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: 14 4. 1 Variation across Districts Pakistan is divided administratively into four provinces with 102 districts — Punjab, Balochistan, North-West Frontier Provinces (NWFP), and Sindh — plus the federal capital Islamabad, the Federally Administered Tribal Areas (FATA), the federally administered Northern Areas and Azad Jammu and Kashmir (AJK). The four provinces or Punjab, Balochistan, Sindh and NWFP, together with Islamabad, account for more than 97 percent of the population. Geographically, parts of Balochistan, the NWFP and FATA border Afghanistan. Sindh and Balochistan are sparsely populated provinces, with the exception of Karachi in Sindh, which is the single biggest metropolis in the country with a population approaching 10 million. We use data from the population census, 1998, as well as the census of private schooling, 2000, to provide estimates of madrassa, private, and government school enrollment in each district except for those in the province of FATA. The geographical dispersion of madrassa enrollment depends on how we define madrassa prevalence. There are three alternatives. We could present a geographical breakdown of the total number of children enrolled in madrassas. This number is related to the total population of the district, and may thus reflect only the size of the district relative to others.

population census, 1998
census of private schooling, 2000

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Input: be imputed into the LFS, it may be unclear, ex-ante, if SUTPs are adequately included in the survey. Despite a small sample of foreigners and other concerns, there is evidence that the LFS sample does include some “ recent foreign ” migrants, especially in the border regions (NUTS2) [TRC1-Gaziantep, Adiyaman, Kilis, TRC2-Sanliurfa, Diyarbakir, TRC3-Mardin, Batman, Sirnak, Siirt TR63-Hatay, Kahramanmaras, Osmaniye] (Map 1). Usage context: primary mention, supporting mention, background mention.

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Input: Publications Office of the European Union. Fasani, F., Frattini, T., and Minale, L. (2022). (The Struggle for) Refugee integration into the Labour Market: European Evidence. Journal of Economic Geography, 22(2), 351-393. Feyissa, D. (2015). Power and Its Discontents: Anywaa’s Reactions to The Expansion of The Ethiopia Statae, 1950 – 1991. International Journal of African Historical Studies, 48(1), 31 - 49 FDRE. (2004). Refugee Proclamation No. 409/2004. FDRE. (2019). Refugee Proclamation No. 1100/2019. FDRE. (2020). Investment Proclamation No. 1180/2020. Fuller, S. (2015). Do Pathways Matter? Linking Early Immigrant Employment Sequences and Later Economic Outcomes: Evidence from Canada. International Migration Review, 49(2), 355-405. Gebreegziabher, T., and Regassa, N. (2019). Ethiopia’s High Childhood Undernutrition Explained: Analysis of the prevalence and Key Correlates based on Recent Nationally Representative Data. Public Health Nutrition, 22(11), 2099–2109. .org/10.1017/ S1368980019000569 Gebru, F. K., Haileselassie, M. W., Temesgen, H. A., Seid, O. A., and Mulugeta, A. B. (2019). Determinants of Stunting among under-five Children in Ethiopia: A Multilevel Mixed-effects Analysis of 2016 Ethiopian Demographic and Health Survey Data. In BMC Pediatrics 19 (1). BioMed Central Ltd. .org/10.1186/s12887-019-1545-0 Ginn, T., Resstack, R., Dempster, H., Arnold-Femandez, E., Miller, S., Guerrero, M., and Kanyamanza, B. (2022). 2022 Global Refugee Work Rights Report.

2016 Ethiopian Demographic and Health Survey Data

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Input: Table 2: Ethnic composition of IDPs, refugees, returnees in the North Ethnicity IDPs in Bamako (%) Refugees Niger (%) Refugees Mauritania (%) Returnees (%) Total I + R + R (%) Ethnic composition of the North (%) Songhai 75 21- 71 43 45 Kel Tamasheq 12 56 69 12 38 32 Arab 3- 28 4 11 3 Peulh 4 21- 6 4 7 Other 6 11 3 7 4 12 Total (%) 100 100 100 100 100 100 Total (n) 100 81 100 220 501 1, 268, 009 Source: Listening to Displaced People Survey, 2014 and 2009 Population and Housing Census. The ethnic composition of IDPs and returnees is almost identical. This is a reflection of the fact that 94 % of returnees were displaced within Mali. Only 6 % returned from outside the country. The reason why few returned refugees are in the returnee sub-sample is explained by their place of residence prior to the crisis: only 5 % of the refugees in Mauritania and Niger lived in Timbuktu town before their displacement; 2 % lived in Gao town and 1 % in Kidal town. The remaining 92 % lived in 27 different towns and villages in northern Mali, locations not covered by the survey. Usage context: primary mention, background mention, supporting mention.

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

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Input:
this approach to calculating hunger the HCES-direct method. Of note is that neither the FBS-CV nor the

HCES-direct method actually measures what individuals ate (as in a food intake survey) or ask about

The FBS-CV and HCES-direct methods both rely on household surveys. In the case of the FBS-CV method,

the second moment of the calorie distribution comes from the surveys, while the HCES-direct method

relies on the surveys for all moments. Yet, the design of HCES varies over several key dimensions, such

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Input: a devastating war, and frequent droughts and floods. SESRE data collection was carried out between November 2022 and January 2023, marked by drought, inflation, and insecurity, posing significant threats to the livelihoods of refugees and host communities in an already fragile economy. The conflict in Northern Ethiopia continued until 2022 and disrupted the socio- economic conditions in the North Gondar Zone, home to over 20,000 refugees. The November 2022 peace agreement between the federal government and Tigrayan authorities offered a glimmer of hope for ending the war in Northern Ethiopia. Still, tensions in other parts of Ethiopia continued. Additionally, following the outbreak of fighting in the Amhara region in 2023, refugees in the Alemwach camp in the Amhara region faced attacks by unidentified armed groups. Moreover, food assistance for refugees has been unstable due to funding shortfalls, resulting in reduced food rations for hundreds of thousands of refugees for several months in 2022 and 2023. Insecurity in the Gambella and Benishangul-Gumuz regions not only undermined refugee and host community livelihoods but also heightened tensions between them. The intensification of conflict in Western Oromia further disrupted humanitarian operations in Eastern Benishangul-Gumuz, blocking the transport of relief and commercial supplies and affecting

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Input: To take advan- tage of the much larger ProGres database of nearly 2. 2. million refugees, we compute area averages for the above-mentioned case-level host community conditions, aggregat- ing to the smallest possible geographic unit available (district level for Lebanon and governorate level for Jordan). This information is then matched with all refugees in the ProGres database that have location information in Lebanon and Jordan, yielding a sample of 1. 85 million refugees. Finally, we worry about reporting bias. Respondents may have felt they were more likely to receive assistance if they reported worse living conditions. The bias could also go the other way if refugees want to signal their gratitude for the assistance they receive. The problem is even more acute given our research question. Those who intend 13 Usage context: background mention, primary mention, supporting mention.

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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: This paper combines newly available data on the distribution of Syrian refugees across Turkey and the Turkish Labour Force Survey to assess their labor market impact. Syrian refugees are overwhelmingly employed informally, since they were not issued work permits, making their arrival a well-defined supply shock to informal labor. Consistent with economic theory our instrumental variable estimates, which also control for distance from the Turkish-Syrian border, suggest large-scale displacement of natives in the informal sector. At the same time, consistent with occupational upgrading, there are increases in formal employment for the Turkish- though only for men without completed high school education. Women and the high-skilled are not in a good position to take advantage of lower cost informal labor. The low educated and women experience net displacement from the labor market and, together with those in the informal sector, declining earning opportunities. Usage context: supporting mention, background mention, primary mention.

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Input: cents. The universe of blocks (“ manzanas ”) was stratified by socioeconomic strata and a representative sample of blocks was selected at random without replacement. To en- sure a sample representative of Colombian children by age group, stratum, and sex, we followed a multi-stage random sampling process. 8 As mentioned earlier, one of the biggest constraints in characterizing the role of forced migration in children ’ s human development within developing countries is the difficulty of finding a representative sample of those migrants. This is specially true in contexts where migrants are not hosted in refugee camps, but are integrated in local communi- ties, which account for 80 % of refugees worldwide (Climate Center 2022). We address these difficulties, leveraging all available information on Venezuelan settlements across the country to construct the largest possible comprehensive listing. The listing included data on Venezuelan settlements from all available sources, such as the 2018 population census, migrant organizations, and settlements identified by iMMAP, a non-profit orga- nization. iMMAP uses multiple sources, including OIM, United Nations, local migrant organizations, and satellite images, to identify Venezuelan settlements geographically. 9 Hence, to create our sampling frame, our field team verified the geographic location of all the Venezuelan settlements in-person and implemented a snowball sampling procedure in all the settlements found. Usage context: supporting mention, primary mention, background mention.

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Input:
complete census of land parcels in Barafu and Kati, known as the Tanzanian Land Rights

Survey (TLRS). Households were identified using records and maps from the Kinondoni

Municipality, which had created a listing of all households in the area to assist with the

**Notes:** data are from Tanzanian Land Rights survey. Sample restricted to dual-headed households in
treatment blocks.

levels of female land ownership: investigating the gender breakdown of land ownership in

using baseline data from the experimental intervention, which is discussed in more

detail in the following section. Households in two unplanned settlements in Dar

es Salaam were asked a series of questions about the _de_ _facto_ ownership of land,

5To avoid priming, households were not asked directly about female ownership. Instead, they were
asked to list all members of the household that were default owners, must be consulted before a sale, or
would be included on a CRO.
6Section 191(2) of the 1999 Land Act and section 58 of the (1971) Law of Marriage Act.
7Authors' calculations using data from the Kinondoni municipal data.
8Section 159(6) of the 1999 Land Act.

8

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Table 1: Female land ownership in Dar es Salaam

baseline data from the experimental intervention

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

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Input: However, there is no consensus or agreed best practices on the use of these methods in different contexts or stages of displacement (Brookings 2013). 92 The absence of data on new displacement may simply mean that no displacement has taken place (IDMC 2016). 93 IDMC reports that data, disaggregated by age and sex, were available for 15 of the 60 countries it monitored in 2014, however these data were not comprehensive and are not published. Additionally, in some countries there are data provided by IOM on IDP populations by location from which the urban or rural character of the population may be inferred (e. g. if the camp is located in the capital), but data are not comprehensive and not published. While the majority of humanitarian profile data does not typically cover IDPs living outside of camp or camp-like settings (the large majority of IDPs), IOM ’ s DTM in countries such as Nigeria, Iraq, Yemen and Libya do include information about those residing in host communities. Usage context: primary mention, background mention, supporting mention.

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Input: project had to meet a basic minimum literacy level in order to qualify for admission to the program; whereas only half of the 15-29-year-old female respondents to the nationally-representative Core Welfare Indicators Questionnaire (CWIQ) survey report that they can read and write (LISGIS 2007). Fewer than two percent of the girls in the EPAG study responded that they had no education, which is much lower than in the CWIQ survey. Second, the majority of adolescent girls and young women in Liberia reside in rural areas, whereas the survey participants were residing in urban and peri-urban areas, where access to basic social services may be much more improved. Consequently, the results are not representative of adolescent girls and young women in Liberia overall. The results are neither indicative of the average Liberian girl and young woman; nor are they indicative of the average Liberian girl or young woman in the project communities. They are only indicative of the average girl and young woman who are part of the EPAG project. Finally, many of the variables that we examine in this study are measures of self-assessed levels of satisfaction or belief. These are entirely subjective variables, and are subject to significant measurement error. There is considerable evidence that the wording of these questions can affect the answers given, as can the order in which the questions are asked. Usage context: supporting mention, primary mention, background mention.

Core Welfare Indicators Questionnaire
CWIQ survey

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Input: The MHPSS referral pathway was tested through six clinical review sessions conducted jointly by the project's MHPSS technical advisor and the district psychiatric nurses. Case reviews identified bottlenecks at the step between community-based MHPSS workers and facility-based counselors, particularly for cases involving domestic violence survivors. Revised referral procedures were agreed, including a protocol for same-day warm handoffs in urgent cases and the designation of dedicated MHPSS consultation slots in three district hospital outpatient departments.

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Input: Using the NLSS data we begin by estimating a regression of the form: yk s = δs + α (ak s − a) + βs (Ek s − Es) + χs (Hk s − Hs) + vk s (4) where yk s is the log of income (or consumption) of household k residing in district s, coeﬃcients δs, βs and χs vary by district, ak s stands for the age and age squared of the household head, Ek s is the education level of the head measured in years of completed education, and Hk s = 1 if the head belongs to what we have earlier classiﬁed as a high caste (i. e., Brahmin, Chhetri or Newar). Since income or consumption are expressed in logs, βs and χs can be thought of as education and high caste premia, respectively. Female headed households are excluded from the regression since the focus is on migrant males. Vector a denotes the average age and age squared of observations across the sample. Variables E and Hs denote the district-speciﬁc averages of Ek s and Hk s. By demeaning regressors, we ensure that eδs measures the unconditional, district- speciﬁc average of yk s. Marital status, household size, and other household characteristics are 15 Usage context: background mention, primary mention, supporting mention.

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Input: estimates, we also estimate the continuous time, semi-parametric Cox proportional hazard (Cox) model. The main advantage of the Cox model is that it allows us to estimate the relationship between the hazard rate and the determinants of refugee returns without having to make any assumptions about the shape of the baseline hazard function. A continuous time model might also be appropriate in this context, given that we have a long panel of 75 months. Using the same variable deﬁnition as in 3, we estimate h (t) = h0 (t) exp [β1chari + β2regi + β3foodsect + β4housingt + µl + δd + τt] (4) We restrict survival analysis to the Syrian refugees based in Jordan and Lebanon as their host country conditions are proxied by the geographical aggregates computed from the VAF and VASyr surveys. Despite this restriction, more than 85 percent of all refugees in our data set is included in the analysis. It is important to note that the conditions in the country of asylum may be the result of a refugee ’ s anticipated length of stay in the host country. Usage context: supporting mention, primary mention, background 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

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Input:
graduates aged 18, 19, and 20. The objective of ENILEMS was to provide information on

The ENILEMS-ENLACE panel merges information from the respondents of the ENILEMS

2010 survey with their results in the ENLACE Grade 12 taken in May of 2008, 2009, or

2010. Although ENILEMS 2010 did not capture the CURP, it included all the necessary

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Input:
For each of these food items we obtain calorie intake values from TBCA that are based on the descriptions of the food item in POF and TBCA. TBCA has calorie intake values for different preparation forms of the food item.

A second step is applied in order to increase the list of food items that have calorie intake assigned to
them-and thus contribute to the cost per calorie estimation. In this step, we create food groups by
aggregating POF's original 7-digit item code to a 5-digit item code. Based on this, we impute calorie intake
to items that were not mapped to calorie intake in step 1.

For instance, different types of rice ( _arroz_ _hibrido_, _arroz bica corrida_, _arroz quirera_ ) were not found in the TBCA, but by creating a 5-digit aggregation, we can assign them to the same group as _arroz polido,_ for which we do have a caloric intake estimate.

For all of these types we assign the average value of calorie intake for rice at this 5-digit item code that had calories assigned from TBCA in step 1 (in this case, _arroz polido_ ). After this step, we have raw calorie intake values for 1,413 items, which account for 86.6 percent of average total expenditures on food consumed at home and 58.1 percent of all food expenditures.

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Input: In order to address these potential sample biases, the CAVR supplemented its documentation with reports produced by Amnesty International and Fokupers (a local NGO). The information contained in these reports was then included into the HRVD database. 9 Note that we do not analyse school completion in 2001 because most children that were of school age in 1999 were still in school in 2001. 10 The questions we used are ― Was [NAME] displaced outside E. Timor in 1999? ‖, and ― Was the [BUILDING] damaged in the violence of 1999? ‖. 14 % of the whole sample surveyed in 2001 report having been displaced, while 26 % report that their house was destroyed. Within our sample of school age children, these figures are 16 % and 25 %, respectively. We have made sure that buildings that are reported to having been destroyed were used for living purposes only. Usage context: primary mention, background mention, supporting mention.

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Input: We measure time-use through the number of hours in the previous day a respondent reports spending idle, as well as the amount of time spent on a variety of other common activities one might do in the camps (including bathing, market, chores, collection of rations, eating, child-rearing, sitting at tea stalls, praying, sleeping, visiting friends / relatives, playing games, playing sport, sitting idle). Finally, we ask respondents how much they consume, borrow and save over the past week. We further consider changes in perceptions on gender and power in two ways. First, we generate a Household Power Index, composed of a set of questions on perceptions of gendered decision-making and intimate partner violence. The questions are drawn from Haushofer and Shapiro (2016), which are themselves adapted from the Demographic Health Surveys. In addition, we produce a Work Rights Index, composed of questions around whether respondents feel that women should be allowed to work inside or outside the home or the camp block. Each outcome is described in greater detail in Appendix C. The frequency with which each outcome is collected is also presented in Appendix C. Multiple hypothesis testing We utilize two approaches to address the issue of multiple hypothesis testing. First, we present our primary outcome, psychosocial well-being, as an inverse-covariance weighted index variable following Anderson (2008). We also generate index variables for other outcomes in which this is possible, such as the cognitive index, the household power index, and the work rights index. Our second strategy is to report the sharpened False Discovery Rate (FDR) q-values for all outcomes within a particular table, which control for the expected proportion of rejections that are type I errors, likewise 12 Usage context: supporting mention, background mention, primary mention.

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

UNHCR statistical population online dataset

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Input: A survey was carried out in the health sector (health centers) with the support of the World Bank in 2005, but has not been yet validated. In the rural development sector, where the first expenditure tracking survey between the decentralized center and services was to be carried out in 2005 on PEFA funds, the survey is yet to be carried out. It is critical that adequate management measures are gradually put in place to stop the current waste of resources. These measures include, inter alia, the accounting improvement of material, improvement of the inventory and delivery control, and especially a transparent planning of the deliveries, including, the posting of the received deliveries, their comparison with the planned deliveries and their certification by users within each service. It would also be desirable that in each ministry, an action plan is prepared for the implementation of these measures, on the basis of existing ones, and with target indicators as regards improvement of the arrival of the expenditure at intended destination. The social ministries could usefully open the way in this field, on the basis of some projection already carried out. Without a quantitative and qualitative improvement of the arrival of the expenditure at their final recipient, the increase in the budgetary appropriations to the priority sectors will hardly be translated into substantial concrete results on the ground. 29 It is difficult to make accurate forecasts for the implementation of certain programs or developments in economic parameters such as inflation or interest rate. Some immediate needs that were not foreseen during budget execution may appear during budget execution. Usage context: background mention, primary mention, supporting mention.

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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 objective of the survey was to analyze perceptions and priorities with regard to the Peace Accord, to analyze perceptions of security, to determine access to basic infrastructure and school attendance, to understand nutrition levels, and to measure household asset ownership. In addition to this baseline survey, the World Bank was sponsoring a mobile phone survey among IDPs in Bamako, returnees in Gao, Kidal and Timbuktu town and refugees in camps in Niger and Mauritania. This survey interviewed 500 respondents on a monthly basis. In the August 2015 round of this survey, questions about perceptions and priorities with regard to the Peace Accord were included. This paper also makes use of a subset of the responses obtained from that survey, particularly those from refugees in Niger (n = 80) and Mauritania (n = 100) as these sub-populations who live outside Mali ’ s borders are important stakeholders in the peace process whose opinions risk being ignored. 15 To select a household in a village or neighborhood for the baseline survey, random selection was used: the enumerator divided the locality into two parts and selected five 15 For a more elaborate description of this mobile phone survey, see: Etang Ndip, A., J. Hoogeveen and J. Lendorfer (2016). Socioeconomic Impact of the Crisis in Mali on Displaced People. Journal of Refugee Studies. Usage context: primary mention, background mention, supporting mention.

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Input: any other population, have varied health-related issues, including noncommunicable and communicable diseases and trauma from injuries and violence. Research shows that conflict inflicts extensive psychological harm on many refugees, particularly youth and children, which often remain unaddressed (Simpson, 2018; Bosqui and Marshoud, 2018; Dong, 2018). Refugee women are specifically vulnerable to sexual and other forms of gender-based violence and require specialized care and access to sexual and reproductive healthcare. 0 10 20 30 40 50 Percent 60 70 80 90 100 Hosts Refugees Hosts Refugees Hosts Refugees Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Eritrean Somali South Sudanese 8 to 14 years 15 to 18 years Need to work Unable to cover education expenses (fee and materials) School too far Too young Marriage or pregnancy Family not willing Sickness/injury or natural or human calamites Negative perception towards the benefit of education Other Figure 2.14: Reasons for not currently attending school Source: World Bank Staff based on SESRE 2023. Sociodemographic Profile 18 Access to essential health services when and where refugees need them is crucial for allowing them to restart their lives. Refugees need access to treatment and preventive care during health emergencies, the importance of which manifested

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

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Input: In 2008, trained enumerators conducted face-to-face interviews in local languages with 26, 513 respondents across 19 countries. 5 The sample is designed as a representative cross-section of all citizens of voting age in a given country. The dataset used for this paper has a multilevel structure; individuals are nested within primary sampling units (PSUs), which are nested within countries. The PSUs are the smallest, well-deﬁned geographic units for which reliable population data are available and they tend to be socially homoge- nous, thereby producing highly clustered data. In most countries, these will be Census Enumeration Areas (Afrobarometer, 2005, 37-38). Although re- spondents were not sampled based on their ethnic aﬃliation, there is likely to be a high level of clustering in the dataset around ethnicity. In other work, I discuss the advantages of multilevel modeling (Levi and Sacks, 2009). Treating the dependent variable as a binary outcome and taking into account the multilevel nature of our data, I estimate random intercepts for 5I excluded Zimbabwe from the analysis because of missing data on key variables. 9 Usage context: supporting mention, background mention, primary mention.

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Input: Some data challenges common to refugees and IDPs Irrespective of the specific questions related to refugee and IDP data, there are also general questions that refer to the forcibly displaced in general and that are distinct from data collection of regular populations or even migrant populations. We explore here selected issues including sampling, unit of analysis, welfare measurement, multidimensional aspects, and the measurement of risks and vulnerabilities. Sampling. As mentioned, the UNHCR is really the only statistical agency for refugees and the UNHCR registry the only population census. As for any other populations, sampling requires the preparation of a master sample that derives from the population census. With various degrees of knowledge and accuracy, this is also what happens with refugees. However, the master sample is more difficult to construct than for regular populations because refugees live in camps and outside camps and are diluted in a host population with different types of arrangements. Some households rent, others stay at relatives ’ places, other live in makeshift shacks and others stay in camps. The information available in the UNHCR registry (the census) can also be quite inaccurate, as already discussed, and the degree of accuracy changes for different groups of refugees. Stratification by urban and rural areas, a typical approach in sampling, may mean little for a population that is mostly in urban areas whether in camps or outside camps. Refugees and IDPs are also mobile and more difficult to track over time than other populations. Several statistical institutes worldwide have developed methodologies to track and measure mobile populations such as herders, nomads or homeless people. However, tracking refugees from other countries has been in the Usage context: supporting mention, background mention, primary mention.

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Input: 7 other disciplines it is relatively rare. A review of published public health literature by Chen et al. (2018) found most surveys use probabilistic designs in the first stage, but random walk or similar methods in the second stage. Lupu and Michelitch (2018) suggest that the combination of random walk and quota sampling is the common approach for political science-themed surveys conducted in the developing world, with 77 percent of respondents to their expert survey using a variation on this design. Diaz de Rada and Martínez (2014) compare a combination of random walk and quota sampling (based on age and gender) to probability designs and find a more accurate estimation of age and educational attainment in the combined method than in the probability methods, but that the probability methods perform better for measuring unemployment. The authors cite the replacement protocols for the probability methods as a reason for the bias and attribute the use of quota sampling for the success in estimating age and education, compared to the gold standard of a high-quality probability sample design. There are also a limited number of papers which directly compare two or three of the methods, but none that consider this wide range of alternatives.

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Input: This paper ’ s scope of analysis includes the country as a whole using a nationally representative survey. While regional case studies may reveal salient stresses on public services and job displacement, nationally, there is no significant impact. Over the period of 2009 to 2013, the poverty rates of host community households have stayed relatively stable near the Syrian border; despite the high poverty rates experienced among the recent migrants. By country of origin, the displacement of Syrians is one of the largest in recent history. As a result of the civil war that began in 2011, Syrians started to leave their homes and look for safety in neighboring countries across the region. By November 2015, about 4. 3 million Syrians were seeking refuge in primarily Turkey, Lebanon, Jordan, Iraq, and the Arab Republic of Egypt. 3 The only other time in the last half century that the world experienced a larger group of refugees from a single country is the case of Afghan refugees during the 1980s to 1990s. Refugee displacements of this size are rare. Consequently, they are not well studied and their impacts are not well understood. Moreover, the case of Afghan refugees in Pakistan is different, since they were stigmatized to a larger extent, which limited their movement in Pakistan. Usage context: supporting mention, primary mention, background mention.

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Input:
**3.5 Environmental and Social Risk Management**

The ESMF establishes the risk management hierarchy to be applied throughout project implementation: avoidance of adverse impacts is the primary objective, followed by minimization, mitigation, and compensation as successively lower-priority options. The ESMF includes standardized terms of reference for subproject-specific ESMPs, a template grievance intake form, and a matrix of applicable national environmental regulations cross-referenced with the relevant World Bank Environmental and Social Standards.

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Input: Children and adolescents ’ long-term exposure to households with a more equalized division of domestic labor, as a result of violent or political conflict, warrants further investigation. 2. 3 Country contexts The countries with subnational regions covered in this study, using data from 2017 or 2018, are Ethiopia, Nigeria, Somalia, South Sudan, and Sudan. All are located in Sub-Saharan Africa, have undergone or are currently involved in armed conflict, and are affected by environmental issues such as drought, famine or flooding. Despite some commonalities, each faces a unique set of social, political and economic challenges, which cannot be accurately covered in this study. However, to contextualize the findings, a brief introduction of the country context is presented alongside the poverty estimates by the $ 1. 90 / day measure and the global Multidimensional Poverty Index (MPI). 3 3 An international measure of acute multidimensional poverty, aligined with the 2030 Agenda, that captures deprivations in health, education, and living standards for more than 100 countries (Alkire and Jahan 2018; Alkire, Kanagaratnam and Suppa 2020). Usage context: primary mention, background mention, supporting mention.

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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: 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.

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Input:
CURP, respectively, was able to match 2,820 observations (40 percent of the ENILEMS

uals in the ENILEMS sample were matched to their ENLACE Grade 12 test scores. After

eliminating missing observations in the ENLACE score, the panel reaches a total of 3,714

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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.

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Input: years (Figure ES.1). Even when asked where they would realistically be in the next three years, one-third of refugees believe that they will live in a Western country (Figure ES.2). The intention to migrate abroad is higher for youth. Refugees also perceive they have less control over their lives than hosts, a result driven by South Sudanese refugees. These intentions to migrate combined with low “locus of control” (LOC) may limit refugees’ investment in improving their livelihoods or to integrate. Welfare and Equity In-camp refugees are poorer than their hosts. While monetary poverty appears to be high in refugee- concentrated areas, it is more prevalent among in-camp refugees than their hosts or OCP refugees (Figure ES.3). Welfare varies significantly over the different groups of refugees in Ethiopia, with Eritrean refugees having the lowest poverty incidence and South Sudanese refugees the highest. Although poverty incidence is higher for refugees, the high 0 20 40 60 80 Percent 100 Eritrean (camps) Somali South Sudanese OCP All Refugees Ethiopian refugee camp Ethiopian city Country of birth Other African country Western country Figure ES.1: Desired location in three years Source: World Bank Staff based on SESRE 2023. 0 20 40 60 80 Percent 100

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Input: 8 neighboring community, (iii) residing elsewhere in the Kagera Region and (iv) residing outside the Kagera Region. Table 3 shows that the basic needs poverty rate declined 8 percentage points in the full sample. This figure masks significant differences in changes between subgroups based on migration. For those found residing in the baseline community, poverty rates dropped by 4 percentage points, but rates dropped by 11, 13 and 23 percentage points for those who moved to neighboring communities, elsewhere in Kagera Region and outside the Kagera Region respectively. A similar pattern is found for consumption per capita. While consumption per capita grew by $ 65 overall, it grew by only $ 30 for those found in the same community and by $ 65, $ 100 and $ 287 for those who moved to neighboring communities, elsewhere in Kagera Region and outside the Kagera Region respectively. Dividing consumption into food and non-food components gives the same result. The most basic assessment of welfare changes would have been wrong if we had focused only on individuals still residing in the community, a practice found in many panel data surveys. We would have underestimated the growth in consumption by half of its true increase. The differences in consumption changes of groups in Table 3 are statistically significant, as shown in Table 4.

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Input:
7 Annex 9 describes the distribution of refined fuel products by overall consumption decile, based on the 2004 National Household Survey. 8 About 15 percent of the population was defined as poor in 2008.

Subsidies Capital invest't Social programs _Source: Ministry of Finance, 2008 APBN-P, assuming oil at US$95;_ _social program expenditure data from 2008 APBN._

More detailed data would enable better estimates, for example monthly data on fuel consumption in the provinces near neighboring economies and for otherwise similar provinces where fuel is more likely to only be consumed locally.

_Source: World Bank calculations based on data from the Ministry of Finance._

To explore how important is such an effect, we use the average em  ployee cost in electricity generation sector (NACE 3511) reported in AMADEUS database   maintained by Bureau Van Dijk as an approximation for labor cost of wind generation.

social program expenditure data from 2008 APBN

monthly data on fuel consumption
data from the Ministry of Finance

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Input:
There are 74,210 Sudanese refugees living in
the Benishangul Gumuz region out of which
22,649 arrived during the recent conflict in
Sudan. Long-staying refugees are located at
the Sherkole (established in 1996), Bambasi
(established in 2012), and Tsore (established
in 2015) camps. Most new arrivals cross from
Sudan into Ethiopia at Kurmuk. A refugee
settlement has been established in Ura for
the delivery of protection and assistance.

i. Kurmuk Transit Centre and Ura
Refugee Settlement in
Benishangul Gumuz (Emergency)

As per statistical data from Kurmuk Transit
Centre and Ura Refugee Settlement, 39% of
the reported incidents involved rape and
sexual assault, 47% were physical abuse, and
14% were psychological and emotional
abuse. Among the survivors, 89% are women,
and 11% are girls.

statistical data from Kurmuk Transit
Centre

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Input: 7 convincing instruments and the impossibility of implementing a randomized controlled trial forces conflict researchers to confront the limits of any identification strategy. Panel data, when available, minimize problems related to recall and ex post measures and enable researchers to trace the dynamics of conflict over time (e. g., Guerrero-Serdan 2009). Some studies have constructed panel data by resurveying households that had been surveyed before the conflict, such as Bundervoet, Verwimp, and Akresh ’ s (2009) study in Burundi and Andre and Platteau ’ s (1998) study in Rwanda. Researchers have often empirically addressed the issue of attribution of causality using difference-in-differences, a nonexperimental technique that compares a conflict-affected group (or region) with its preconflict situation and with a control group (or region) that did not experience the conflict. The validity of this method is contingent on no other changes between the two groups (regions) at the same time as the exposure to conflict. Even if there are no other changes, there may be spillover effects from the conflict-affected group to the nonconflict control group, leading to an underestimation of the effects of conflict. Usage context: supporting mention, primary mention, background mention.

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Input: expect the prices of many manufactures to do as well. The 1995 / 96 NLSS collected information on the quantity and price paid for rice by individual households. From this we compute a unit price per Kg. The log of the district median is used as our price index proxy. To construct an index of housing costs, we take advantage of a section of the 1995 / 96 NLSS survey focusing on housing. The survey collected information on hypothetical and actual house rental values of each household together with house characteristics such as square footage, number and type of rooms, quality of materials, and the availability of various utilities. We use these data to construct an hedonistic index of housing costs for each district. Let rk s be the house rental price paid (or estimated) by household h in district s and let xh s denote a vector of house characteristics. We estimate a regression of the form: log rk s = as + bxh s + ek s to obtain estimates of eas, the housing cost premium in each district s. Regression results are shown in Table A1 in appendix. Many house characteristics are signiﬁcant with the expected sign, e. g., larger, better built houses with better in-house amenities are worth more. District price diﬀerentials are large and jointly signiﬁcant. Usage context: background mention, supporting mention, primary mention.

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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: Addis Ababa. Many refugees report that social interactions and sharing resources with hosts is “not easy,” especially in the South Sudanese domain. Overall, 30 percent of refugees say it is not easy to have social interactions with hosts, and 34 percent report that it is challenging to share resources such as water and food. These rates fall to 21 for social interaction and 15 percent for challenge in sharing resources in the South Sudan domain. On the other hand, refuges do not report that it is difficult to conduct market interactions. Country-wide, the relationship between integration outcomes and demographic characteristics is complex. More-educated male refugees are more likely to have Ethiopian friends, but this does not appear to improve ease the creation of social interactions or sharing resources with hosts. The results in Column 2 of Annex D, Table D.19 show—controlling for other characteristics, including region and year of arrival—that refugee men are 6.7 percentage points more likely to have an Ethiopian friend than refugee women, and those who completed secondary education are 22 percentage points more likely to have an Ethiopian friend. However, no significant difference exists in the ease of which these groups find it to have social

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Input:
**SIGAF Reconciliation Status**

As of 31 December, cumulative project expenditures recorded in SIGAF amount to USD 14.7 million across all disbursement categories. This figure reconciles to within USD 12,000 of the Bank's Client Connection disbursement records, a variance attributable to timing differences in exchange rate application. The SIGAF balance will be reconciled in the first week of January following the receipt of the final bank statement for the Designated Account. No unexplained variances were identified in the year-end SIGAF reconciliation.

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Input: As a result, imputed poverty is measured as income poverty. Another advantage of using the LFS is the availability of CPI at the NUTS2 level in Turkey which allows for spatial deflation of different price levels across the country. Table 1. Survey Comparison and Data Availability Years Available Migration Variables Income or Consumption Geographic Identifier Spatial Deflation HICES 2003-2012 No Consumption, income National, urban / rural No SILC 2009-2012 No Income NUTS1 No LFS 2009-2013 Yes Imputed Income NUTS2 Yes However, there are other issues for consideration when using the LFS. Principally, there is a low number of sample points that are migrant households. Moreover, the study cannot identify migrant households and individuals that are specifically Syrian refugees. Foreign migrants are defined as those who were born abroad and have lived abroad for at least more than 12 months. Some Turkish-born households have also lived abroad for over a year, and these individuals are not considered to be migrants. Amongst foreign-born individuals, only the ones who have been in the country for more than 12 months are included in the sample which underrepresents the actual number of foreign migrants in the region. In addition, no specific procedure is adopted by the enumerators if the household does not speak Turkish. Given that a majority of Syrian refugees do not speak Turkish, the language barrier might result in the removal of Syrian households from the sample. Finally, refugee camps are not included in the sample frame, which limits the study to only examining recent migrants who do not live in refugee camps. 9 Wage income is only available for regular and casual employees in the LFS which accounts for around 60 % of total employment. There is no other monetary income value for the rest of the working population.

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Input: nizations such as UNHCR, and national and international non-governmental organizations. Data is compiled from a number of sources, including but not restricted to individual registration of refugees and asylum seekers (information typically includes name, gender, date of birth, country of origin, marital status, and place of displacement), tracking of population movement in situa- tions where the movement is ﬂuid or continuous, standardized surveys such as Living Standards Measurement Study (LSMS) surveys, Labor Force Surveys (LFS), Demographic and Health Sur- veys (DHS), and Multiple Indicator Cluster Surveys (MICS), administrative records and registries. Yet, data collection is a difﬁcult exercise, due to both methodological issues (UNHCR 2014) and practical challenges, especially in situations of heightened insecurity or mass refugee situations. To date, UNHCR maintains the most comprehensive statistical database under a uniform methodology. UNHCR publishes annual data on refugee ﬂows and stocks by countries of resi- dence and origin dating back to 1951, shortly after the Ofﬁce was established. UNHCR publishes annual statistical reports ranging from “ Global Trends ”, “ Mid-year trends ”, “ Asylum trends ”, to a “ Statistical Yearbook ”. There is a consensus that these data provide the most reliable source of information (Sarzin 2016). Usage context: background mention, supporting mention, primary mention.

Labor Force Surveys
Living Standards Measurement Study
Multiple Indicator Cluster Surveys

individual registration of refugees and asylum seekers

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Input: The large number of interconnected conﬂicts in these provinces involving non-state armed groups and state actors create a continuous ebb and ﬂow of displacement in eastern DRC (Jacobs & Kyamusugulwa 2018). In June 2020, UNHCR estimated that over 4. 5 million persons were internally displaced in Ituri (1. 6M), North Kivu (1. 9M) and South Kivu (1M) provinces alone (UNHCR 2020). DRC hosts an additional 536, 000 refugees (UNHCR 2020) from neighboring countries with recent experiences of violence, especially Burundi, Uganda, CAR, and South Sudan. Figure 2 plots the trend in the new IDPs in the DRC between 2009 and 2020. 5 Most IDPs in DRC favor staying with host families as opposed to camp displacement (Haver 2008, Rohwerder 2013). In 2017, UNOCHA estimated that around 500, 000 IDPs were in camp- like settings, whereas 3. 3 million sought refuge in host communities (Jacobs & Kyamusugulwa 4The qualitative analysis covers only the Kivu provinces, but the quantitative analysis covers all three. 5Data provided by the Internal Displacement Monitoring Center DRC Page, accessed May 14, 2021. 6

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Input: DiD estimate is (E (𝑌 ௜ ଵ | 𝐷 ௜ ൌ 1ሻ- E (𝑌 ௜ ଴ | 𝐷 ௜ ൌ 1ሻ) – (E (𝑌 ௜ ଵ | 𝐷 ௜ ൌ 0ሻ- E (𝑌 ௜ ଴ | 𝐷 ௜ ൌ 0ሻሻ ൌ ሺ 𝛽 ൅ 𝛿ሻ െ 𝛽 ൌ 𝛿. The DiD estimator relies on the “ Equal Trend Assumption ” that does not require both selected and non-selected youth to be on average balanced at baseline on key observable & unobservable characteristics. Table 1 shows that both groups differ on some key characteristics. Non-selected youth are more likely to be older, more educated (hold more academic degrees), come from Beqaa and Nabatiye, and have parents with intermediate education (grade 7 to 9). Selected youth are more likely to be males, younger, students, come from Mount Lebanon and the North, and have mothers with university education. Both groups appear balanced on key outcomes related to soft skills, tolerance values, and labor market outcomes. The exception is that non-selected youth exhibited a better sense of belonging to the Lebanese community and selected youth were more likely to have been unpaid employees (interns) at the time of baseline data collection. In addition to comparing means of observable characteristics, the study also tested for the differences in the statistical distributions of key outcomes using two sample Kolmogorov-Smirnov tests of the equality of distributions. Results indicate that the only key outcome for which there is a statistically significant difference in its distribution between the treatment and comparison groups at baseline is the sense of belonging to the Lebanese community. The largest difference between the distribution functions in the direction that the comparison group contains larger values 10 Standard errors are clustered at the NGO level because that was the unit of allocation into treatment and comparison groups. Abadie et al. 2017 argue that clustering is generally needed even if NGO fixed effects are included in the regression. Usage context: primary mention, supporting mention, background mention.

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Input: expect the prices of many manufactures to do as well. The 1995 / 96 NLSS collected information on the quantity and price paid for rice by individual households. From this we compute a unit price per Kg. The log of the district median is used as our price index proxy. To construct an index of housing costs, we take advantage of a section of the 1995 / 96 NLSS survey focusing on housing. The survey collected information on hypothetical and actual house rental values of each household together with house characteristics such as square footage, number and type of rooms, quality of materials, and the availability of various utilities. We use these data to construct an hedonistic index of housing costs for each district. Let rk s be the house rental price paid (or estimated) by household h in district s and let xh s denote a vector of house characteristics. We estimate a regression of the form: log rk s = as + bxh s + ek s to obtain estimates of eas, the housing cost premium in each district s. Regression results are shown in Table A1 in appendix. Many house characteristics are signiﬁcant with the expected sign, e. g., larger, better built houses with better in-house amenities are worth more. District price diﬀerentials are large and jointly signiﬁcant.

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Input: A significant increase in non-participation among men can be clearly seen in the West Bank in 2020Q2, mostly at the expense of the private infor- mal sector. The labor market then quickly bounces back. By 2020Q3, labor market stocks in the West Bank appear indistinguishable from pre-pandemic periods. Gaza, on the other hand, experienced three consecutive quarters of depressed employment from 2020Q2 to 2020Q4. Non-participation spiked twice, first in 2020Q2 and then in 2020Q4, corresponding respectively to the initial lockdown orders and the subsequent outbreak in Gaza. Recovery also appears to be slow and uneven. Figure (3) shows the labor market flows. We exploit the specific panel structure of the LFS dataset, described in Section 3. 1 by focusing on one cohort of the same respon- dents who were surveyed in 2019Q1, 2019Q2, 2020Q1, 2020Q2, and finally 2020Q4. This cohort of individuals allows us to observe labor market transitions into the pan- demic; to compare with a period over the same quarters in 2019; and, finally, to observe their recovery outcomes in 2020Q4. Overall, Figure (3) shows two labor markets with high levels of churning. On average, 29 % of individuals in the sample would change their labor market states after just one quarter. These churns are especially prominent between informal employment and unemployment, and in Gaza between unemployment and non-participation. The figure also illustrates the significant differences between the West Bank and Gaza in labor market dynamics, differences already observed in the labor market stocks presented in Figure (1). In addition to the significant flows between unemployment 11

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

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

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

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

Pesquisa Nacional por Amostra de Domicílios Contínua (PNADC)

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Input: 40 Sub ‐ Saharan Africa 8604000 5895000 7055000 5406100 5068000 N. A. MENA 6230000 8000000 6675000 8592900 10892000 N. A. Asia and Pacific 4325000 2405000 3392000 2128800 5490000 N. A. (excl. Australia, Japan, New Zealand) Americas 1126000 1280000 2176000 2900000 3661000 N. A. (excl. North America) Note: Refugee data are from the UNHCR statistical population online dataset, accessed in September 2014. Refugee data from 2007 to 2013 include people in refugee ‐ like situations (see note, Figure 1). IDP data from 1990 to 2008 are aggregated based on Center for Systematic Peace (http: / / www. systemicpeace. org /). As indicated in Figure A1, these data are much lower compared to those provided from 2003 by IDMC but provide a longer time series. UNHCR assisted ‐ IDP are compiled based on several UNHCR (1995, 1996, 2007, 2008, 2009, 2010, 2011, 2012, 2013, and 2014) reports. UNHCR ‐ assisted IDPs are only IDPs who are protected / assisted by UNHCR. These are also not necessarily representative of the entire IDP population in a given country. Many of the world's IDP situations are not covered by UNHCR and are thus not reflected. Usage context: background mention, primary mention, supporting mention.

UNHCR statistical population online dataset

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

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Input: household. The dependency ratio— the ratio of dependents of those under age 15 and above age 64—to working members in a household, is also higher for in-camp refugees relative to hosts and highest among South Sudanese refugees. OCP refugees have the smallest average household size and the lowest dependency ratio. Refugee households are more likely to be headed by women. The share is exceptionally high for South Sudanese refugees, where 84 percent are female-headed (Annex D, Table D.1). This reflects a large share of women (71 percent) aged 25 to 44 among South Sudanese refugees (Annex D, Figure D.1). Refugees have younger household heads than hosts, except for Somali refugees, with the youngest household heads in Addis Ababa. -60 -40 -20 0 20 40 60 -60 -40 -20 0 20 40 60 <15 15 to 24 25 to 44 45 to 64 >=65 In camp refugees In camp hosts Percent Percent <15 15 to 24 25 to 44 45 to 64 >=65 Addis refugees Addis hosts Figure 2.4: Age structure Source: World Bank Staff based on SESRE 2023. 49% 48% 45% 45% 47% 47% 51% 52% 55% 55% 53% 53% 0 20 40 60 80 Percent 100 Hosts Refugees Hosts

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

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Input: In terms of geographical coverage, this study covers all low-income and middle-income countries with a significant presence of refugees, other Venezuelan refugees and migrants 11 in need of international protection, and / or IDPs. We apply 100, 000 (in terms of the number of FDP as of 2021) as an inclusion threshold for this analysis. This results in the final list of 53 low-income and middle-income countries, which altogether account for 23 million refugees and 58 million IDPs. 12 3. Methodology The methodology we apply to analyze micro-level datasets in the UNHCR and WB MDLs follows a procedure that is systematic, replicable, and scalable (Figure 1). First, we scrape the metadata from all the micro-level datasets found on the UNHCR and WB MDLs. 13 We find 412 datasets from UNHCR MDL and 1, 927 datasets from WB MDL that have been collected in the sample of countries under study. Second, we remove false positive datasets from the UNHCR MDL. While a large majority of datasets in the UNHCR MDL are individual / household-level household survey datasets sampled from refugees or IDPs, some are not. Furthermore, many datasets do not have a clearly defined sampling frame from which a representative sample can be drawn, thus failing to meet our inclusion criteria for this exercise. Usage context: primary mention, supporting mention, background mention.

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Input: The 2024 survey data collection protocol required the field team to conduct back-checks on 15 percent of completed interviews within 72 hours of the original interview. Back-checks were conducted by telephone where network coverage permitted and in person where phone contacts were unavailable. The back-check process identified three enumerators with unusually high rates of interview fabrication; these enumerators were dismissed and their questionnaires invalidated. The affected questionnaires were re-administered to the same households by verified enumerators within five days.

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Input: In the case of refugees, host countries rarely facilitate naturalization, only a minority of refugees ever gets resettled in third countries and voluntary repatriation is frequently not a realistic option for several reasons. International law provides for three possible durable solutions for refugees, including integration within the area of displacement, repatriation to their home country or resettlement in a third country; refugee status can also cease when there are no longer compelling reasons for an individual to refuse to avail themselves of the protection of their country of origin. In 2015 only 119, 265 refugees under UNHCR ’ s mandate were either resettled, naturalized53 or ceased to be refugees; and there were only 201, 415 voluntary returns, mostly Afghanistan, Sudan, Somalia and CAR (see Figure 17). These statistics highlight the significant gap between the unprecedented numbers of refugees and the capacity of the international community to provide durable solutions. For the 85 percent of refugees hosted in developing countries, there are only minute prospects for resettlement. Figure 17: Durable Solutions Relative to Refugee Stock 2015 Source: UNHCR Global Trends 2015 Global statistics that show the low rate of refugee returns masks the variation in returns over historical periods and across displacement crises — with significant voluntary returns for some countries.

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Input: Challenges around skill mismatch exacerbate exclusion, as many young Lebanese lack the skills and competencies demanded by private sector employers, particularly ‘ soft skills ’. To address some of these challenges, the Lebanese government (GOL) identified volunteerism as a mechanism to enable diverse youth to work together for improved community assets and service delivery as well as increased employability. In September 2012, the GOL issued a Decree (Number 8924 / 2012) that created a new extra curriculum program that requires secondary school students to complete 60 hours of civil work. In addition, the Ministry of Social Affairs (MOSA), through its Volunteering Department, launched annual action plans for the implementation of youth volunteer summer camps across Lebanon. 4 Father ’ s education and residence (region and location of school) are the two largest contributors to inequality of opportunity in students ’ math test scores, accounting for 44 and 23 percent of total inequality, respectively (World Bank, 2016). 5 According to the 2013 Gallup Poll, 90 percent of respondents in Lebanon agreed with the statement that knowing people in high positions is critical to getting a job. Usage context: primary mention, background mention, supporting mention.

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Input:
We also use a project level database constructed from provincial and central

However, the household survey was designed in view of combining it with the nationally representative 1998 Vietnam Living Standards Survey (VLSS) to predict baseline consumption expenditures for SIRRV households (van de Walle, 2006).

We then compare this to the independent administrative data on the aggregate allocation.

1998 Vietnam Living Standards Survey
VLSS

project level database
independent administrative data

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Input:
_Source: UNHCR Internal movement of refugees in Sudan as of 16 July 2023_

_4 See Sudan Protection Brief, June 2023 and UNHCR Sudan- Overview of refugees and asylum seekers distribution and_

_movement in Sudan Dashboard as of 16 July 2023_

UNHCR 4

UNHCR Internal movement of refugees in Sudan

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Input:
of data is the National Water Commission; the data consist of daily rainfall measures in

Third, we use the geographic location data of electoral sections obtained from the Department of

elections in 2000 and 2006 by electoral section are public from the Federal Electoral Institute

(IFE) website. In addition to these, we use complementary information on socio-demographic

characteristics of municipalities from the 2000 Population Census and the 2005 Short Census or

2000 Population Census
2005 Short Census

geographic location data of electoral sections

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

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

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

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