Input: food item per month and cash transfers per person per month for each camp and period. The food items include cereal, wheat, maize, rice, sorghum, CSB/famex (CSB+), pulse, biscuit, date biscuit, dates, oil, vegetable oil, salt, and cash (Table E.4). We have computed the per person per month in-kind aid quantities into annual values using the household size and prices from SESRE and mapped them to the closest food item in SESRE (this was not straightforward as the items are different) considering food ration change periods. The food ration scaling factor is 50 percent vs. 84 percent. Based on this information, we compare how the distribution list shared what refugees should have received to what they reported regarding food consumption. The results show that refugees reported quantities lower than UNHCR food aid admin data for every item except Biscuits. Refugee households still report lower quantities, even correcting for shares indicated as sold. Annexes 125 Table E.2: Food aid and consumption comparisons Items Quantity (per capita/year) Expenditure (per capita/year) SESRE UNHCR SESRE UNHCR Nonzero All Net of sold ration* Cereals/other cereals 23.2 186.1 175.5 493 12404 Wheat 60.5 133.2 116.6 1427 4710 Maize 39.6 125.5 118.3 312 4267 Rice 21.3 48.5

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Input:
Climate data on temperature and precipitation were taken from Bitan and Rubin (2000). Average annual temperature calculations are based on data collected in 38

Table 3 presents the results of the two models. In the first model, linking farm profits to

farm exogenous variables, the irrigation water quota was omitted. The second model in

and 2 percent for flowers and other garden plants (Israeli Central Bureau of Statistics, 2005). Almost all the crops excluding field crops are irrigated. Field crops are grown on

_Source: World Bank calculations based on Ministry of Energy and Mineral Resources 2007 data._

(2007), reports that from a survey of 51 countries, nearly half had an ad hoc pricing mechanism where the government adjusted the price level irregularly, 14 percent an automatic adjusting mechanism that holds the margin between world and local prices constant while allowing domestic prices to adjust, and 37 percent enjoyed a liberalized pricing system.

Ministry of Energy and Mineral Resources 2007 data

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Input:
and more immediate impact on food access, we are able to find additional empirical support

for the last explanation. Given data and information constraints, it is not possible to estimate

Sundberg, R., and E. Melander. 2013. "Introducing the UCDP Georeferenced Event Dataset."

Notes: This table compares mobile phone ownership in the November 2017 WFP mobile phone survey and the 2014 Household Budget Survey (HBS), where the 2014 HBS summary statistics are restricted to the share of the population that resides in a household that owns at least one mobile phone.

We gratefully thank Claudio Montenegro, David Newhouse and Minh Nguyen for their help with the I2D2 database. We gratefully acknowledge the generous support of the World Bank (Office of the Senior Vice-President and Chief Economist and Social Urban Rural and Resilience Global Practice), the Cities Program of the International Growth Center (Grant number 89408), the GWU Institute for International Economic Policy and the GWU Center for International Business Education and Research.

Data Used to Estimate the Returns**   **Sources.** The data source for the analysis is the _International_ _Income_ _Distribution_   _Database_ (I2D2) of the World Bank. The database consists of a large number of   individual-level surveys and census samples.

UCDP Georeferenced Event Dataset
2014 Household Budget Survey
I2D2 database

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Input: 6 3. Data Sources and Methods 3. 1. Administrative data on educational outcomes in Italy Two administrative data sources represent the backbone of this paper. These are the administrative data obtained from the Ministry of Education (MoE) for academic years 2021-22, 2022-23 and 2023- 24, and standardized test score data from the Italian National Institute for the Evaluation of the Educational System (INVALSI) for the 2022-2023 academic year. These datasets offer valuable insights into the educational outcomes of students in Italy, including Ukrainian refugees who entered the Italian school system following the invasion in 2022. Deϐinitions. In both datasets, students are categorized into ϐive demographic groups based on their nationality and timing of entry into the Italian educational system. These groups are Italian students, Ukrainian refugee students, non-refugee Ukrainian students, newly arrived foreign students, and other foreign students. Among Ukrainian students, the distinction between refugees and non- refugees is based on their enrollment date in the Italian education system. Ukrainian refugees are deϐined as Ukrainian students who enrolled in Italian schools after February 2022. In this paper, Ukrainian refugees are labeled “ Ukr post-Feb 2022 “, while non-refugee Ukrainians are labeled “ Ukr pre-Feb 2022 “. Usage context: background mention, primary mention, supporting mention.

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Input: 35 Inputs: 1. Household Survey with consumption or income welfare aggregates 2. Project data / Other survey data without welfare aggregates 3. Set of harmonized common variables in both surveys Outputs: 1. Set of imputed welfare variables for project data / other survey for each household in the data 2. Imputed welfare variables can be used for poverty, distributional analysis (quintiles or more), profiling of the poor or group of interest Models: 1. Ordinary Least Squares (OLS) 2. Probit 3. Multiple Imputation (MI) Table 18. Model Specification Variables Demographic Share of children, share of adults, share of adults squared and share of old (omitted) Characteristics of head Age, gender, and level of education Interactions with urban dummy variable Level of education of the head, age of the head Geography Dummies for regions at NUTS 1 level (12 regions) Interactions with Geography Level of education of the head, age of the head interacted with regions at NUTS 1 level (12 regions) and urban-rural division 1. Validation and Robustness Check Figure 7.

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Input: which increases signiﬁcantly under both treatment arms. In other words, the psychosocial value to employment appears to be driven largely by the non-pecuniary dimensions of the employment experience. 5. 4 Impacts of employment on reported physical health, cognitive function, and economic decision-making The positive eﬀects of employment extend to other measures beyond psychosocial health. Table 3 presents results on reported physical health, cognitive function, and incentivized measures of risk and time preference. We observe a signiﬁcant increase in the days reported healthy. This eﬀect may be due to ‘ real ’ health improvements from increased exercise (which has also been documented to translate to improved mental health (Herbert et al. (2020))) from the employment task or ‘ perceived ’ health improvements in which improved psychoso- cial well-being translates into feeling less physically ill. Should the channel be exercise, we may expect health improvements to grow over time. Our weekly data on days healthy sug- gests this is not the case: we observe the treatment eﬀect on health from the ﬁrst week of working, and the gap remains steady throughout the following two months (Appendix Figure A3).

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Input:
**Annex 2: Project Cost by Component and Expenditure Category**

| Component | IDA (USD M) | Govt (USD M) | Total (USD M) |
|---|---|---|---|
| 1. Livelihoods and Social Protection | 18.5 | 2.0 | 20.5 |
| 2. Infrastructure and Service Delivery | 24.0 | 3.5 | 27.5 |
| 3. Institutional Strengthening | 4.0 | 0.5 | 4.5 |
| 4. Project Management and M&E | 3.5 | 0.0 | 3.5 |
| **Total** | **50.0** | **6.0** | **56.0** |

Project management costs include operation of the PIU, SIGAF licensing and maintenance fees, and the annual external audit. M&E costs cover baseline and endline surveys, the MIS and activity monitoring dashboard platform, and supervision of protection monitoring activities.

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Input: However, permit-holding status is neither sufficient for, nor necessary to, working in Israel. As of 2019Q4, just under a fifth of West Bank residents had the right to work in Israel and the occupied territories, but almost a quarter among them were not commuting across the border for work. The vast majority of such individuals are holders of Israeli or Jerusalem IDs. Conversely, among those who do commute to Israel and occupied territories, 17 % do not hold valid permits or IDs. Likewise, permit-holding status does not logically affect the formality status of the commuter. The frequent border crossings between the West 2This is derived from authors ’ own calculations using the 2016 Jordan Labor Market Panel Survey. 3It is worth noting that the LFS is representative of the residents of the West Bank and Gaza, whose work may not lie in the country. 6

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Input: displacees in their communities, the survey asked an additional question in which respondents re- ported whether their communities hosted IDPs (displaced persons from within DRC) or refugees (displaced persons from Burundi, Rwanda, Uganda, South Sudan, or other countries). These re- sponses are used to create a categorical variable that measures whether respondents report hosting IDPs, hosting refugees, or not hosting displaced persons in their communities. Table 3 summarizes the measurement strategies for hosting status. It is possible that respondents may misreport whether they are displaced or whether displaced people are present for a number of reasons. First, they might not know that displaced persons are present, a risk that is especially acute for IDPs. Because the paper is primarily interested in how knowledge of hosting impacts perceptions of social cohesion, this measurement challenge is not as acute a problem as it may at ﬁrst seem. Respondents must know that IDPs or refugees are present in their community for hosting to impact their perceptions of social cohesion. If they are not aware of the presence of IDPs or refugees, their presence is unlikely to systematically impact their perceptions. Second, there might be incentives to either hide or, alternatively, to over-claim the presence of IDPs or refugees. Usage context: background mention, supporting mention, primary mention.

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Input: The GLSS follows a multi-stage stratified cluster design with 580 enumeration areas selected in proportion to population size. Within each GLSS cluster, 20 households are systematically selected using a random start. The GLSS sample is designed to be representative at the regional level and for urban/rural disaggregation within each region. Analytical weights supplied with the GLSS public-use file must be applied to produce nationally representative estimates; unweighted analyses will produce biased results due to differential sampling rates across strata.

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Input: by the migration episode. These include the minors age and sex, the parent ’ s and grand- parent ’ s education pre-migration, and a wealth index constructed with retrospective in- formation on the household conditions pre-migration. 14 Grandparent ’ s education is used a proxy for living standards that is unaffected by the migration episode from Venezuela to Colombia and the Venezuelan crisis, which intensified in 2016. ϵij depict the standard errors clustered at the household level to correct for intra-household correlation. For robustness, we will present the estimates of equation 1 with and without controls. As further robustness, we use propensity-score weights (Hirano and Imbens 2001, Hirano, Imbens and Ridder 2003). 15 V. A Physical development: Body Mass Index and health status In our study, we examine disparities in nutritional and health status among Colombian and Venezuelan children aged 5 to 10 years, focusing on standardized body mass index (BMI), instances of overweight and underweight, and overall health status. The BMI serves as an indicator of nutritional status for both adults and children, calculated as an individual ’ s weight in kilograms divided by their height in meters squared, according to World Health Organization (WHO) guidelines. Usage context: background mention, supporting mention, primary mention.

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Input: 2 International migration — the movement of people across national borders — has important economic, social, and political implications. Despite the recent emergence of a dynamic literature, empirical analysis of migration flows and their impact lags behind the policy debate and the theoretical literature. The main reason is the absence of comprehensive and reliable data on international migration patterns and migrant characteristics at either the aggregate or the household level. The objective of this article is to use data from more than one thousand national censuses and population registers to estimate a complete global origin – destination migration matrix for each decade over 1960 – 2000. These 226 * 226 matrices, comprising every country, major territory, and dependency around the world, are divided into periods corresponding to the last five completed census rounds. The gender dimension of international migration over this period is also presented. The primary source of the raw data is the United Nations Population Division ‘ s Global Migration Database, created through the collaboration of the United Nations Population Division, the United Nations Statistics Division, the World Bank, and the University of Sussex (United Nations [2008]). This unique data repository comprises 3, 500 individual census and population register records1 for more than 230 destination countries and territories over the last five decades. Usage context: background mention, supporting mention, primary mention.

national censuses and population registers

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Input:
In short, these contour maps are ShakeMaps from USGS, which are automatically generated maps providing several key parameters following an earthquake, such as peak ground acceleration (PGA), peak ground velocity (PGV) and modified Mercalli intensity (MMI), are used as a base for localized impact.

For the actual construction of the damage index, two types of data will be used; the intensity data - expressed as PGA - and building inventory data. The building type data stems from the USGS building inventory for earthquake assessment, which provides estimates of the proportions (based on total number of buildings) of building types observed by country; see

\n<!-- PAGE 17 -->\nJaiswal and Wald (2008). The data provide the share of 99 different building types within a country separately for urban and rural areas. For Indonesia the building type information was compiled from a World Housing Encyclopedia (WHE) survey.

Damage curves by building type are derived from the curves constructed by the Global Earthquake Safety Initiative (GESI) project; see (International and Regional Development 2001).

The source for the localized wind speeds is the IBTrACS database that provides the strength and tracks every 6 hours of all typhoons that affected Southeast Asia during the period.

ShakeMaps from USGS
World Housing Encyclopedia (WHE) survey
IBTrACS database

USGS building inventory for earthquake assessment

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Input:
The surveys were conducted
each year between May and November of the survey year, with expenditures referring to the past
12 months.

Real total per capita expenditure less per capita expenses on health care is taken as the
dependent variable.

In particular, using the historical daily rainfall records over 1980-2006 in 166 geo-referenced weather stations from across Vietnam (see Figure 1) [9], monthly rainfall grids of 0.1 degree resolution are constructed [10] using both inverse distance weighting (IDW) and inverse elevation difference weighting (IEW).

To also capture riverine floods, which may occur downstream following heavy rainfall in the mountains or as a result of storm surges in coastal areas, riverine flood indicators will be constructed based on the satellite based flood data from the Dartmouth Flood Observatory (DFO) (2008). The 1980-2006 geo- referenced UNEP/GRID-Europe storm track dataset is used to separately explore the effects from high winds and gusts from cyclones. As the damage from heavy rainfall associated with cyclones will already be captured by the localized and riverine flood indicators, these measures will capture the wind damage associated with cyclones. [5]

Tropical storms approach Vietnam from the east. They typically arrive during the Southeast and Northeast monsoon (Christiaensen et al., 2009), with 90 percent of them occurring between June and November, and almost half of them coming ashore in the northern part of the country. To generate annual cyclone maps, a GIS dataset of areas affected by hurricane force winds was developed from the UNEP/GRID-Europe (2007a, 2007b) tropical cyclones databases. In particular, the storm track and wind speed data were used to create symmetric polygons about each path, based on the algorithm by Klotzbach and Gray (no date). [21]

4 The frequently used CRU TS2.1 monthly rainfall database (Mitchell and Jones, 2005) only has a half degree resolution, which is around 55 kilometres at the equator. 5 See Thomas (2009) for a detailed description of the different data sources and a more elaborate description of the construction of the different natural hazard maps. 6 The nearest neighbour method assigns the value of the weather station nearest to the grid cell centre. 7 Radial basis functions are functions of distance used for exact interpolation of point data.

satellite based flood data from the Dartmouth Flood Observatory (DFO)

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Input: Our research complements and extends the findings of Demirci, Foster and Kirdar (2022), who investigated health and nutrition disparities between native children and Syrian refugee children aged 0 to 5 years in T ¨ urkiye, using data from the Demographic and Health Survey. The authors document find no significant differences in infant or child mortality rates between refugee children born in T ¨ urkiye and their native counterparts, it did reveal that refugee infants have lower birth weights and age-adjusted weights and heights compared to native infants. Our work broadens the scope of analysis beyond anthropometric indicators to encompass a holistic assessment of child development. By incorporating measures of physical, cognitive, socio-emotional, and mental health devel- opment, along with factors such as food security, time use, risky behaviors, and social integration, we offer a more comprehensive understanding of the developmental chal- lenges faced by displaced minors. Additionally, our study includes a wider age range, 5Chiovelli et al. (2021) examine the effects of forced displacement on separated sibling in the long-term. 8 Usage context: background mention, primary mention, supporting mention.

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Input: 10 Figure 3: Level of education age 25 +; compared with regional average (%) (*) INSTAT refers to census 2009 Source: Listening to Displaced People Survey, 2014. With regards to ownership of consumer durables, IDPs, refugees and returnees were better endowed than the average citizen of the North (see Figure 4). As was the case for education, they are more comparable to the average citizen in Bamako than to the average citizen in the regions of Gao, Timbuktu and Kidal. Figure 4: Asset ownership compared with regional average Source: Listening to Displaced People Survey, 2014 and EMOP 2011 (INSTAT). The main occupation of IDPs, refugees and returnees before the crisis was commerce (Table 5). This held for over half of the IDPs, 37 % of refugees and 34 % of returnees. 18 % of the refugees 51 85 60 47 85 89 87 15 6 18 29 11 8 8 34 9 22 25 5 3 5 IDPs Refugees Returnees Bamako (INSTAT) Gao (INSTAT) Timbuktu (INSTAT) Kidal (INSTAT) Secondary or Higher Primary None 0 100 200 300 400 500 600 IDPs Refugees Returnees Bamako (Instat) Gao (Instat) Timbuktu (Instat) Kidal (Instat) Percentage Mobile Phone Car / Motorized Vehicle Motorbike / scooter Bicycle Refridgerator TV CD Usage context: primary mention, supporting mention, background mention.

Displaced People Survey
Listening to Displaced People Survey

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

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Input: Language barriers, mental health challenges, and uncertain futures are identified as major obstacles to integration. The study highlights the importance of tailored interventions, such as psychological support and more dedicated teaching time, to foster refugee students ’ academic and social inclusion. This paper is a product of the Development Data Group, Development Economics and the Social Protection and Labor Global Department. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http: / / www. worldbank. org / prwp. The authors may be contacted at michela_carlana @ hks. harvard. edu; pcastaing @ worldbank. org; mtestaverde @ worldbank. org; and mtiberti @ worldbank. org.

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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.

national labor force surveys
quarterly labor market data

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Input:
As with the earlier two matching estimations, we matched the children within each DHS year.

This is around 7, 6, and 5 percentage points for the 2007, 2011, and 2014 DHS, respectively.

"The Effect of Water and Sanitation on Child Health: Evidence from the Demographic and Health Surveys 1986-2007.

16 According to the Joint Monitoring Programme (JMP), an improved sanitation facility is defined as "one that hygienically separates human excreta from human contact.

" The JMP considers the following categories as improved sanitation: flush to piped sewer system, flush to septic tank, flush to pit (latrine), flush to unknown place, ventilated improved pit latrine, pit latrine with slab, and composting toilet.

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Input: also face high turnover of teachers as they take on better-paid jobs (UNHCR, 2017). Secondary education, on the other hand, is provided for refugees in camp-based refugee schools and in government administered public schools, with support from UNHCR’s NGO partner (Development and Inter-Church Aid Commission, DICAC). This relies on qualified national teachers exclusively. UNHCR and partners are working towards progressive transfer of secondary school administration from DICAC to Regional Education Bureaus. The MoE is responsible for managing refugee and national education for higher education. However, enrollment of refugees in higher institutions is low due to low absorption capacity of higher education institutions (UNHCR, 2020a). At the same time, the Ministry of Skills and Labor (MoLS) is responsible for managing Technical and Vocational Education and Training (TVET). OCP refugees receive education at the same levels as nationals through the national education system. Refugee education data is integrated into the MoE’s Education Management Information System (EMIS) (UNHCR, 2020), and a separate chapter on refugee education is included in the annual education statistics report of the MoE. The GoE included expanding primary and secondary education for refugees in the national five-year Education Sector Development Programme VI (ESDP), covering 2020 to 2025, but little

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Input:
The data for this paper come from the European Social Survey (ESS) for the survey years 2002,

observations per country/year. The ESS covers 36 countries, 24 of which are included in our

Card et al (2012) investigates the drivers of attitudes towards immigrants in Europe using,

among others, the following variables of the ESS:

European Social Survey (ESS)
ESS
European Social Survey

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

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Input: followed the same standards and procedures as the HoWStat. SESRE data was not collected alongside HoWStat due to security concerns at the time of data collection for HoWStat, especially in the refugee areas. The SESRE aimed to solve two problems: (i) gaps in data on the socioeconomic dimensions of refugees, and (ii) gaps in analytical studies presenting the socioeconomic outcomes of refugees and hosts. Lack of up-to-date evidence is a significant obstacle to designing effective policies and support for refugees and host communities. To this end, the availability of the data helps to analyze refugee hosting areas’ social dynamics and longer-term socioeconomic viability by focusing on the: (i) social impact of refugees on host communities, (ii) socioeconomic interaction, (iii) social inclusion, and (iv) social relations among refugees and between refugees and host communities. The data provides valuable information to development partners and governments to inform policies to facilitate refugees’ integration and improve their lives, along with refugee hosting communities. The SESRE covers all current major refugee camps: Eritreans, South Sudanese, and Somalis, as well as the out-of-camp refugees in Addis Ababa. In addition, the survey covers the respective host communities around the camps, including the host communities of Addis Ababa.

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Input:
Responding to the evolving situation, in line with the Return SOP endorsed by the
Humanitarian Country Team (HCT) in February 2012, but also in accordance with the
“Return Policy Framework for IDP from FATA” endorsed by the FATA authorities in 2010, the
Protection Cluster agreed to conduct a series of consultations with the Shalozan Tangi
population to capture their intentions and position vis-à-vis the return process.

**II.** **Methodology**

After the crosscheck of UNHCR data on Shalozan Tangi IDPs, 359 records were found. Out of
those, telephone numbers were available for 171 families. The return intention survey was
conducted through IVAP call centre (enumerators trained by protection cluster on 20 May
2014 on the return intention survey form) and 137 of IDPs responded to the calls. The
quantitative data collection was facilitated by the use of Personal Data Assistants (PDAs)
programmed with ODK system software. The RIS was conducted by 6 enumerators who
contacted displaced families from a call centre using the contact information available
through the IVAP records. This strategy was chosen due to limited time constraint before
the start of returns.

UNHCR data on Shalozan Tangi IDPs
return intention survey

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Input: 34 Any statistics on the imputed welfare will based on the set of imputed welfares for each household. The estimator takes the form, with R denotes the number of simulation: ܪ ෡ ൌ 1 ܴ ෍ ݄ ሺݕ ෤ ௥ ሻ ோ ௥ ୀ ଵ where ݄ ሺݕሻ is a function that converts the vector y with (log) incomes for all households into a poverty measure (such as the head-count rate or bottom 40 %), and where ݕ ෤ ௥ denotes the r-th simulated imputed welfare. Figure 6. Survey-to-Survey Imputation Methodology, an illustration For the case of Turkey, we use the Survey on Income and Living Conditions survey to impute to the Labor Force Survey. Income is used instead of consumption for this paper ’ s analysis. The model included variables related to: household demographics (age, gender, age composition, etc.), household characteristics (education, labor activity, etc.), household head ’ s characteristics (age, gender, labor, education, marital status, etc.) and household assets holding (both livestock and durables). Based on that model the simulated values of consumption (at household level) were imputed for the households in the corruption survey. Usage context: primary mention, background mention, supporting mention.

Survey on Income and Living Conditions survey

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Input: tanker water. 36 Improved bathing refers private or shared bathtub, shower, separate room for bathing. 0 20 40 60 80 100 120 Hosts Refugees Hosts Refugees Hosts Refugees In camp Addis Ababa Total Overcrowded Improved wall Improved roof Percent Figure 2.21: Housing quality Source: World Bank Staff based on SESRE 2023. 0 20 40 60 80 100 Hosts Refugees Hosts Refugees Hosts Refugees In camp Addis Ababa Total Owned Rented UN/NGO temporary UN/NGO permanent Other Percent Figure 2.20: Dwelling type Source: World Bank Staff based on SESRE 2023. Sociodemographic Profile 23 Refugees’ access to improved sanitation facilities is similar to hosts. Refugees’ access to improved toilet facilities37 is the same as hosts, or even better in some cases. Eritrean, Somali, and OCP refugees and their hosts have similar toilet facilities. Even though the percentage of households with access to improved toilet facilities is lower among South Sudanese refugees than other refugees, it is higher compared to their hosts. Moreover, refugees have higher access to improved waste disposal methods38 than hosts. Both refugee and host households have low access to electricity, except for hosts of Eritrean refugees. Hosts around Eritrean refugees have better access to electricity (meter private or shared) for

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Input: 13 Proposition 7 State-Level Effects of Population Size: The risk of civil war events at a location varies with the size of the population of the country to which the location belongs, controlling for the local effects. 3 Research Design 3. 1 Unit of Analysis To distinguish between the different theoretical statements regarding how population sizes, population concentrations and locations relate to risk of conflict, we need to investigate exactly where conflicts occur. We have created a dataset using a Geographic Information Systems (GIS) program which converted large territories into smaller portions of 8. 6 km x 8. 6 km, totaling 74 square kilometers. Each of these grid squares are our units of observation (we will refer to them as squares). This approach is similar to that of Buhaug & Rød (2006), with two important differences. First, their squares are much larger (100x100km). Second, they code the dependent variable considerably more crudely than is done in the ACLED dataset described below. Buhaug & Rød (2006) use the `scope'and `location'variables in the Uppsala / PRIO dataset. Usage context: background mention, primary mention, supporting mention.

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Input: interactions between hosts and refugees may help improve hosts’ attitudes (Betts et al., 2023). In some contexts, refugee inflows have been found to harden in-group identification and increase support for ideological extremes. This was the case with refugee inflows in Denmark, for instance, but only in rural areas (Dustmann et al., 2019). On the other hand, refugees hosted in Austrian municipalities for extended periods, as opposed to those who passed through, were found to reduce support for anti-immigrant parties, pointing to the benefits of refugee-host interactions (Steinmayr, 2021). All-in-all, there is little evidence that refugee hosting tends to worsen attitudes toward refugees in the Global South (World Bank, 2023b). 7.1 Attitudes between refugees and hosts SESRE data show that, while some hosts have negative attitudes towards refugees, most attitudes are generally positive. Sixty-five percent of hosts agree that refugees are friendly and good people, and only 20 percent are uncomfortable with having a refugee neighbor. This is an important finding, highlighting the potential for integration policies. Host attitudes are generally most favorable in the Somali region and most negative around South Sudanese camps; the share not comfortable with having a refugee neighbor increases to 37 percent in the South Sudanese

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Input: 6. Robustness Checks 6. 1. Sample attrition Many challenges were encountered during survey implementation, due to the context – the densely populated and impoverished communities in and around Monrovia are difficult settings in which to find and track respondents — as well as the transience of a young study population. Despite vigorous efforts to track and interview each individual in the sample, a certain amount of survey attrition was expected. As the survey response rates in Table 1 show, 1622 (or 80 %) of the individuals in the study sample were successfully interviewed in both the baseline and midline surveys. Another 305 respondents were interviewed at baseline but not at midline and hence are not in the panel used for the analysis in this paper. 27 This survey attrition, while not much higher than other program evaluations in Africa, may cause concern that the results of this evaluation are biased, especially if the loss to follow up is correlated with individual characteristics that might affect the outcomes. To address this concern, Table 10 presents regressions on the likelihood of panel inclusion, that is, the likelihood of being interviewed at both baseline and midline. The first column indicates that treated individuals are significantly more likely than control to have been interviewed twice. This result persists even after controlling for individual characteristics and community dummies. Usage context: background mention, primary mention, supporting mention.

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Input: of the groups and the distances between them. For instance, (Bazzi et al., 2019) shows that polariza- tion increases ethnic attachment. Others have highlighted the reduction in trust, either interpersonal trust or institutional trust Alesina and Ferrara (2002); Beugelsdijk and Klasing (2016). To assess the importance of alternative explanations, we first replicate our analysis using individual data on violence. In addition to participation in protests, we follow McGuirk and Burke (2020b) in using the Afrobarometer survey data on interpersonal crime and physical assault. We then assess the relationship between the revised refugee diversity indices and alternative individual outcomes such as ethnic vs. national identity, generalized trust, trust in neighbors, and institutional trust (trust in government). The questions from the Afrobarometer mentioned below are used as a proxy for these outcomes: 32 1 Attack: Over the past year, how often (if ever) have you or anyone in your family: Been physically attacked? 2 Crime: Over the past year, how often (if ever) have you or anyone in your family: Feared crime in your own home? 3 National identity: Let us suppose that you had to choose between being a [Ghanaian / Kenyan / etc.] and being a [respondent ’ s identity group]. Usage context: primary mention, background mention, supporting mention.

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Input:
**5.2 Geospatial Data Integration in M&E**

Geospatial data from the national statistics office's 2020 census cartographic database have been integrated into the MIS to enable automatic generation of geographic coverage reports. When a community is registered in the MIS, its geographic code is linked to the corresponding census enumeration area boundary in the geospatial data layer, allowing the M&E team to produce maps of beneficiary coverage against the total population of each target district without additional data processing.

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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: supporting mention, background mention, primary mention.

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Input: 8 areas are listed so that a given number of households can be randomly chosen from the list to be interviewed. The advantage of this approach is that it only requires knowledge of any FDP residing in an enumeration area, so that this person can be included in the sampling frame. The more accurate the number of FDPs in an enumeration area before listing households, the more efficient is the resulting sample. This approach requires appropriate enumeration area maps that can be easily defined through satellite images for camps, but might not be available across the country for FDPs living in host communities. Implementation can be expensive especially with limited knowledge about the number of FDPs in enumeration areas. However, area-based sampling has the big advantage of not requiring FDPs to register. In contrast, list-based sampling uses an existing list of all FDPs and randomly chooses a sample among them. If additional characteristics are available, like location or country of origin, the sample can be stratified. However, the sample will only be representative of registered FDPs. Hence, it is rarely used in the context of IDPs unless a proper registration system is in place. Usage context: primary mention, supporting mention, background mention.

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Input: 16 5. 3 Desire to return (Y / N) Keeping our attention on refugees and IDPs, we wanted to deepen our understanding about their migration plans. In particular, we would like to discover which characteristics are associated with the desire to return to Northern Mali. To this end, we estimated a probit model using the same regressors as in the previous sections. The dependent variable was set equal to one when the respondent was considering the possibility to eventually go back to the North, zero otherwise. The estimated marginal effects have been reported in Table 3 for all respondents (Column 1-2), as well as for only the household heads or their spouses (Column 3-4). The strongest predictor of a planned future return was refugee status: individuals living abroad in refugee camps were up to 25 percentage points more willing to go back than IDPs. Joining this result with those on unemployment presented in the descriptive statistics, we may wonder whether this desire to go back home may have resulted from a more general malaise experienced by these respondents forced to migrate and halted in a limbo not fully integrated with the local community and labor market.

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Input: migration, and reason for movement including asylum / refugee protection (or conflict-induced internal migration) (UNHCR 2016), or a specific question to identify IDPs or refugees. However, not all censuses cover refugees and asylum-seekers (if foreigners are considered outside the scope of the census or because they are considered a special category), 71 nor is it common practice for national censuses to include questions related to forced displacement. 72 Nevertheless, there are several examples of national censuses that have included relevant questions on forced displacement. 73, 74 In the case of protracted internal displacement situations, IDPs are likely to be included in national censuses; however, census instruments may be subject to manipulation for political purposes. There are several drawbacks of population censuses including their cost, the significant training required for enumerators to ensure consistent answers to questions on forced displacement, impediments to field operations and data processing (such as weather conditions and technical problems), the relative infrequency with which they are carried out, and the long processing time before data and statistics become available, which have consequences for the timeliness of data. Moreover, often censuses are not conducted in contested territory or conflict zones where many displaced persons reside, and this limits the completeness of the data.

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Input:
The decision to link it with CM made ENLACE a de facto high-stakes test encouraging

in grade inflation (Contreras and Backoff, 2014). Anomalies in ENLACE and the creation

<!-- PAGE 10 -->
###### **2.2 The ENLACE Panel**

ENLACE created a unique personal identifier ( _Clave_ _Única_ _de_ _Registro_ _Poblacional_ or

the ENLACE dataset included a school identifier, socioeconomic information for each

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Input:
Table 2 reports average daily hours in the three locations for a representative sample of 4,612 individuals drawn from 600 households in rural, peri-urban and urban areas of seven Bangladeshi regions

A previous paper by the authors (Dasgupta, et al., 2004) has documented extensive indoor air-quality monitoring in the peri-urban area of Narshingdi (Dhaka region).

Drawing on information from continuous, 24-hour monitoring of PM10 in 27 households in Narshingdi, Figure 2 displays a typical daily pollution cycle as

closer to cooking-area concentrations, and our 24-hour monitoring data indicate that daily pollution

monitoring of PM10
24-hour monitoring data

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Input: We complete this data with exact geographic location data from MineAtlas (2013), where satellite imagery shows the actual mine boundaries, which allows us to identify and update the center point of each mine. The production data and ownership information are double-checked against the companies ’ annual reports. For Ghana, this exercise results in 17 industrial mines tracked over time. We have annual production levels from 1990 until 2012. As mentioned, Table 1 shows the mining companies active in Ghana during recent decades, with opening and closing years (although some were closed in between, and are not presented in the table). Figure 2 shows the geographic distribution of these mines. Figure 2 Gold mines and DHS clusters in Ghana Panel A Gold mines and 20 km buffer zones Panel B Gold mines, DHS clusters, and 100 km buffer zones 4 The distances are radii from mine center point, and form concentric circles around the mine. 5 The DHS and the GLSS data are representative at the regional level, and not at the district level. Since the regional level is too aggregated, we do the analysis at the district level, but note that the sample may not be representative. Usage context: primary mention, background mention, supporting mention.

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Input: The ESMF prepared for this project builds on environmental screening templates developed under the predecessor operation and incorporates updated guidelines on asbestos management and e-waste disposal issued by the Ministry of Environment in 2023. Subproject screening will be conducted using the ESMF's standardized checklist, and outputs will be retained in the project's environmental and social documentation register. Where screening identifies potential impacts on natural habitats or physical cultural resources, a qualified environmental specialist will prepare an ESMP prior to works commencement.

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

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Input: 2 INTRODUCTION In 2015, an estimated 2. 2 million Syrians Under Temporary Protection (SUTPs) were residing in Turkey, the majority arriving in the country over the last 4 years. 2 Turkey ’ s national population is roughly 75 million; recent refugees account for approximately 3 percent of the population. For a country that has never experienced such a large-scale, sudden inflow of foreigners, demographic changes in the composition of the population and labor force will yield unprecedented implications. This paper examines, as data allows, the relationship between the size of the foreign-born population and host community poverty rates in Turkey. First, this paper finds the poverty rates of ‘ recent migrants ’ near the Syrian border (NSB) significantly increased from 2009 to 2013. Second, the number of foreign-born households being captured by the Labor Force Survey (LFS) is expanding, which suggests a growing number of foreign households that are likely to be Syrians. Third, with respect to poverty, the results show no negative impacts on the host community as a result of the increasing size of the foreign-born population. The impact of SUTPs has been both positive and negative. Overall, a significant negative impact on host communities ’ welfare is not observed in the data.

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Input:
income has not led to more happiness using Eurobarometer and US GSS data. Variables used

or panel data) but a few use variables transformations of income and relative income that would

problem one would need panel data, good instruments for personality traits or variables that

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

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

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

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Input: Staff based on SESRE 2023. Note: Columns 3-4 are restricted to workers, and Columns 5-6 are restricted to workers in camps. High-skill occupations include managers, professionals, and associate professionals (around 7% of refugees). Standard errors clustered at the EA level. * p < 0.10, ** p < 0.05, *** p < 0.01 Annexes 124 Table E.1: Food aid data/information received from UNHCR Item Remark Assumptions Cereal Not clear Other cereals Wheat Matched Maize Matched Rice Matched Sorghum Matched CSB/famex (CSB+) Not in SESRE Average of other cereals/pulses Pulse Not clear Peas Biscuit Matched Date biscuit Not in SESRE Merged with biscuits Dates Matched Oil Merged with edible oil Vegetable oil Merged with edible oil Salt Matched Cash - - Source: UNHCR Annex E: Robustness Checks of Refugees’ Consumption This Annex discusses assessing the disparity between refugee ration aid and reported consumption quantities. This is reported as a robustness check. As discussed earlier, the expenditure of in-camp refugees is almost half that of hosts despite sizeable food aid and significant investments made by the WFP and UNHCR in cash transfers (in selected camps). The significantly lower expenditures (food and non-food) among refugees compared to the host population led to higher poverty

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

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Input: For this study, data on the four types of capital are obtained for three periods - 1995, 2000 and 2005 and for 210 countries, from an updated database underpinning the wealth estimates of nations (World Bank, 2006; G. Ruta and K. Hamilton, personal communication, 2009). The data are measured in per capita values at 2005 constant prices. An econometric analysis is conducted for a panel data of capital, along with the data on the magnitude of natural disasters for the same 2 <!-- PAGE 5 --> periods. Because of limitations in the data on human capital related to education (HS), the intangible capital residual (HR) is used as a proxy measure of human capital in this study.

updated database underpinning the wealth estimates of nations

data on the magnitude of natural disasters

data on human capital related to education

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Input: The age categories are 15 – 19, 20 – 24, 25 – 29, 30 – 34, 35 – 39, 40 – 44, 45 – 49, 50 – 54, 55 – 59, and 60 – 64 years. There are 183 groups since we exclude groups containing less than 40 observations. 24 An additional advantage of the IV approach is that it helps deal with measurement problems. Despite the improved measures of refugee numbers in Turkey by subregion starting in 2014, there is likely considerable measurement error, resulting in attenuation bias in the OLS estimates. For the IV estimates to be consistent, it is only necessary that- conditional on the fixed effects and control variables- the flows of Syrian refugees are uncorrelated with the instrument. 25 Using data from AFAD (2013) we can also weight the aggregate refugee numbers using the Syrian source governorates of refugees in 2012-13 (see Figure 2). Results are qualitatively robust to this alternative instrument and first-stage F-statistics about the same. We prefer the use of the pre-war distribution of population in Syria,

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Input: Looking also at the impact of IDPs in Colombia on wages, Morales (2017) uses a labor force survey, census data and registry data to study short and long-term effects as follows: 𝑆ℎ𝑜𝑟𝑡 െ 𝑟𝑢𝑛: 𝑦 ௜ ௠ ௧ ൌ 𝛼 ൅ 𝛽𝑑 ௠ ௧ ି ଵ ൅ 𝜆 ௜ 𝑋 ௜ ௠ ௧ ൅ 𝜆 ௠ 𝑋 ௠ ௧ ൅ 𝛾௧ ൅ 𝛿 ௠ ൅ 𝛿 ௠ 𝑇 ൅ 𝜀 ௜ ௠ ௧ 𝐿𝑜𝑛𝑔 െ 𝑟𝑢𝑛: 𝑦 ௜ ௠ ൌ 𝛼 ൅ 𝛽𝑑 ௠ ൅ 𝜆 ௜ 𝑋 ௜ ௠ ൅ 𝜆 ௠ 𝑋 ௠ ൅ 𝛿 ஽ ௠ ൅ 𝜀 ௜ ௠ where y is the log of wages, i, m, and i are individuals, municipalities and time respectively, 𝑋 ௜ ௠ ௧ are individual controls, 𝑋 ௠ ௧ is the log of total population or other municipality controls, 𝛾௧ and 𝛿 ௠ are time and municipality fixed effects, 𝛿 ௠ 𝑇 are municipality time trends, 𝛿 ஽ ௠ are department fixed effects and d is the inflow of IDPs defined as 𝑑 ௠ ௧ ൌ 100 𝑝𝑜𝑝 ௠ ௧ 𝑓 ௠ ௧ where 𝑓 ௠ ௧ is the total number of IDPs arriving in municipality m at time t. The same variable without the t subscript is used for the long-run effects equation. Usage context: background mention, primary mention, supporting mention.

labor force survey
census data
registry data

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Input: Surveys of employers consistently find that more than hard, technical skills, employers value these harder-to-quantify skills of honesty and integrity, problem-solving ability, work ethic, communication skills, the ability to work productively with others, responsibility and dependability (Blom and Hobbs 2007). The AGI program has focused on the development and measurement of these softer attributes that matter for employment as well as those that matter more to the individual, such as self-confidence and empowerment. Despite the challenges of measuring such subjective outcomes, the survey instruments included panels of questions designed to elucidate a nuanced picture of the personality and psychosocial characteristics that are most relevant for labor market success. Table 6A presents results on empowerment and decision-making. The first series of questions have to do with control over resources, spending decisions and earnings. Respondents were asked how much control they had over how to spend their own earnings; also, whether they had money of their own for basic uses that they alone could decide how to use, without having to ask for permission. The EPAG baseline survey found that respondents reported a high degree of control over resources even before the program started.

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Input: of Return Migration, Human Capital Accumulation, and Wage Assimilation. The Review of Economic Studies, 89(6), 2841-2871. Alix-Garcia, J., Walker, S., Bartlett, A., Onder, H., and Sanghi, A. (2018). Do Refugee Camps Help or Hurt Hosts? The Case of Kakuma, Kenya. Journal of Development Economics, 130, 66-83. Alkire, S., Kanagaratman, U., and Suppa, N. (2021). The Global Multidimensional Poverty Index (MPI) 2021, OPHI MPI Methodological Note 51. Oxford Poverty and Human Development Initiative, University of Oxford. Altindag, O., Bakls, O., and Rozo, M. S. (2020). Blessing or Burden? Impacts of Refugees on Businesses and the Informal Economy. Journal of Development Economics, 146. https://doi.org/10.1016/j.jdeveco.2020.102490 Andersen, H.L., Osland, L. and Zhang, M.L. (2023). Labour Market Integration of Refugees and The Importance of the Neighborhood: Norwegian Quasi-experimental Evidence. Journal of Labour Market Research 57, 16. https://doi.org/10.1186/ s12651-023-00341-y Aracl, D., Demirci, M., and Klrdar, M. (2022). Development Level of Hosting Areas and the Impact of Refugees on Natives’ Labor Market Outcomes in Turkey. European Economic Review, 145. https://doi.org/10.1016/j.euroecorev.2022.104132 Atamanov, A., Hoogeveen, J., and Reese, B. (2023). The Costs Come Before the Benefits Follow. Why Should Donors Invest More in Refugee Autonomy in Uganda? 1–11. Azlor, L., Damm, A. P., and Schultz-Nielsen, M. L. (2020). Local

Global Multidimensional Poverty Index (MPI) 2021

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Input:
In the ALTA study, perception of tenure security is asked on a scale from 1 to 5, ranging from "not at all likely [to involuntarily lose land]" to 'extremely likely [to involuntarily lose land]", in line with the joint module by FAO, World Bank, and UN-Habitat (2019).

In the ALTA study, the non-response rates at the individual level for Arms 1 and 2 are 13% and 12%, respectively, with the difference not statistically different from zero.

This paper uses data from a methodological experiment in Armenia to assess the implications of survey design-namely, respondent strategy and the level of disaggregation of land data-on the measurement of individual land rights and SDG indicator monitoring.

Evidence from the Uganda Methodological Survey Experiment on Measuring Asset Ownership from a Gender Perspective (MEXA), which fed into the development of the UN EDGE guidelines, illustrates the asymmetric impacts of respondent approach by gender.

3 For reports on the LSMS+ surveys in Tanzania, Malawi, Ethiopia, and Cambodia, see Hasanbasri et al. (2021a) and
Hasanbasri et al. (2021b).

LSMS+ surveys in Tanzania, Malawi, Ethiopia, and Cambodia

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Input: 16 Source: Authors ’ calculations based on data from the High Frequency Surveys of Ethiopia (2017), Nigeria (2018), Somalia (2017), South Sudan (2017) and Sudan (2017). 6. Gender differences in multidimensional poverty Next we examine differences in multidimensional poverty outcomes by the gender of the household head. Existing literature points out the limitation of household level MPI analysis in masking the intrahousehold distribution of deprivations, and thus being less sensitive to gender based differences in individual outcomes within the family unit, which might lead to underestimation of inequality and gender gaps (Espinoza-Delgado and Klasen 2018; Franco 2017; Klasen and Lahoti 2020, Rodriguez, 2016). However, as the MPI identifies poverty at the household level, our initial analysis focuses on disaggregated results by the gender of the household head. 19 We acknowledge that this approach has several limitations since most women reside in male-headed households, and the composition of households can change after displacement due to separation of family members, and widowhood. Regardless, the analysis at the household level remains relevant given the high prevalence of female-headed households that emerge after displacement, with the analysis showing large differences across countries between households based on the gender of the head. Usage context: supporting mention, primary mention, background mention.

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

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Input:
<!-- PAGE 7 -->
As we did not have meteorological data for each and every municipality in Chile, this
information was estimated. Since average annual temperature in any particular location
depends principally on distance from the equator and elevation above sea-level, we
estimated a simple model (see Table 2) using information on average annual temperature,
latitude, and altitude for all the Chilean stations for which we could obtain "normal"
temperature data (from www.worldclimate.org). In order to get sufficient variation in the
elevation variable, we included 4 stations located close to Chile (Catamarca, Mendoza,
Arequipa, and Oruro).

In this section we will analyze climate data for Chile from May 1948 to March 2008 to test
whether there are any significant trends, and whether these trends differ between regions.

We will use the Monthly Climatic Data for the World database collected by the National
Climatic Data Center (NCDC) in the US. This project started in May 1948 with 100
selected stations spread across the World, including five in Chile. Since then, many more
stations have been included in the data base, but only seven stations in Chile have
contributed systematically throughout the period, with only inconsequential gaps. These are
listed in Table 5, ordered from north to south.

According to the model simulations reported in Christensen et al (2007), temperatures are going to increase faster in the northern part of Chile than in the southern part

temperature data are extracted from the New et al. (2000) gridded 0.5 degree dataset. Calculation of

indices, such as the Palmer Drought Severity Index which uses precipitation and temperature to measure

Monthly Climatic Data for the World
Palmer Drought Severity Index

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Input: Surveys, 76 Demographic and Health Surveys (DHS), 77 and Multiple Indicator Cluster Surveys (MICS). 78 The advantage of these surveys is that they cover a wide range of countries and are conducted in a regular or systematic manner (UNSD 2014). There are only a few cases where modules or questions on forced displacement have been integrated into survey instruments (most notably in Somalia, Uganda, West Bank and Gaza, Azerbaijan, Bosnia and Herzegovina, Serbia, Ghana, as well as health surveys in Albania, Ukraine and Moldova). There are several challenges associated with ‘ mainstreaming ’ forced displacement into household surveys: (a) there is huge demand for adding sector-specific or thematic modules to international surveys; (b) it is relatively difficult to convince national statistical agencies to modify their county-specific surveys; (c) disaggregating survey results by specific vulnerable groups (e. g. refugees, IDPs, migrant populations) requires these distinctions to be integrated into the sampling frame and sometimes there is insufficient information to do this or a lack of resources to expand the sample size; (d) lack of access to displacement- affected areas; and (e) difficulties associated with integrating an inherently political topic into less controversial surveys.

Multiple Indicator Cluster Surveys
Demographic and Health Surveys

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Input:
To complete this analysis with information on how these losses are distributed in the population and especially on the poorest, a survey was conducted with informal dwellers affected by the 2005 floods. It was found that the aggregated losses they suffered from are about $250 million (for total losses due to the 2005 flood of about $2 billion), but the relative impact on their savings and consumption was extremely large, with average capital losses of the same order of magnitude than their average total savings (in other terms, their savings were totally wiped out by the event).

<!-- PAGE 12 --> _Figure 2: Roofer wages in an area where losses have been significant after the 2004 hurricane season in_ _Florida. Data from the Bureau of Labor Statistics, Occupational Employment Surveys in May 03, Nov 03,_ _May 04, Nov 04, May 05, May 06, May 07._

The box figure illustrates the effect of insurance penetration [13] on the household's budget, for a July 2005 like flood estimated using the ARIO model. Three scenarios are included: (i) γ=0, equivalent to the absence of insurance system, but with an access to credit; (ii) the current value of flood insurance penetration estimated by RMS (γ=0.08 for households, γ=0.15 for firms); and (iii) γ=1, representing the situation where all the reconstruction is paid for by insurance.

<!-- PAGE 5 --> methodologies and approaches, and they often reach quite different results. In the US, for instance, a systematic analysis by (Downton and Pielke, 2005) showed that loss estimates differ by a factor of 2 or more for half of the floods that cause less than $50 million in damages.

One of the appealing features of night lights data is their availability on every level. Night lights
data are measured on the so-called 30 arc sec level, corresponding to roughly 1 square kilometer
at the equator.

Bureau of Labor Statistics, Occupational Employment Surveys

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Input: Produced by the Research Support Team Abstract The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development / World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Policy Research Working Paper 10100 This paper explores the impact of refugee return on social cohesion using data from Burundi, a country that experienced high levels of repatriation during the 2000s. It uses a nationwide survey conducted in 2015 and relies on geographic features of the communities for identification purposes. The results suggest varying impacts of refugee return on different aspects of social cohesion. The stronger effects, suggest that refugee return has a negative impact on the feeling that community members help each other, could borrow money for emergencies from non-household members and feeling that the community is peaceful. Usage context: primary mention, background mention, supporting mention.

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Input: Wages: the earnings measure we use is the response to the question “ how much did you earn from your main job activity during the last month? ” In the LFS 2011 there is further information on how much of that income was irregular, for example a bonus payment, but the LFS 2014 no longer provides that breakdown. There is also a measure of the “ number of hours per week worked in the main job ” (both usual and total hours), which can be used to construct hourly wages. Since the hours worked measure does not correspond exactly to the earnings measure and introduces additional measurement error, our preferred wage measure is the monthly wage. We exclude wage observations were respondents report having usual working hours of less than 14 or more than 84 hours per week. Usage context: supporting mention, primary mention, background mention.

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Input: 14 people may also gain from conflict in terms of income and wealth and this may explain why some people do not move. The defining attributes of the alternative choices are very different from any other model and the task of economics is to understand what these defining attributes should be. In terms of independent variables, “ push ” factors become more important than “ pull ” factors in forced displacement models. The intensity of a conflict may be more important than the income opportunities in potential destination areas. In addition to the classic socioeconomic variables, risk aversion, stress, anxiety, other traits of personality and behavioral factors in general have to be well understood and measured. Hence, one could think of four essential blocks of independent variables including individual or household socioeconomic characteristics, “ push ” factors, “ pull ” factors and behavioral factors. Also, access to and dissemination of information related to the conflict in the place of origin but also in the potential places of destination may be crucial for people to make choices. This is where social psychology, behavioral economics and neuroeconomics may offer insights into such choices. Forced displacement data are also unusual in their form. Usage context: background mention, primary mention, supporting mention.

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Input: 14 displacement. 55 % of the returnees reported to have been employed before the crisis and 36 % in June 2014. Over time the employment situation among the displaced has improved steadily and by December 2014 more people reported being employed than prior to the crisis. All the returnees were able to regain employment after returning. The employment situation of IDPs, returnees, and refugees in Niger is steadily improving; only for refugees in Mauritania does one notice a steady decrease, with 100 % reporting no employment during January and February. Source: Listening to Displaced People Survey, 2014 and 2015. The ownership of livestock and consumer durables was reduced significantly as a consequence of the crisis. Table 7 demonstrates this by showing the Tropical Livestock Units (TLU) 12 owned prior to the crisis and in June 2014 as well as the percentage of ‘ yes ’ responses on a question whether a given asset was owned by the household. 13 The loss on livestock has been enormous particularly amongst IDPs and refugees who lost respectively more than 90 % and 75 % of their animals. 12 TLU is a common unit to describe livestock numbers of various species as a single figure that expresses the total amount of livestock present – irrespective of the specific composition. 13 This was a ‘ yes / no ’ question meaning that if 56 % of the Usage context: background mention, supporting mention, primary mention.

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