Input: to the Venezuelan migratory crisis, whereas the VenRepPS survey was conducted during the pandemic in 2020. These temporal inconsistencies result in varying sample composi- tions across surveys, diverging from the landscape we observe in 2022. Notably, forced migrants in the VenReps Kids survey migrated during the crisis but have since remained in the country for several years, potentially leading to disparities in household integration outcomes. IV GENERAL DESCRIPTIVE STATISTICS IV. A Key characteristics of adults Table 2 provides descriptive statistics for the adults in our study, encompassing the pri- mary caregiver, mother and father (if residing with the child), and the individual finan- cially responsible for the child (should they be different from the aforementioned per- sons). Typically, the roles of primary caregiver and financial provider are fulfilled by either the mother or the father. The table is organized into three panels for clarity: Panel A details key individual characteristics, Panel B outlines adults ’ access to services, and Panel C focuses on labor market characteristics. Within the table, columns (1) and (2) present average values for adults from Colombia and Venezuela, respectively, while the final column displays the results of mean difference tests between these two groups, with standard errors noted in brackets. Usage context: supporting mention, background mention, primary mention.

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Input:
**Annex 1**

**Demographics information.**

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

**Are you from the Host community or**

**IDPs?**

**Internally**

**displaced**

**person …**

**Host**

**Community**

**53%**

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

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

**Marital status of interviewee**

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

Married Single Widow Divorced Seperated

**16**

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Input: These data are only for three districts in the province of Punjab, but is very recent, was conducted by an independent team of academics, and is a complete census of all households in the selected villages. Consequently, it yields sufficient madrassa enrollment to examine correlations with household attributes in a meaningful manner (this data source provides information on four times as many children as the PIHS). Table A2 in the appendix shows how these different data sources are used in the paper. Each source asks about madrassa enrollment in a slightly different but comparable way. The population census (1998) asks about the field-of-education (“ What is name ’ s field of education? ”) with options that include (for instance) engineering, medicine, or religious education. This question is also asked of all literate adults irrespective of their current enrollment status, allowing for comparisons in the stock of religious education over time. The PIHS rounds ask, “ What type of school is name currently attending? ” with options that include government school, private school, or deeni-madrassa (religious schooling). Finally, the LEAPS census directly asks, “ Is the child enrolled in a madrassa or an Islamic education school? ” Fortunately these different questions all give rise to similar numbers. This is reassuring since it suggests that any one particular result is not driven by the specific question or definition that was used. 7 This is complemented with the census of private schools carried out by the Federal Bureau of Statistics in 2000 (www. statpak. gov. pk). Usage context: primary mention, supporting mention, background mention.

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Input: Because of this, the program impacts on control over resources were small, albeit statistically significant: 80 percent of respondents at baseline said they controlled their own resources, with a seven percentage point increase for the treatment group (relative to control). Similarly, 80 percent of those engaged in income-generating activities said that they controlled the money they earned. The midline results indicated that among the treatment group, this had increased by roughly eight percentage points. As shown in the second panel, EPAG graduates report that they worry less than those in the control group. They are less likely to worry about their jobs or incomes or that they won ’ t be able to pay for basic necessities, and those with partners are less worried about their relationships breaking up. The impact on subjective well-being, as measured by a series of questions about the respondent ’ s satisfaction with various dimensions on her life, indicate that EPAG was most 20 See for example Ashraf et. al. (2010); Morcos and Sebstad (2010); and Austrian and Ghati (2010). 21 “ Formal ” loans are those from banks, credit groups, susu, or money lenders; “ informal loans ” are those from parents, friends, relatives, or business partners. 16 Usage context: background mention, primary mention, supporting mention.

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Input: In 2003, almost 60 % of young girls and 40 % of young boys had no formal schooling (ILO / UNICEF 2005). Data from the Demographic and Health survey shows that more than 40 percent of adult women have no education, compared to fewer than 20 percent of men, while 23 percent of women and 44 percent of men have some secondary schooling (DHS 2007). Happily, access to education is rising rapidly, especially for girls: according to the Liberian labor force survey from 2010, the ratio of girls to boys enrolled in primary school has risen from 72 in 2000 to 90 in 2009. Enrollment levels and sex ratios are lower among older children and youth, as they become increasingly engaged in 1 Both are unweighted averages; Barro-Lee comprises 32 countries with data from 2010; Edstats comprises 43 countries with data from 2007-2011. 2 Defined as without work, available for work, and actively looking for work (LISGIS 2010). 2

Barro-Lee
Demographic and Health survey
Liberian labor force survey
Edstats

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Input: Disaggregated data on IDPs who are not protected or assisted by UNHCR are collected by other agencies, including IOM, but data are not comprehensive and therefore not published in IDMC ’ s global reports. 93 The difficulties of collecting disaggregated data on locations of IDPs are compounded by the fluidity of IDP movements — IDPs might suffer multiple displacements or they might resort to changing locations as a coping strategy (e. g. moving between their homes and place of displacement or testing different locations before deciding where to stay) (Brookings 2011). In recent years, efforts have been made to improve data collection for IDPs living outside of camps by employing a range of techniques including: (a) profiling; (b) household surveys; (c) collecting information on IDPs who come to camps to visit family members or collect relief items; and (d) community outreach programs (Brookings 2013). Usage context: background mention, supporting mention, primary mention.

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Input: World Bank team undertook field supervision, providing on-time and on-the-spot guidance for the field teams whenever and wherever they encountered a challenge. (e) Challenges faced and lessons learned The SESRE served as a learning experience for including refugees in future rounds of the official household survey (HoWStat). Given the unique feature of refugees compared to Ethiopians, the sampling methodology for the SESRE is unique for sampling refugees. Therefore, SESRE successfully tested the feasibility of sampling refugees and their hosts. To ensure the successful implementation of the sampling procedures, the ESS implemented a pilot sampling methodology before data collection started to ensure that all systems and processes were functioning. The ESS and World Bank teams conducted field visits for this pre-test in Afar and Addis Ababa. The field visits included discussions with camp community leaders, including the refugee community leaders, about the upcoming survey to understand better any sensitivities that may arise. The field visits helped to understand the camp administrative structure and environment of the teams facilitating the camp and to test the accessibility of sampled refugee households inside the camp, in Addis Ababa, and the identification of the host. ESS provided detailed feedback on the fieldwork procedures and adjustments

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Input: There is one limit to our approximation in Equation 4. The ethnic composition of refugees in each year t for a given origin – destination pair of countries obtained from the EPR-ER database is assumed to be homogeneous across camps of the same origin – destination pair of countries for the refugees at year t. This may seem to be a strong assumption; however, the risk of misallocating refugees is reduced as the annual variation in the EPR-ER is generated by just a few dominant groups for a given origin – destination pair and the geographical distribution of refugees by country of origin is highly influenced by the proximity to their countries of origin. 16 As can be seen from panel A of Table B. 2, in refugee-hosting areas, on average, both EF and the EP seem to increase quite significantly when they are revised by incorporating the number of refugees in an 80-km buffer: the mean value of the standard EF index is 25. 58 %, while the mean value of the revised refugee EF index is 37. 90 %. The mean value of the standard EP index is 10. 11 %, while the mean value of the revised refugee EP index is 14. 07 %. Usage context: supporting mention, background mention, primary mention.

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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: background mention, primary mention, supporting mention.

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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: Chew et al. (2018) use a baseline convolutional neural network model on a gridded population sampling frame to select a sample of households in Nigeria and Guatemala. The authors found this technique to be on par with human canvassing in terms of accuracy, and to outperform other machine learning models based on crowdsource or remote sensing data. Grais et al (2007) compared an unweighted random point selection methodology to a random walk in their study of vaccination rates in urban Niger. The authors do not find statistically significant differences between the methods, though the sample size was limited and both methods were non-probabilistic. 3. Design and Field Protocols 3. 1. Experiment Design This paper makes use of a dataset from the purposefully designed methodology experiment conducted in one section of the Protection of Civilians site 1 (PoC1, Figure 1), one of the largest IDP camps in Juba, South Sudan. To generate a gold standard as the basis of comparison, a household census was conducted between August and September 2017. During this exercise, 2, 655 households were interviewed using a questionnaire designed to collect demographic information, dwelling characteristics, household consumption, and perception data. At the end of each census interview, households received a unique barcode that could be used to identify them later in the experiment.

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Input: The panel database was constructed by merging administrative enrollment records with survey data collected at baseline for a representative sample of 1,800 households. Individual household identifiers were assigned at enrollment and used to link administrative and survey records throughout the panel. The panel database is maintained by the evaluation firm and stored on encrypted servers with access restricted to the principal investigator and designated data analysts. De-identified extracts from the panel database will be provided to the Bank's task team for independent verification of reported outcome changes.

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Input: The relation- ships between displacement dynamics and perceptions of each manifestation of social cohesion are analyzed separately by running 12 models for each independent variable (6 regressions for each sample). The regressions are correlations and should not be interpreted causally. Hosting status and displacement ﬂows are likely related to perceptions of social cohesion in indirect ways and the structure of the survey data limit the ability to specify the channels through which these relation- ships run. Each regression controls for characteristics that may inﬂuence respondents ’ perceptions of social cohesion outside of the presence of IDPs or refugees in the local community such as province, gender, age, marital status, level of education, employment, and exposure to violence. 11Poll numbers correspond to the number wave in our larger project, as described and shown in Table 2. 28

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Input:
HIV behavioural surveillance surveys 149

Table I. Internationally accepted key BSS indicators.

Knowledge International standard

Prevention Percentage of young women and men
aged 15 �24 years who, in response to
prompted questions, say that:
1) people can protect themselves from
contracting HIV by having sex with only one
faithful, uninfected partner. [a]

UNGASS, MDG, PEPFAR

2) people can protect themselves from UNGASS, MDG, PEPFAR
contracting HIV by using condoms. [a]

Misconceptions Percentage of young women and men
aged 15 �24 years who, in response to
prompted questions, correctly reject that:
1) A person can get HIV from mosquito UNGASS, MDG, PEPFAR
bites. [a]

2) A person can get HIV from sharing a UNGASS, MDG, PEPFAR
meal with someone who is infected. [a]

General Percentage of young women and men
aged 15 �24 who, in response to
prompted questions, know that:
1) A healthy-looking person can have UNGASS, MDG, PEPFAR
HIV. [ab]

Attitudes

Care and support The number of respondents who report
an accepting or supportive attitude of:
1) Would be willing to care for a family
member who became sick with the AIDS
virus.

PEPFAR

2) Would buy fresh vegetables from a vendor PEPFAR
whom they knew was HIV�/.

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Input:
twins) variation on 6th grade ENLACE, identifying, therefore, the relationship between

as captured by ENLACE, on future outcomes and the (within-family) individual-level

characteristics. In the ENLACE panel, this last specification uses the sample of students

who answered the ENLACE context questionnaire to control for differences in household

ENILEMS-ENLACE panel regressions, _Xi_ _[′]_ [includes] [upper] [secondary] [school] [grade] [point]

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

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

2017/18 Household Budget Survey
Household Budget Survey

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Input:
FAO (2012) being the latest. More recently, the FAO indicator is used to track progress toward the first

country. [2] Combining this with population data allows the FAO to estimate the total kilo calories available

number of HCES. [3] For most countries the CV was kept constant across years and only the mean was

revised. [4] Finally, the FAO estimates the required energy of a population by determining age-sex specific

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Input:
**3.3** **Open Street Map (OSM) Road Network Data Set**

In addition to the five public transportation networks, we also added the drive as well as the pedestrian network leveraging the Open Street Map data set to account for commuters who walk or drive to work.

**3.4** **Fathom Flood Maps**

<!-- PAGE 10 --> Pluvial and fluvial flood maps from the Fathom global flood model were first clipped to the bounding box [9] of the Kinshasa city and then mosaiced together using the maximum operator so that the maximum flood depth from both fluvial and pluvial flood estimates were preserved.

Flood models are an integral tool for understanding and managing flood risks on transportation networks. In
the past decades, increased computing power and precision of remote sensing data sets have led to the
development of multiple global flood models (Bernhofen et al., 2018; Wood et al., 2011). Among them, the
lastest flood map products from Fathom (A. Smith et al., 2015) are selected to provide flood depth and extent
estimates in Kinshasa for the following reasons: 1) the map products from Fathom have relatively high
spatial resolution (90 meters) which is sufficient for this study given the geographic extent of the Kinshasa
city; 2) flood extent and depth estimates for both pluvial and fluvial floods under 10 return periods [8] are
included in this data product; 3) it uses 2D hydrologic flood model which is more advanced in mapping flood
plain and modeling dynamic water flows.

Open Street Map (OSM) Road Network Data Set

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Input: In practice, most of those approved for the OCP have family and friends in Ethiopia who support them with remittances—fewer than 1,500 OCP work permits were issued by 2022. The permit allows refugees to freely move and establish residence in all areas of the country except restricted areas. OCP refugees are systematically different from in-camp refugees, as seen in their livelihood strategies. Therefore, the remainder of this chapter divides the analysis between in-camp refugees and OCP refugees. 3.1 Labor market outcomes of in-camp refugees and their hosts In-camp refugees have high inactivity rates (not working or unemployed) and low labor force participation. Table 3.1 shows that only 31 percent of all in-camp refugees aged 15-64 “participated” in the workforce (in the week before the survey), meaning they were employed or available to work and actively searching (strict unemployment). This compares to 52 percent for hosts. This figure increases to 43 percent for refugees and 57 percent for hosts if you include all available to work regardless of whether they are searching (relaxed unemployment). The remaining 57 percent of refugees are inactive, and just over half are currently in school, leaving 23 percent of refugees neither working nor studying, compared to

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Input: Impacts on the labor market are unclear; initial research suggests that there has been a supply shock to informal labor markets. This has had a large-scale impact on the employment of natives in the informal sector. At the same time, research suggests there has been a boost to formal employment for the Turks, but this has been uneven: the low educated and women experience net displacement from the labor market and, together with those in the informal sector, declining earning opportunities.  The “ Socio-economic Assessment of the Impact of Syrians under Temporary Protection (SuTPs) on Turkish Hosting Communities ” [ongoing], to be undertaken in partnership with the Government of Turkey, will include a nationally representative household survey with SuTP and local Turkish households including camp and non-camp environments. The questionnaire will cover welfare (assets, income, expenditure), municipal services, labor and employment, education, social networks and quality of life. F. Options to improve forced displacement statistics Significant efforts are needed to enhance the reliability, comparability, quality and scope of the global data on forced displacement. In particular, more robust estimates are needed of the scale (stocks, flows and locations) and typology (demographics, location and accommodation) of forced displacement crises. This requires substantial improvements in the rigor of data collection and compilation methodologies including: (a) Harmonization of definitions and methodologies used in the collection and analysis of statistical data on forced displacement — covering stocks and flows of refugees, asylum- seekers and IDPs — to ensure comparability across regions and countries;

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Input: camp refugee households with improved bathing facilities36 is low, especially among Somali refugees and their hosts. In addition, few refugee and host households have a place or item designated for hand washing in their dwellings. Availability of water or detergent for hand washing is low, especially among refugees (Annex D, Figure D.15). Regarding rented homes, OCP refugee households live in houses with better bathing facilities (82 percent) than hosts (66 percent). Also, around 80 percent of refugee and host households in Addis Ababa have a place for hand washing, and more than half of refugees and hosts have water or soap. 32 Overcrowding occurs when if more than three people live per room (UN-Habitat). 33 Improved wall is made of stone & cement, blocks-plastered with cement or bricks. 34 Improved roof is made of corrugated iron sheet or concrete/cement. 35 Improved sources of drinking water are piped, bottled, sachet, or 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

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Input: 23 86 % of the IDPs, 91 % of the refugees and 88 % of the returnees are confident or fully confident that a coalition like this would be capable of providing security. Source: Listening to Displaced People Survey, 2014. In an open-ended question on who can be trusted most when it comes to ensuring security in the North, survey results suggest that the majority of refugees in Mauritania (86 %) trust the armed rebel groups as opposed to the army or police. This does not hold for refugees in Niger of whom 75 % trust the army and police. Similar results hold for IDPs and returnees, who put much more confidence in state authorities when it comes to securing the North: most trust is placed in the army and police (72 % of the IDPs and 66 % of the returnees) while little to no trust is placed in armed rebel groups (3 % of IDPs, 1 % of returnees). Usage context: primary mention, supporting mention, background mention.

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Input: Most papers with few exceptions use standard OLS estimators or some of its variants (Table 2). Two papers use general equilibrium models (Bodvarsson, Van den Berg, and Lewer 2008; Hercowitz and Yashiv 2002) and two papers simply compare means between treated and non-treated groups resulting in simple difference estimations (Card, 1990 and Alix-Garcia and Bartlett, 2015). [Table 2] The unit of observation varies depending on the data at hand. Most studies rely on household survey data where individuals or households are the unit of observations and most studies include some regional dimension (more frequently administrative areas). Where longitudinal or panel data are available time is also included. Other choices for unit of observations include skills or education level, various types of population groups (based on gender, age etc.), and, in a few cases, economic sectors, industry or labor market segments. The use of fixed effects varies. Some papers use the full set of parameters depicting units of observation (for example, household, region and time fixed effects in equations where the unit of observation is constructed using household, region and time). Other papers use subsets of these parameters whereas other papers introduce variables that are not used to identify the unit of observation. Usage context: supporting mention, primary 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: 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 10631 This paper aims to understand the existing gaps in micro- level data on forcibly displaced people — refugees and internally displaced persons. The paper undertakes a comprehensive review of all existing micro-level data sets in the United Nations High Commissioner for Refugees Microdata Library and the World Bank Microdata Library. It first identifies a corpus of micro-level data sets that are designed to have a representative sample of refugees and / or internally displaced persons and assesses gaps in geographical and thematic coverage. The paper then evaluates whether the data sets contain a core set of questions that are essential for the proper identification of refugees and internally displaced persons. Usage context: supporting mention, primary mention, background mention.

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Input: They exclude other categories of displaced people who were not forced to move because of conflict or violence, such as economic migrants and victims of natural or environmental disasters. 4 Of course, many people cannot be simply categorized in these groups and this makes statistics on FDPs gross estimates, but the growth and relevance of these numbers are undisputed. The growth in the number of FDPs poses a challenge to the measurement of global and national poverty. Those who are forcibly displaced and in need of international protection tend to be persons who have lost their assets, financial resources, and social networks. They are typically very poor with no obvious path out of poverty. For refugees, their number vanishes from poverty statistics of their own country because they are no longer counted in the place of origin. Both IDPs and refugees are also not properly accounted for in the country in which they reside. Their numbers – even though high in absolute terms – are often low relative to the non-displaced population (with some exceptions like Lebanon and South Sudan). Hence, they do not explicitly show up in official statistics. Even if – as in some but not all countries – their locations are appropriately included in the sampling frame, they are unlikely to be sampled due to their small proportion relative to the population and high clustering in specific locations. 3 https: / / www. unhcr. org / refugee-statistics / 4 Note that the IASC definition of IDPs explicitly includes those fleeing from disasters. Usage context: supporting mention, primary mention, background mention.

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Input: assignment process was conducted to assign the trainees to the first or second round of training. 9 Of those entered into the random selection, 1273 young women were assigned to the first round of training, with the remaining 808 to serve as a control group (the control group would participate in the second round of training starting in July 2011). Of the 1273 assigned to treatment, 118 women were not found or chose not to participate after they were selected. 10 In order to fill at least some of these slots, 39 young women from the control group were randomly issued as replacements, resulting in a modified control group of 769 individuals. In the end, 1191 young women entered the first round of training. 11 The assignment process and all post-randomization modifications are summarized in Figure 2. Table 1 reports the baseline and midline survey response rates leading to the sample used for the analysis in this paper. The target sample for both the baseline and midline survey consisted of the original 2106 EPAG recruits, of which 1989 were successfully interviewed during the baseline survey. 12 At midline, 1736 were interviewed, including 56 who were not interviewed at baseline. For our analysis, we drop individuals who were excluded from the randomization or who were manually re-assigned from control to treatment as replacements after the randomization.

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Input: milk and milk products, oils and fats, sugar/honey, and others. Food consumption status is determined based on food consumption score. a. Dietary diversity score (out of 12 groups) b. Food consumption status Refugees’ Aspirations 49 Moreover, insecurity and displacement-related shocks are common for Eritrean refugees, with 14 percent having experienced a recent displacement event. This result is driven by refugees in the Alemwach refugee hosting site, all of whom moved to the refugee site within a few months before the survey as a result in the conflict in Tigray, and would have reported a recent displacement event. Both refugees and host communities use “consumption-smoothing” to cope with the various shocks they face. Households utilize a mix of coping strategies to mitigate harm to their welfare that shocks cause. “Consumption smoothing”, among the major risk coping strategies, mainly involves relying less on preferred food and more on less expensive food (diet changes) and reducing the number of meals eaten daily (negative food intake). Borrowing food or cash from friends and relatives and purchasing food on credit second represent the second and third most common coping strategies. Refugees in camps and in Addis Ababa are more likely to rely on these coping

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Input: These people are then expected to return to their place of origin once the conflict is over and governments are typically over optimistic about the duration of civil conflicts and about return of IDPs. In some cases, governments also have an interest in denying the very existence of IDPs for political purposes. Therefore, little time is spent in surveying IDPs or trying to find durable solutions in the place where they migrated. Moreover, national censuses are usually conducted every ten years and statistical agencies have little incentives to revise censuses, master samples and sample survey structure for situations that are perceived as short ‐ term. In most cases, new surveys are suspended or carried out under the pre ‐ crisis frameworks and, in either case, information on IDPs is not collected or poorly collected. This leaves specialized government agencies or international organizations in charge of IDP statistics (and care). However, unlike refugees, the IDPs do not benefit from a specialized international agency such as the UNHCR. IDP assistance is currently provided by a multitude of organizations including ministries of interior, specialized government agencies, the UNHCR, the International Organization for Migration (IOM), the UN Office for Humanitarian Affairs (UN ‐ OCHA), specialized NGOs and others. Some of these organizations collect information on IDPs and make this information public while others collect information that is not published and others do not collect information and focus on providing assistance. Most data collected are for the simple purpose of counting IDPs and do not include individual or Usage context: background mention, supporting mention, primary mention.

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Input: ESS translated the survey instrument into different main languages and undertook an in- depth training of supervisors and enumerators for enumerators to understand better the concepts of the questions related to the refugee context. Moreover, a close follow-up and coordination in the field helped to get better quality data and provided timely responses to challenges faced during data collection. During the survey implementation period, the main challenge was tracking sampled refugee households in all refugee domains. One of the Eritrean camps, Alemwach Camp, was newly established at time of data collection. Tracing the originally sampled and backup households initially took a lot of work. The issue of missing households in Asayita camp was severe during the second data collection phase. Moreover, some camps were very large; for example, there were more than 100,000 refugees in one camp, creating challenges for field workers in tracing the sampled households. Refugees in Addis Ababa live in rented houses; the team faced challenges in tracing some refugees due to changes in their residential locations. Challenges related to identifying the eligible sample households were also observed due to outdated names of the household heads in UNHCR lists, and UNHCR’s registration of names which is not

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

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Input: The SEIS was fielded over a 14-week period by a nationally certified survey firm using CAPI on Android tablets. Interviewers received five days of training covering the survey instrument, tablet operation, and protocols for interviewing households with protection concerns. The SEIS questionnaire was translated into four languages in addition to the national language to accommodate the linguistic diversity of the target population. Response rates exceeded 94 percent in all settlement types, and back-checks were completed for 12 percent of interviews, revealing no systematic interviewer effects.

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Input: 4 The only publicly available sources of data to document patterns of enrollment and available educational options for Pakistani families are household-based surveys. These are the official 1998 Census of Population (Government of Pakistan) 3, the 1991, 1998, and 2001 rounds of the Pakistan Integrated Household Survey4, and a 2003 census of schooling choice conducted by our research team. The fact that three sources use different definitions of madrassa enrollment, and were collected at different times by individuals with very different institutional affiliations provides independent verification of enrollment estimates and allows us to determine the sensitivity of our results. The household data tell us whether a child is enrolled full-time in a madrassa, but not whether a child goes for an hour on any given day to study the Quran. Therefore this data does not confound full-time with part-time attendees — a child who attends a public school during the day and a madrassa in the evening is recorded as enrolled in a public school. This is an important distinction since parents might use a modicum of madrassa or mosque based education to teach their children about religion. Consequently, if we contrast these household-based numbers with numbers from establishment-based reports, discrepancies can arise. From virtually any policy perspective, including evening quran classes in enrollment figures seems misguided. Usage context: primary mention, background mention, supporting mention.

1998 Census of Population
Pakistan Integrated Household Survey

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Input:
come ratios relative to extractives,
2008-13|
|---|---|
||Kayes
Sikasso
Other
regions
Total
Agriculture
6%
37%
60%
40%
**Extractives**
**100%**
**100%**
**100%**
**100%**
Industry
111%
50%
110%
85%
Construction
14%
75%
413%
214%
Services (tradable)
129%
68%
107%
84%
Services (non tradable)
76%
73%
183%
126%|
|_Source:_ CPS/SME (Mining and Energy Sector Planning and
Statistics Unit), 2013.|_Source:_ EPAM (Permanent Household Survey), 2010.|

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

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

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

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

Development Indicators (WDI).

#### **3.3 Sample Construction**

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

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

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

Global Positioning System (GPS) tracking records

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

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Input: a relatively higher percentage of married individuals. In Addis Ababa, 60 percent of refugees are unmarried. 16.2 15.7 14.9 8.8 14.1 Eritrean Somali South Sudanese Addis refugees All 0 20 40 Percent 60 80 100 Eritrean Somali South Sudanese Addis refugees Conflict and violence Natural/man-made disaster Personal threat and political persecution Social and economic reasons Hope to go to a Western country Other reasons Figure 2.3: Refugees arrival in Ethiopia (15 years and above) Source: World Bank Staff based on SESRE 2023. a. Years since arrival b. Reasons for leaving the country of birth 13 For details on OCP refugees, please see Box 2.2. Sociodemographic Profile 11 Refugees have larger households, younger heads, and a higher proportion of female heads than hosts. Household size is higher among in-camp refugees compared to hosts. Across in-camp refugees, South Sudanese refugees have the highest number of household members, averaging roughly seven members per 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.

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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: Kreibaum (2016) corroborate the ﬁnding that host communities near refugee settlements in Uganda have relatively higher consumption levels using data on three south-western districts, though the eﬀect is small in magnitude. d ’ Errico et al. (2021) ﬁnd that the presence of refugees has only modest eﬀects on local households ’ consumption levels. The authors attribute this ﬁnding not to an increase in demand for local produce, but to greater participation by host households in paid employment in aid agencies, and to the resulting increase in wage incomes. However, the eﬀects they observe are small, and concentrated in areas very near refugee settlements. 11 Most relevant to our study, Kreibaum (2016) reports that access to private primary schools (but not public schools or health services) has increased at a greater rate as a function of refugee presence. They measure refugee presence at the district level (refugee share of the district popu- lation) and focus on the south-western districts between 2002 and 2010. Thus, by including all of Uganda at the parish-year level as well as the post-2014 inﬂux, we extend their analysis. In sum, our study is the ﬁrst to measure the eﬀects of refugee presence on service delivery outcomes in Ugandan host communities. 10See Gianvenuti, Jalal and Kirule (2020) for more details. 11Note that both Zhu et al. (2016) and d ’ Errico et al. (2021) use original cross-sectional surveys. Without pre-treatment data, it is harder for them to make causal claims. 12 Usage context: supporting mention, background mention, primary mention.

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

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Input: Although 86 % of the refugee sample was surveyed at least once, there was some differential attrition between the treatment and control refugee sam- ples, and therefore we estimate bounded effects following Lee (2009) (and the text highlights the results for which both estimated bounds take the same sign unless otherwise noted). These data are analyzed largely following the econometric models and primary outcomes speciﬁed in an AEA pre-registration (AEARCT # 0006141) and associated pre-analysis plan, while making note of ad- ditional and exploratory results. Another core contribution of this study is to examine the host community reaction to refugee assistance, utilizing a detailed survey of the attitudes and experiences collected among a repre- sentative sample of the Jordanian neighbors (N = 2, 146) of both treatment and control households. To our knowledge, this is among the ﬁrst studies to experimentally examine how humanitarian assistance to refugees affects the views of the local communities who do not directly beneﬁt. Speciﬁcally, we examine whether refugee-targeted transfers — in this case via rental payments 1Statistic calculated directly from data on the universe of Syrian refugees in Jordan registered with UNHCR. 2 Usage context: supporting mention, primary mention, background mention.

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Input: 14 do selected volunteers increase their teamwork / leadership and their communication skills? Do they increase their self-esteem / self-satisfaction? iii) As a result of their assignment to NVSP volunteering experience, are selected youth more likely to find a job than non-selected ones? (a) IMPACTS ON SOCIAL COHESION VALUES The two main indicators that measure improvements in social cohesion values are tolerance and a sense of belonging to the Lebanese community. Measuring social cohesion values in large-scale surveys is challenging. We are unable to use extensive measures, but rely instead on brief measures adapted from Harb (2010). The tolerance measure relies on a series of 12 questions, each of which is ranked on a four-point scale, which makes the total possible score range between 12 and 48 points. The sense of belonging to the Lebanese community measure consists of 18 questions, each of which is ranked on a seven-point scale, which makes the total possible score range between 18 and 126. Thus, higher scale values indicate higher tolerance values and a stronger sense of belonging to the Lebanese community. Both values are internally standardized so that they have a mean of 0 and a standard deviation (S. D.) of 1 in the comparison group at baseline. Usage context: supporting mention, background mention, primary mention.

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Input: 14 Figure 3 Sample Distribution for Refugee Children Compared to Global Distribution (n = 92) Figure 4 Sample Distribution for Children Living in Rural Areas Compared to Global Distribution (n = 902) AIM-ECD direct assessment scores were created by calculating the percent correct out of the 77 direct assessment tasks and questions asked. There were four early literacy tasks (listening comprehension, letter identification, initial sound discrimination and name writing), six numeracy Usage context: primary mention, background mention, supporting mention.

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Input: Gender may inﬂuence how members of the host community experience and perceive their role as hosts. Since each of the samples are gender-balanced, Figure 6 re-reruns the logistic regres- sions above but after sub-setting the data by gender. Hosting IDPs is associated with improved perceptions of social cohesion among men for all sub dimensions other than access to basic needs in the general sample, but women ’ s perceptions of social cohesion are only positively associated with contact with other ethnic groups (OR: 1. 26, CI: 1. 01 – 1. 56) and access to services (OR: 1. 44, CI: 1. 15 – 1. 80). In cities, female respondents were more likely to report negative perceptions of in-group (OR: 0. 59, CI: 0. 41 – 0. 84) and out-group relationships (OR: 0. 63, CI: 0. 44 – 0. 90) when hosting IDPs. Women were less likely to participate with other ethnic groups (OR: 0. 57, CI: 0. 40 – 0. 82) if they had IDPs in their communities. But men had positive associations for IDPs with relationships and solidarity in cities.

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Input: The 2023 survey of transport infrastructure conditions found that 68 percent of rural access roads in the project's five target provinces were in poor or very poor condition, with pavement failure attributed primarily to inadequate drainage maintenance and axle-load violations by commercial freight vehicles. The 2023 survey was administered by provincial public works directorates and compiled by the national road authority using standardized pavement condition index scoring. Results were shared with the Ministry of Finance to support the project's economic justification.

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Input: The weight given to each province in constructing the synthetic control is based on pre-treatment outcomes. We use the pre-treatment average of the outcome dimension, Y, the unemployment rate, employment rate and the import and export per capita of the province to determine the degree of similarity between control group provinces and the treated provinces, which in turn determines the weight assigned to control provinces. The unemployment and employment rates are included to control for the general economic performance while trade values are added to control for the degree of ’ openness ’ of the province. 6 The treated unit i = 1 is constructed by taking the mean of the outcome variables in the provinces hosting refugees in 2012 or 2013. 5 Data We use several data sources for the analysis. The IV estimations use data from years 2011 and 2014 while the DD estimations use data from 2009 to 2014. The numbers of refugees up to 2012 are treated as 0. The refugee data for 2012 and 2013 are obtained from UNHCR ’ s oﬃcial weekly statements in December. Data on the number of refugees in 2014 is from Erdo ˘ gan (2014), who uses statements released by the Ministry of the Interior to compile his data. All refugee data we use in the analysis is provided at the level of 81 provinces. Usage context: primary mention, background mention, supporting mention.

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

population census
census of private schooling, 2000

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Input: stipend money, and they were formed into small groups or"EPAG teams", each with a coach or mentor, to foster support networks and boost attendance. 3. Methodology 3. 1. Research design The impact evaluation of the EPAG project uses a randomized controlled trial, in which eligible applicants to the program were randomly assigned to participate in one of two cohorts (or “ rounds ”) of training. The treatment group is defined as those who were offered a space in the first round of training and the control group comprises those assigned to the second round. Selection into the training rounds was performed on a computer (using Excel) and was stratified by the track choice of the applicant (job skills versus business development skills), community, and service provider. Data were collected using three quantitative household surveys (baseline, midline, and endline) and two sets of qualitative focus group discussions (one after each round of training). A timeline of the impact evaluation is depicted in Figure 1. During both the baseline and midline surveys, the head of the household in which the EPAG participant was residing was also interviewed, in order to examine potential spillover effects of the program on non-treated household members.

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Input: Research on long-term migration has established positive effects on host countries and shown that these effects are larger or faster if migrants are permitted to integrate eco- nomically (Abramitzky and Boustan 2022). The features of PEP facilitate causal identiﬁcation of its effects. First, the program was in- troduced unexpectedly, thereby isolating anticipatory decisions or ex-ante behavioral re- sponses. Unknown to both migrants and government ofﬁcials, ex-post eligibility for the program was based solely on prior registration in a nationwide census of irregular forced mi- grants, the Registro Administrativo de Migrantes Venezolanos (RAMV for its Spanish acronym), that was administered between April and June of 2018. According to the government of- ﬁcials who designed RAMV, the census was implemented to count the number of irregu- lar Venezuelan forced migrants in Colombia and was not intended to precede or lead to a regularization program. However, in August 2018, Colombia ’ s president unexpectedly 3 Usage context: supporting mention, primary mention, background mention.

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Input: . 12 10. 45 – # 20 December 2019 5752 4. 71 8. 14 – # 21 November 2020 2627 4. 19 5. 14 – # 22 February-March 2021 5847 6. 86 9. 30 – Overall July 2017-March 2021 49831 4. 64 8. 19 30. 58 Table 2: Details on Surveys and Displacement Trends Second, the paper conducts an individual-level analysis of two cross-sectional surveys of 1, 933 and 5, 951 individuals conducted in March-April 2018 and June- July 2018, respectively, to probe the relationship between hosting displacees and social cohesion in more detail. This survey wave 22

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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: The relation- ships between displacement dynamics and perceptions of each manifestation of social cohesion are analyzed separately by running 12 models for each independent variable (6 regressions for each sample). The regressions are correlations and should not be interpreted causally. Hosting status and displacement ﬂows are likely related to perceptions of social cohesion in indirect ways and the structure of the survey data limit the ability to specify the channels through which these relation- ships run. Each regression controls for characteristics that may inﬂuence respondents ’ perceptions of social cohesion outside of the presence of IDPs or refugees in the local community such as province, gender, age, marital status, level of education, employment, and exposure to violence. 11Poll numbers correspond to the number wave in our larger project, as described and shown in Table 2. 28 Usage context: background mention, primary mention, supporting mention.

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Input: 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. Due to the conflict in the Tigray region of Ethiopia between 2020 and 2022, Eritrean refugees living in camps in Tigray could not be included in this survey. To avoid exclusion of Eritrean refugees in Ethiopia, we included Eritrean refugees living in camps in the Afar region and the newly established refugee hosting zone Alemwach. Eritrean refugees who were in the Tigray region prior to the conflict are included in this survey in two ways: we sampled (i) refugees from Alemwach, where most of the refugees previously located in Tigray moved after conflict broke out and (ii) from Addis Ababa, namely those refugees who arrived in Addis Ababa after November 2020. Data collection took place between November 2022 and January 2023. Sample population The SESRE covers three types of groups, all of which require a distinct sampling procedure:55 (i) refugees in camps; (ii) refugees out-of-camps; and (iii) host communities. This

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Input:
Notes: (1) The table displays the estimation of the probability of being enrolled in college, employed, or employed in a formal firm given ENLACE grade 12
scores and a set of socioconomic variables. (2) Sample: ENILEMS-ENLACE panel. (3) All specifications include school fixed effects

45

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Table A.6: Probit         - ENLACE test scores and post-secondary school outcomes

Enlace Score 0.301*** -0.0474 -0.0474 0.114*** -0.0152 -0.0175 (0.0499) (0.0870) (0.0811) (0.0186) (0.0280) (0.0298) Upper secondary GPA 0.223*** 0.128* 0.0667 0.0846*** 0.0409* 0.0246 (0.0427) (0.0671) (0.0661) (0.0162) (0.0216) (0.0245) Girl -0.194** -0.661*** -0.0615 -0.0736** -0.212*** -0.0227 (0.0792) (0.132) (0.127) (0.0291) (0.0339) (0.0473) Private upper secondary 0.275*** -0.277 -0.271 0.104*** -0.0886 -0.100 (0.102) (0.186) (0.173) (0.0392) (0.0585) (0.0646) Urban resident 0.244*** -0.0709 0

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Input: Maps provided by the humanitarian coordination body delineated displacement hotspots, areas of refugee concentration, and border crossing points used in the preparation of the targeting methodology. These maps were produced using UNHCR's population of concern data combined with host government administrative records. The maps were last updated in October and reflect registration data through September 30. Any changes in population distribution identified through subsequent biannual registration updates will trigger a review of the targeting lists by the PIU and the relevant district authorities.

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Input: Thirty-eight percent of the sample was already engaged in at least one income-generating activity (IGA) at baseline. This is consistent with the national figures from the 2007 DHS survey, which found labor force participation rates of 34 % for women aged 15-19 and 49 % for women ages 20-24. It is also consistent with the Liberian 2010 Labor Force Survey, which found labor force participation rates of 25 % for women aged 15-19 and 47 % for women aged 20-24. For the purposes of this study, to be consistent with program objectives and the Liberian context, our definition of income-generating activity encompasses the full range of activities through which people earn money, including paid employment, either formal or informal, and self-employment in small business or through petty trade. The most common types of IGAs reported at baseline were petty trade, including 15 The balance tests are run on the same sample as will be used in the impact analysis in Section 4, that is, the subset of individuals for whom we have a panel. Balance tests run on the full sample of baseline survey respondents, regardless of whether they also participated in the midline survey, confirm the same findings. A report summarizing the balance tests on the full sample, including comparisons to nationally representative data, is available upon request from the authors. 9 Usage context: primary mention, background mention, supporting mention.

2007 DHS survey
Liberian 2010 Labor Force Survey

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Input: Geographic Information Systems (GIS) and geospatial analysis can be used to map, monitor and analyze data on forced displacement. Triangulation of this information with socio-economic and other indicators can provide a rich source of data and enable insights into underlying patterns and trends over time. (e) Use of big data (mobile phone data, news scraping, social media). IDMC is pursuing big data approaches to capturing displacement data in real time in order to report on displacement situations as they are happening and to provide updates on how they are evolving (IDMC 2015). These data are not necessarily representative but can be used in conjunction with other methods to triangulate trends. For example, the Swedish NGO, Flowminder, has pioneered the use of de-identified data from mobile operators to track population displacement caused by natural disasters such as earthquakes in Haiti in 2010 and Nepal in 2015, and these techniques may also have applications in conflict-induced displacement crises. 100 (f) High-resolution satellite imagery and unmanned drones. High resolutions satellite imagery can be used to map physical structures in refugee and IDP camps including changes to the number and type of these over time, support the remote detection of displaced populations in hard to reach or insecure settings; and conduct rapid assessments during or immediately after a mass displacement (Harvard Humanitarian Initiative 2014).

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Input:
daily changes in the amount of time spent at different places within a given geographic area. These data

capture daily percent changes from February 15 through July 15 relative to a baseline representing the

Figure 2 displays the Google Community Mobility data for both the entire country of Mali and

for Bamako specifically. Google aggregates locations into six types of places: Grocery and Pharmacy,

Finally, we use information from the COVID-19 phone panel survey, our third source of information used to investigate the intensity of pandemic-related disruptions within Mali.

as suggested by the Google Mobility Data, price effects could influence behavior on the intensive margin.

More research is needed to fully understand these dynamics.

Figure 4 shows self-reported estimates of the impact of the coronavirus pandemic on economic out

Google Community Mobility data
COVID-19 phone panel survey
Google Mobility Data

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Input: Estimation Results Using Proposition 3 (i), we start first with transforming some positive variables including household size and age in the HEIS and LFS to normality using the Box-Cox method, then standardizing the variables in the LFS according to the distributions of the corresponding variables in the HEIS respectively for 2008 and 2010. As a result, t-tests (not shown) indicate that the distributions of the standardized LFS variables are not statistically different from those in the HEIS, which satisfies Assumption 1. To ensure that Assumption 2 is satisfied, we use the closest version of Model 6 in all the following estimation, where the income variable is in a categorical format as earlier discussed. 26 We implement this test by pooling data from the two surveys, setting the data to incorporate the complex sampling design, and running a (complex survey adjusted) regression of the variable of interest on a dummy variable indicating the survey round. 31 Usage context: primary mention, background mention, supporting mention.

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

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Input: consultation with UNHCR and RRS. We used the ESS EA maps to assess the settlement of communities around camps, ensuring a precise fit to the definition of a “host community”. The assessment highlighted that using the list of EAs obtained from the new cartographic frame57 meets the definition of host community In the SESRE, host community members are defined as those who live adjacent to a refugee camp but within a radius of 5km. We use the updated Ethiopian Statistics Service 2018 cartographic database of enumeration areas (EAs) to define them. An EA is a defined area where 100-150 households live in rural areas, while in urban areas, it is an area where 150- 200 households live. The first stage of sampling for the host community involved using simple random sampling to select EAs—the primary sampling unit— from the list of EAs that are adjacent but within a radius of 5km. Following EA selection, a fresh list of households was prepared at the beginning of this survey, which was used as a frame to choose sampled households from each sample EA. In Addis Ababa, a separate host domain was developed as refugees spatially concentrate in a few sub-cities and Woredas.

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

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Input: Regrettably, until now almost all enrollment numbers cited have been based on establishment surveys which do just that. These data sources show that around 200, 000 children were enrolled full-time in madrassas before 2001. Since 2001, our school census suggests that these numbers may have increased somewhat, although the experience varies across districts. To put this number in context, total primary enrollment (grades 1-5) in public and private schools stood at 17. 4 million in 2003 (Government of Pakistan, Ministry of Finance, 2003). The choice of madrassa schooling viewed as either the percentage of eligible children or the percentage of enrolled children, is statistically insignificant for the average Pakistani household. Enrollment in madrassas accounts for approximately 0. 3 percent of all children between the ages of 5 and 19. Given that the overall enrollment rate for this age group is roughly 42 percent, this represents less than 0. 7 percent of all enrolled children, an order of magnitude less than the 33 percent cited by the International Crisis Group report (2002). 3 This is complemented with the census of private schools carried out by the Federal Bureau of Statistics in 2000 to provide statistics for private versus public enrollment. 4The PIHS is the equivalent of the widely used Living Standard Measurement Surveys (LSMS) implemented in various countries. See http: / / www. worldbank. org / lsms for extensive notes on the 1991 PIHS. See also www. statpak. gov. pk for information on the census and the Federal Bureau of Statistics data.

PIHS
Living Standard Measurement Surveys

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Input: 15 causes of death. The Danish Epidemiology Science Centre (1999) found severe malnutrition and high mortality in a survey of 422 refugee children in Guinea ‐ Bissau. They report higher malnutrition and higher mortality for children living in a non ‐ camp setting, compared to children living in a camp. The Goma epidemiology group (1995) found high prevalence of child mortality as well as acute malnutrition among children in refugee camps in Eastern Zaire, especially in female headed households. The magnitude of the difference between ‘ normal ’ mortality in the country under study, in the absence of conflict and the mortality in a refugee camp, depends on several parameters: the health infrastructure in the country as well as in the camp, the food available to camp and non ‐ camp residents, the frequency of visits by nurses or doctors, the intensity of the conflict (e. g. attacks on camps), and so on. Thus, the results are highly dependent on the context. For example, Singh et al (2005) do not find a difference in under 5 mortality among refugee versus non ‐ refugee households in western Uganda and South Sudan, whereas Verwimp and Van Bavel (2005) find higher child mortality and fertility among Rwanda refugees in Congo versus Rwandan women who did not became a refugee.

survey of 422 refugee children in Guinea ‐ Bissau

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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: The ZAR dataset includes all foreigners residing in Switzerland and contains similar information than AUPER. We are combining these two datasets with the yearly population census data that includes ZAR and AUPER starting from 2010. By combining these three datasets we can follow refugees and migrants over 1997-2018 and natives over 2010-2018. We define as refugees, all foreign-born individuals that went through an asylum process, and as migrants all other foreign-born individuals. Natives are defined as individuals born in Switzerland. In the final sample, we are drawing a random sample of 6 % of the native population. For the main outcome variables used in the descriptive analysis, we are first adding Swiss social security data provided by the Federal Compensation Office. This data collects information about every Swiss resident that contributed to old age provision (i. e., the old-age and survivor ’ s insurance OASI or AVS in French). We know the size and nature of the contribution made by individuals (from paid work, independent work, voluntary contribution or other kinds). This data is available from 1998-2018. Our main outcome variables measuring economic integration include employment, earnings and self- employment, and are constructed from the social security data. An individual is defined as employed if he or she contributed to old age provision from salaried or independent work. Earnings are defined as the sum of all positive contributions made from salaried and independent work in a year. Lastly, we 10 Usage context: background mention, supporting mention, primary mention.

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The severe escalation of the conflict has led to significant destruction of UNHCR property.
During the month of June, both UNHCR offices in Khartoum were destroyed, the UNHCR
warehouse in Al Obeid was looted, and other UNHCR warehouses remain inaccessible or
have recently been looted such as in South Darfur. In locations accessible to humanitarian
workers, UNHCR and partners continue to scale up humanitarian delivery despite capacity
limitations. UNHCR has established a small operational presence in Wadi Halfa while
scaling up its footprint in Wad Madani, Kosti, Gedaref, Kassala and Port Sudan. Further in
North Darfur, in collaboration with the sectors, UNHCR has been able to continue delivering
NFIs to IDP sites in El Fasher as well as conduct protection monitoring of new arrivals from
Kutum and Tawilla.

UNHCR 3

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

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Input:
- The XCO2 database (https://datacatalog.worldbank.org/search/dataset/0062760), an OCO2 panel database for a 25 km grid (G25), in Stata format, beginning in September 2014 and
updated regularly. The database includes G25 grid cell ID numbers, cell centroid coordinates,
monthly means of measured CO2 concentrations, and monthly means of Hakkarainen prefiltered CO2 concentration anomalies. The JPL/NASA database publishes OCO-2 data with
a lag of approximately two months.

  - For functional urban areas (FUAs) with sufficient data, annually-updated change parameter
estimates for models (6) and (7), with statistical significance categories [p>.05, ≤ .05, ≤ .01,
≤ .001].

Using a rich dataset consisting of geocoded household data combined with detailed information on gold mining activities, the authors conduct two types of difference-in-differences estimations that provide complementary evidence.

We use two complementary geocoded household data sets to analyze outcomes in Ghana: the Demographic and Health Survey (DHS) and the Ghana Living Standard Survey (GLSS), which provide information on a wide range of welfare outcomes.

XCO2 database
OCO-2
Demographic and Health Survey (DHS)
Ghana Living Standard Survey (GLSS)

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