  (2016) uses inundation maps to construct a district level damage index assuming uniform  6  <!-- PAGE 9 --> damage across all flooded areas.

aggregation of the disaster indices in the main paper. To weight the indices, nightlight data  are used as a proxy for economic activity.  **A.1** **Flood** **Index**  The flood index is made from stream flow modeled in GeoSFM, a software that uses remotely  sensed data as inputs, which are weather and soil and terrain based.

the contour maps as a base for damage infliction, we combine them with the nightlight and  building type data from the USGS building inventory for earthquake assessment to create  fragility curves by building type; see Jaiswal & Wald (2008) and GeoHazards International  and United Nations Centre for Regional Development (2001).

nightlight data
earthquake intensity data

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Input: IDMC reports that of the 52 countries it monitored in 2015, it was only able to obtain data on new displacements in 20 countries, 92 on returns in 20 countries, on integration in one country, on resettlement in two countries, on children born in displacement in two countries and on deaths in one country; no data was obtained for any county on cross-border flight in 2015 (IDMC 2016). Moreover, existing systems for collecting data on refugees and asylum-seekers make it difficult to know how many were formerly IDPs, and it is possible for some people to be simultaneously counted in both categories, e. g. in the case of the Syrian displacement crisis (IDMC 2016). If no data on returns are available, IDMC risks overstating the number of IDPs (IDMC 2015).

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