Input: 20 capacity to offer these services. Many may be at risk of violence or trafficking. These are very important aspects from the perspective of welfare economists interested in measuring well ‐ being but these measurements are complex and not usually included in multidimensional indicators of deprivation or poverty. The dimensions of deprivations to consider are more numerous and more complex to measure. Again, there is very little research in welfare economics dedicated to the special needs of these populations. Risks and vulnerabilities. The analysis of risk and vulnerability is also much more complex in the context of the forcibly displaced. Welfare economics has only approached these topics recently, in the past decade or so. Essentially, the idea is to measure the risk of being poor or falling poor in the future using cross ‐ section or panel data studying spells of poverty over time. This is work that requires accurate and complex data sets that would be rarely available in a refugee or IDP context. More importantly, the nature of the problem changes. Refugees and IDPs are by definition more at risk and more vulnerable than regular populations and these vulnerabilities are not only linked to skills and efforts but to legal status, discrimination, limited mobility and other factors that are unique or much more acute with refugees and IDPs. Usage context: primary mention, supporting mention, background mention.

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Input:
Data on the structural and cyclical characteristics of national economies comes from the World Bank's World Development Indicator Database [9] and UNCTAD-STAT; [10] the figures on education are sourced from Barro & Lee (2013); [11] those on the real effective exchange rate (REER) are taken from Darvas (2012); [12] and metal- and oil-price figures are sourced from the IMF's Primary Commodity Prices database. [13] Referring to the original datasets will provide further details on the methodology and sources used.

We need first to describe inequality and poverty levels in the affected region. We define the poor as the individuals in the bottom quintile in terms of consumption or income. Therefore, the parameter �� is equal to 20%. To estimate �� and ��, we use the World Development Indicators database, which provides the income share of the bottom 20%. Figure 3 shows the result, highlighting the large variability - and lack of correlation - between inequality and national income level.

In this national-level analysis, and consistent with our focus on the socioeconomic drivers of resilience, we use a very simple methodology. We use the Global Building Inventory database from PAGER, by USGS, which provides a distribution of building types (buildings only, not contents) within countries across the world (USGS 2015). This typology has been developed to assess vulnerability to earthquakes but here we use it for all hazards.

UNCTAD-STAT
Primary Commodity Prices database
World Development Indicators database

Global Building Inventory database from PAGER

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Input: A number of different road indicators are available and we choose road line type to use in the analysis. Road type is defined by the following: The reference category (0) points out squares with dual lane / divided highways, other primary roads, or road connectors within urban areas (types 1 or 8 in the ESRI dataset). The second category include secondary roads (type 2), and the third combines squares with informal or tertiary roads (tracks, trails or footpaths) or no road registered at all (types 3 and 0, respectively, in the ESRI dataset). Figure 4 overlays the types of roads in the original dataset before our recategorization. The shaded area represents the portion of Africa for which we code

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Input: Page 19 of 51 Source: Own calculations based on Household surveys Finally, we analyze the trends in the task content performed by non-standard workers following the task methodology following the methodology proposed by Acemoglu and Autor (2011). Figure 13 presents the variation in the task content index by non-standard workers vis-a-vis standard workers. A first general view suggests that non-routine cognitive task content of jobs (both analytical and interpersonal) increased in both NSE and SE even though we have some exceptions. Indeed, the only countries where non-standard employment shows a less intense profile in non-routine cognitive analytical tasks are Peru and the Dominican Republic. Additionally, Chile and El Salvador show a virtually null change in the intensity of this kind of tasks. In the case of standard employment, the change in the profile towards non-routine cognitive analytical tasks is even more obvious (the Dominican Republic is the only exception). A similar scenario is recorded in the case of the intensity of non-routine cognitive interpersonal tasks, even though in this case the trend is more pronounced in both, standard and non-standard employment. Additionally, the trends in SE and NSE are more correlated for this type of tasks. The evolution of the intensity in the routine cognitive tasks in the last two decades in NSE presents a much more heterogeneous picture. Usage context: background mention, primary mention, supporting mention.

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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.

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Input:
**Annex 8: SIGAF Configuration and Reporting Requirements**

The SIGAF installation at the PIU uses Version 4.2 of the government's integrated financial management system. Key configuration parameters include: project budget structure mapped to the loan disbursement categories; reporting hierarchy linking district accounts to the central project account; and automated monthly statements that consolidate transactions across all spending units. SIGAF user accounts are managed by the Ministry of Finance's system administrator and must comply with the government's password security policy updated in 2022.

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Input: Notably, while we cannot rule out that time outside due to employment may play a role (e. g., fresh air may boost one ’ s mood), our time-use data indicates that the average refugee already spends at least three hours outside per day, with no measurable diﬀerence between employed and cash arms. As we are powered to detect changes of at least twenty minutes for each activity, our results suggest that large substitutions away from unsavory activities are unlikely to be driving the improvements in psychosocial well-being, insofar as the respondent recalls. 1718 We also investigate whether those who were more idle prior to being employed beneﬁt more from employment. We ﬁnd no impact along this margin, suggesting that the elimination of boredom per se is not the driving force behind the psychosocial value of employment (Appendix Table A10). 17Most respondents do not track their day by time, making collection of reliable time use data challenging (though recent literature documents the broader unreliability of such data). We piloted a variety of strategies, and settled on asking respondents how much time they spent on a set of activities in the previous day. Usage context: background mention, supporting mention, primary mention.

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Input:
7 Gibson and Kim (2012) use a HCES with direct measures of consumption from food stocks and find an error of up to 300 KCal per person per day from ignoring destocking of one major calorie-source (rice) that is subject to bulk buying and storage.

these reports when made by people who never transact in metric units. A typical HCES consumption

Once the food reported in an HCES is converted into calories, the household's calorie intake is compared

While the potential sources of mismeasurement in HCES are numerous, this study systematically

using a survey experiment conducted in Tanzania. There were a total of eight alternate designs, which

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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:  In Somalia, the Mogadishu Household Survey covered both residential areas and IDP camps, collecting data on expenditures, demographics and living conditions [survey completed; analysis forthcoming]. As part of the Somalia Knowledge for Operations and Political Economy (SKOPE) initiative, the Puntland Household Survey will also cover both residential and IDP populations [ongoing].  An IDP study in South Sudan [ongoing] aims to assess the economic needs of IDPs and host communities in urban areas, covering livelihoods, water and sanitation, infrastructure as well as intentions and conditions to return. Basic information about education, employment and general health variables will also be collected.  The Iraq Crisis Response Study [ongoing] will assess the impact of the Islamic State and oil price-related crises on IDPs and households left behind in IS controlled areas. Usage context: background mention, primary mention, supporting mention.

Iraq Crisis Response Study
Mogadishu Household Survey
Puntland Household Survey

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

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Input: tionnaire from Falk et al. (2022), along with a question on how much do the subjects in our sample trust the Colombian government. Additionally, we inquired about the ado- lescents ’ social networks by asking about their number of friends of each nationality and whether they have felt discriminated in school. While these outcomes were not the pri- mary focus of the VenReps Kids survey, they collectively provide a general assessment of social cohesion, a crucial aspect in understanding the overall well-being of children and adolescents. We measure the average differences in altruism between Venezuelan and Colombian ado- lescents following the estimation of equation 1. Table 8 presents the results for altruism, trust, discrimination and social ties in panels A, B and C respectively. As in the previous tables, the first column for each outcome reports the results of the estimates of equation 1 without controls, and the second and third columns report the results of the estimation with all controls and the propensity score matching respectively. As for altruism, we see that Venezuelan adolescents are on average willing to donate 17 % more of their imagi- nary money endowment to a good cause relative to Colombian adolescents. As for trust, the results are mixed when analyzing the trust items separately.

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Input: The LMP commits the project to applying the principle of equal pay for work of equal value and to prohibiting any deduction from wages without explicit written worker consent. Contractors are required to keep payroll records in a format compatible with SIGAF's payroll reporting template and to make these records available to the PIU's social development officer upon request. The PIU conducted unannounced payroll audits at three construction sites in the quarter and found that wage payment was consistent with LMP requirements at all three sites.

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Input: Excluding respondents who have relocated would omit those with the higher rates of income growth and poverty reduction. Table 5 reports confidence intervals for the incremental samples (which are not mutually exclusive); it gives a more detailed picture of how inference on consumption growth and poverty reduction would have changed if we had not tracked movers. It is apparent that inference from a ‘ simple ’ panel survey of respondents continuing to reside within the original communities would have produced underestimates of actual consumption growth and poverty reduction in this population. These conclusions are robust across the distribution of consumption, as well as at the mean and poverty line. Panel A in Figure 2 depicts the cumulative density function for consumption per capita for those people who remained living in the same community. Panels B, C and D make the same graph for respondents found residing in neighboring communities, elswehere in Kagera Region and outside Kagera Region. As respondents were located further from their location in 1991, so the difference between the 1991 and 2004 graphs becomes more pronounced. Note how, for people who remained in the baseline community, the 1991 and 2004 distributions lie close to each other under the poverty line and diverge above it, while for other mobility categories there is more divergence at the bottom of the graph. Usage context: primary mention, background mention, supporting mention.

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Input:
In the alternative specification, an additional step has been taken to assign calories to food items registered in the POF household expenditure questionnaire on frequent purchases (POF 3). The cost per calorie in this alternative scenario is minimally higher, leading to a food poverty line of R$259 in 2018 urban Southeast prices.

_Source:_ Own calculations using POF 2017/18.
_Note:_ Main specification estimates the cost per calorie based on assigning food items in POF to the TBCA and imputation for food
items at the 5-digit level (i.e., steps 1 and 2 described above). The alternative specification extends the imputation to larger food
groups based on categorization by IBGE (2020).

**Lower** **Upper**
**Total poverty line** R$455 R$1,061
𝒔 [𝑭𝑭] 0.235 0.243
_Source:_ Own calculations using POF 2017/18 data.
_Note:_ These total poverty lines are based on the food poverty line of R$258, coming from our main specification, which is based
on the minimum calorie requirement of 2,100 calories per person per day and average cost per calorie of the bottom 40 percent
of the welfare distribution, with calories having been assigned in a two-step procedure and deflated by household-specific foodprice Paasche indices, as described earlier in this section.

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Input:
This assessment is made possible through the use of state of the art transportation modeling techniques and by combining three data sets: 1) An innovative General Transit Feed Specification (GTFS) data set collected for the purpose of this analysis under normal (dry) and flooded (wet) conditions, 2) a travel survey data set with travelers' socioeconomic attributes and Origin-Destination (OD) information, as well as 3) a set of high-resolution global flood maps that capture both the extent and depth of pluvial and fluvial floods.

**3.2** **General Transit Feed Specification (GTFS) Public Transit Feed**

Wong, J. C. (2013). _Use of the general transit feed specification (GTFS) in transit performance measurement_ [Thesis,
Georgia Institute of Technology]. https://smartech.gatech.edu/handle/1853/50341

To understand the impact of flooding on public transit, we compared the GTFS transit feed mapped under dry and wet conditions and evaluated changes in headways, blockages of roads and rerouting, and travel speeds.

General Transit Feed Specification (GTFS)

General Transit Feed Specification (GTFS) Public Transit Feed

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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:
We complete this data with exact geographic location data from MineAtlas (2013), where satellite imagery shows the actual mine boundaries, which allows us to identify and update the center point of each mine.

1 In the 2010 Ghana population census average district size is 112,000

We combine the respondents from all four DHS standard surveys in Ghana for which there are geographic identifiers. The total data set includes 19,705 women (of which 12,392 live within 100 km of a mine) aged 15-49 from 137 districts. They were surveyed in 1993, 1998, 2003, and 2008,

We complement the analysis with household data from the GLSS collected in the years-1998-

99, 2004-05, and 2012-13. These data are a good complement to the DHS data, because they

MineAtlas (2013)
2010 Ghana population census
DHS standard surveys

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Input: For a detailed definition see section 4 Household size Number of people included in the case records of each PA in Individual ProGress dataset Wage Income 1 if the household receives income from employment and / or daily or irregular work Income from remittances 1 if the household receives income from remittances Income per capita Raw sum of household income from all sources; work, pension, assets in Syria transfers, donations, other organizations'humanitarian aid, and other divided by household size Male Adults Number of males above 18 (inclusive) in the household Marital Status Categorical variable. The classification includes married PAs with spouse in the household, married PAs without spouse in the household, widowed, single or engaged, and divorced or separated. Proportion of female Number of female divided by the household size Location Categorical variable for 11 Governorates / cities. Ajloun City, Aqaba, Balqa, Irbid Jerash, Karak, Maan, Madaba, Mafraq, Tafilah, Zarqa. In Camp 1 if the household is located in a refugee camp Poverty before UNHCR and WFP assistance 1 if household expenditure before UNHCR plus WFP assistance is below the poverty line (JD50) Poverty before UNHCR assistance 1 if household expenditure after WFP assistance but before UNHCR assistanc is below the poverty line (JD50) Source: Authors ’ elaboration.

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Input: 6 3 Methodology 3. 1 The A-F method and individual deprivations The Multidimensional Poverty Index (MPI) used in this paper was first presented, with a full methodological discussion, in Admasu et al. (2021). Here we present a general overview of the measure for the individual-level and intrahousehold analyses. The MPI is constructed based on the Alkire-Foster (AF) method of multidimensional poverty measurement (Alkire and Foster 2011). Three key statistics characterize any MPI: incidence or headcount ratio (H), which is the proportion of the population who are multidimensionally poor; intensity (A), which is the average share of weighted indicators in which multidimensionally poor people are deprived; and adjusted headcount ratio (M0 or MPI), which is the product of the incidence and intensity (MPI = H × A). The AF method uses a dual-cutoff counting approach to poverty measurement. Having fixed relative weights across indicators that sum to 100 %, it first identifies who is deprived in each indicator, then sums up the weighted deprivations each person experiences into a deprivation score. A person is identified as poor if their deprivation score meets or exceeds a cross-dimensional poverty cutoff that is greater than 0 and less than or equal to 100 %. It then aggregates this information to compute society-level MPI, incidence, and intensity.

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Input: Since the set of household members at baseline have subsequently moved, and usually not as a unit, the 2004 round results in more than 2, 700 household interviews (from the baseline sample of 912 households). Although the KHDS is a panel of respondents and the concept of a ‘ household ’ after 10-13 years is a vague notion, it is common in panel surveys to consider re-contact rates in terms of households. Excluding households in which all previous members are deceased (17 households with 27 people), the field team managed to re-contact 93 % of the baseline households. This is an excellent rate of recontact compared to panel surveys in low-income countries and high-income countries. The KHDS panel has an attrition rate that is much lower than that of other well-known panel survey summarized in Alderman et al. (2001) in which the rates ranged from 17. 5 % attrition per year to the lowest rate of 1. 5 % per year. Most of these surveys in Alderman et al. (2001) covered considerably shorter time periods (two to five years). Figure 1 charts the evolution of households from baseline to 2004. One-half of all households interviewed were tracking cases, meaning they did not reside in the baseline communities. Of those households tracked, only 38 % were located nearby the baseline community. Overall, 32 % of all households were not located in or relatively nearby the baseline communities. While tracking is costly, it is an important exercise because migration and dissolution of households are often hypothesized to be important Usage context: background mention, supporting mention, primary mention.

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Input: 21 Results suggest that 66 % of the returnees trust the Malian police and army most when it comes to providing security in the North. Almost half believe that the Malian army is brave and well trained. The vast majority of returnees believe that the government ’ s policies regarding reconciliation, security and social cohesion are good or very good. They also support the government ’ s approach towards decentralization and providing infrastructure such as access to potable water and electricity. As the next section will illustrate this differs strongly with the opinions of refugees. 6. Prospects for Peace IDPs, refugees and returnees have comparable opinions with regard to the requirements for peace: (i) addressing the ongoing crisis, (ii) improving security and (iii) reconciliation. Although there is agreement on what needs to be done, there is little consensus on what happened during the crisis, who the culprits are and who the main victims. Figure 15: What is the most important problem the Government needs to resolve today? (%) Source: Listening to Displaced People Survey, 2014. Usage context: supporting mention, background mention, primary mention.

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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: background mention, supporting mention, primary mention.

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Input:
From 23 to 25 May 2014, 137 interviews were conducted with the Shalozan Tangi displaced
population. The Return Intention Survey (RIS) was conducted using a specific tool/
questionnaire developed in 2013 for previous consultations and slightly adapted to the
current situation.

Furthermore, during an inter cluster mission from 26 to 28 May, protection cluster
representative conducted additional consultations with populations displaced from
Shalozan Tangi (12 male key informants) and in areas of return in Shalozan Tangi (two male
key informants from amongst the population already returned to the area of origin in 2012).

**III.** **Profile of respondents**

Out of the 137 respondents, one was women (a female headed household) and 126 men. 69
% of the respondents were heads of households (including one female respondent) and also
included three community leaders.

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Input: The notion that volunteering may affect positively youth ’ s sense of social cohesion has gained policy relevance since the publication of the World Development Report 2013: On Jobs, which stresses that in countries affected by conflict situations, creating the types of productive opportunities that strengthen social cohesion can help reduce the volatility of economic growth and achieve international development goals by defusing tensions and building trust among the different communities involved. This paper provides novel empirical evidence on the impact of volunteering on enhancing social cohesion values in Lebanon, a country with a fragile and highly complex political, religious and social landscape, as well as high degrees of social and economic exclusion among its young population. To our knowledge, this is the first impact evaluation that rigorously addresses this research question in Lebanon and in the Middle East and North Africa (MENA) region. The main results show that youth who were selected to participate in a volunteering program that consisted of 80 hours of inter-community volunteering activities and 20 hours of soft skills training were more likely to report higher and improved values of social cohesion in the short term. In specific, they were more likely to report higher tolerance values as well as a stronger sense of belonging to Usage context: primary mention, supporting mention, background mention.

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Input: 18 the local data on physical geography and population from the raster data. These data can then be imported into statistical programs for analysis. We aggregate all data up to a grid of 8. 6x8. 6km squares. Each grid square is assigned attributes of the country it is in along with information from data disaggregated to the level of the individual squares. Figure 3 illustrates this grid as a fictive country somewhat smaller than the average size in our dataset (50x50 squares, or 430x430 km) with a fairly representative but stylized population distribution. The country has three major cities, one of which is the capital, and two smaller ones. A rebel group has its headquarters at the Eastern border. The ACLED data for the Central African conflicts were aggregated up to the 8. 6x8. 6km squares and merged with information on other explanatory variables aggregated to the same level.

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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: I expect citizens who perceive tax collection to be the responsibility of non-state actors to be less likely to be willing to pay taxes to the state ’ s tax department than citizens who perceive tax collection to be the responsibility of the state. Perceptions of the eﬀectiveness of donor and non-state actor provision of services are assessed using the following items. Respondents were probed on how much they believe the following non-state actors and donors do to help their country: the United Nations; international donors and NGOs; international businesses and investors; China; and the United States. 9 I also include Freedom House ’ s political liberties and civil rights ratings for the 19 countries in the sample. These two variables should capture the relative equality of inﬂuence in making policy. They indicate whether citizens are able to express their voice without fear of repression and whether elections are free and fair. Neither of these variables are signiﬁcant at the p < 0. 05 level. 14

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Input:
**SOUTH SUDAN** | October 2023

#### **CONTEXT**

**YOUNG POPULATION AND PREVALENCE OF DISABILITIES**

South Sudan is a young nation with an average age of 18.8 years. In the absence of an updated census, it is estimated that 1.2
million people, or 16% of the population have disabilities. The most commonly identified disabilities include visual
impairments, hearing impairments, and physical disabilities. [iv] Additionally, the proportion of older people in South Sudan is on
the rise, accounting for 5.1% of the population in 2016, an increase from 3.9% in 2008, and an indication that the number is
growing each year. [v] Notably, most older people in South Sudan reside in impoverished rural areas, where they play a crucial
role as caregivers for children whose parents have often perished in the conflict.

The country has a troubled history marked by decades of armed conflict, leading to displacement, economic instability, and
increased climate hazards such as flooding and droughts. These factors have further weakened an already fragile state and
limited governance capacity, disproportionately impacting older individuals and those with disabilities.

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Input: Page 25 of 51 higher followed by the “ Professionals ” and “ Skilled agricultural, forestry and fishery workers ”. On the contrary, “ Managers ”, “ Technicians ”, “ Craft and related trades workers ” and “ Plant and machine operators and assemblers ” are the types of occupations with a lower incidence of NSE in the region. Figure 16: Prevalence of NSE among salaried employees. (Early 2000s / Mid-2010s) Source: Own calculations based on Household surveys Figure 17: Prevalence of NSE by categories of occupations ISCO. (Mid-2010s) Source: Own calculations based on Household surveys. As in the case of Latin American countries, the observed prevalence of NSE across types of occupations suggests a strong heterogeneity across non-standard employees. Actually, as we will analyze in detail in next sections, the productivity and task profile of workers in the categories of “ Professionals ” and “ Elementary workers ” is very different, even though both types of occupations are characterized by a higher prevalence of non-standard employment arrangements. 0 % 5 % 10 % 15 % 20 % 25 % 30 % Russia Georgia Kyrgyz Republic Turkey Armenia Albania Moldova starting point ending point 0 % 5 % 10 % 15 % 20 % 25 % 30 % 35 % 40 % 45 % 50 % Managers Professionals Technicians Clerical Support Workers Services and Sales Workers Skilled

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Input: 19 children and 61 % of caregivers prefer to remain in Italy. Adolescents between the ages of 15 and 19 express a greater desire to continue living in Italy compared to children aged between 9 and 14. Another survey conducted across Europe from June to December 2022 shows that only 8 % of Ukrainian refugees planned to settle outside Ukraine (Adema et al., 2024). Compared to other foreign children in Italy, the aspirations of Ukrainian refugees to return to Ukraine seems signiϐicantly higher: indeed, a recent study from ISTAT on children 11 to 19 years old shows that only 11 % of foreign children wish to return to their home country (ISTAT, 2024). The relatively strong desire to return to Ukraine can have negative effects in refugee parents'educational decisions, particularly in encouraging their children to learn the language of the host country and in enrolling in school (Dryden-Peterson et al., 2019; Zengin and Atas-Akdemir, 2020). Figure 6- Aspirations and identity of refugee caregivers and students (Source: World Bank Survey on Ukrainian refugees in Italy) Many students facing uncertain futures try to stay connected to both educational systems. Findings from the World Bank survey indicate that 25 % of children are engaging in online Ukrainian schooling while being enrolled and attending Italian schools.

World Bank Survey on Ukrainian refugees in Italy

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Input:
### 6.1 Grievance Redress Mechanism

The project-level GRM will receive and process complaints related to beneficiary selection, service delivery, labor conditions, environmental impacts, and GBV incidents. A dedicated toll-free hotline, an SMS channel, and physical suggestion boxes at community centers will serve as intake points. All complaints will be logged in the MIS within 24 hours of receipt and assigned to the responsible district coordinator for investigation. Complainants will receive a response within 15 working days, with more complex cases referred to the PIU's E&S specialist for resolution.

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Input: Considering that these statistical standards and recommendations were established in recent years, it may not be surprising that the overall level of compliance with EGRISS recommendations is still evolving. Figure 6: Prevalence of Identifying Questions in FDP Datasets A) Refugee identification questions B) IDP identification questions Notes: Panel A shows the percent of FDP datasets containing each of the core identification questions recommended by EGRISS for refugees (in all publicly available datasets designed to sample from refugees that are not project specific and collected after 2010) whereas Panel B shows IDP equivalent of that. For refugees, we do not make a distinction between the question on the country of citizenship and the acquisition of citizenship because many datasets we study often collapse these questions into one by simply asking respondents to indicate their nationality (or nationalities). 5. Conclusion With an ever-growing number of people forced to flee their homes due to conflict, violence, fear of persecution, and human rights violations, data on FDP has become ever more important. A solid evidence base is crucial to inform effective policy responses to address their challenges and to establish such a base, 35 More than 95 percent of the FDP datasets asked questions on either the country of birth or citizenship. 36 While the country of birth does not change, nationality or citizenship can. And it is the country of citizenship or acquisition of citizenship that determines whether refugees and refugee related persons should still be regarded as refugees by the national authorities even though their country of birth may be different from that of their citizenship or nationality and how citizenship interplays with refugee status varies by country (EGRISS 2019, p. 28). Usage context: background mention, supporting mention, primary mention.

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Input: natural log of a country ’ s population size and government consumption as a share of GDP; the latter is the most widespread measure of government size (Adsera and Boix, 2002; Alesina and Wacziarg, 1998; Rodrik, 1998). Tax compliance is also related to the government ’ s ability to eﬀectively detect and punish tax avoiders, tax evaders, and tax arrears. Although an imperfect measure of states ’ deterrent capacity, Afrobarometer includes two survey questions on perceptions of government enforcement and monitoring capacities. One question probes respondents on how often ordinary people who break the law go unpunished. The other probes respondents on how often oﬃcials who commit crimes go unpunished. This latter question is also a measure of perceived government fairness- the extent to which a government implements the law evenly across all social groups. 6. 2. 5 Procedural Justice I include two indicators of procedural justice. The ﬁrst probes respondents on how often people are treated unequally under the law. The next taps citizens ’ perceptions of the government ’ s treatment of their ethnic group. Speciﬁcally, respondents were asked how often their ethnic group is treated unfairly by their government. 9 6. 2. 6 Donor and Non-State Actor Provision of Services I include a measure of who citizens believe is responsible for collecting income taxes. Usage context: primary mention, background mention, supporting 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: of the groups and the distances between them. For instance, (Bazzi et al., 2019) shows that polariza- tion increases ethnic attachment. Others have highlighted the reduction in trust, either interpersonal trust or institutional trust Alesina and Ferrara (2002); Beugelsdijk and Klasing (2016). To assess the importance of alternative explanations, we first replicate our analysis using individual data on violence. In addition to participation in protests, we follow McGuirk and Burke (2020b) in using the Afrobarometer survey data on interpersonal crime and physical assault. We then assess the relationship between the revised refugee diversity indices and alternative individual outcomes such as ethnic vs. national identity, generalized trust, trust in neighbors, and institutional trust (trust in government). The questions from the Afrobarometer mentioned below are used as a proxy for these outcomes: 32 1 Attack: Over the past year, how often (if ever) have you or anyone in your family: Been physically attacked? 2 Crime: Over the past year, how often (if ever) have you or anyone in your family: Feared crime in your own home? 3 National identity: Let us suppose that you had to choose between being a [Ghanaian / Kenyan / etc.] and being a [respondent ’ s identity group]. Usage context: background mention, primary mention, supporting mention.

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Input:
The Normalized Deviation Vegetation Index (NDVI) is used to determine the exposure of households to
the drought. The NDVI is derived from satellite images measuring the health of vegetation.

In controlling for potential confounding factors, we rely on geo-coded conflict fatality data provided by the Armed Conflict Location Event Dataset (ACLED) and on data on the percentage of target beneficiaries reached with aid by pre-war region coming from the Food Security Cluster Somalia (Table A.1).

Armed Conflict Location Event Dataset (ACLED)

geo-coded conflict fatality data provided by the Armed Conflict Location Event Dataset

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Input: own/parents’ COB 0.05 (0.04) HH received humanitarian food aid in past 12 months -0.00 (0.04) Distance to woreda capital (log) -0.10*** (0.01) Distance to border (log) -0.03 (0.02) Medium market accessibility -0.02 (0.06) High market accessibility 0.29*** (0.05) Constant 11.10*** (0.34) Survey domain Yes Survey time Yes Observations 1,266 Source: World Bank Staff based on SESRE 2023. Note: Dependent variable is the log of total per capita consumption expenditure. All regressions include the controls in Table D.12. This table provides the results for the additional independent variables of interest. Standard errors in parentheses; * p < 0.10, ** p < 0.05, *** p < 0.01 Annexes 115 38% 60% 2% Drought prone, lowland, pastoralist Humid moisture reliable, lowland Moisture reliable, highland-Cereal Figure D.31: In-camp refugee locations by ecological Zone Source: World Bank Staff based on SESRE 2023 and Ethiopia Ecological Zone Classification from ESS. 0 10 20 30 40 50 60 70 80 90 100 Employment rate Unemployment rate LFP Share of individuals (%) 1-20km 20 -100km >100km 0 10 20 30 40 50 60 70 80 90 100 Share of individuals (%) 1-30km 30 -50km >50km Employment rate Unemployment rate LFP Figure D.32: Refugee’s labor market performance Source: World

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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 10044 Most refugee hosting communities are characterized by high levels of poverty with precarious livelihood conditions, low access to public services, and underdeveloped infrastructure. While the unexpected inflow of refugees might bring both constraints and opportunities for improving and maintaining local livelihoods in these communities, the understanding of these effects remains limited. Using a household level micro data set from a 2018 baseline survey of the Ethiopia Development Response to Displacement Impacts Project, this paper assesses the impact of refugee inflow on the livelihood strategies of host communities with respect to diversification and agricultural commercialization. Usage context: primary mention, supporting mention, background mention.

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Input: Page 7 of 51 In this sense, it is necessary to draw attention to the fact that the non-standard employment statistics presented below are not homogeneous among countries. In countries where both forms of non- standard employment were identified, we define non-standard employment as those occupations that satisfy at least one of the conditions, that is, either corresponds to a part-time occupation or a temporary job. In countries where temporary employment was not identified in the data, our non- standard employment category will coincide with part-time employment. Note that in either case, as other non-standard employment modalities are not identified, the indicators presented in this paper indicate a lower level with respect to the true dimension of the phenomenon. The only aspect addressed that required the use of additional information was the analysis linked to the profile of tasks that are developed in the framework of non-standard jobs. To carry out this analysis, the information available in the O * NET (Occupational Information Network) database was used in conjunction with the Household surveys. This database provides information referring to the content of tasks of the occupations. Usage context: primary mention, background mention, supporting mention.

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Input: NGOs. Initiatives such as JIPS, a collaborative project of UN and NGO actors, have also been established to support governments and operational organizations to design and implement data collection processes. There are a variety of data sources for generating statistics on forced displacement, each of which has strengths and weaknesses. Despite the significant challenges, large amounts of data are collected and disseminated every year. The main data sources and methods for the generation of statistics on forcibly displaced populations include: (a) registration of refugees and asylum-seekers; (b) registration of IDPs; (c) profiling of IDPs; (d) population movement tracking systems; (e) national population censuses; (f) sample surveys; (g) border crossings; (h) administrative records and registers; (i) general population registers; and (j) a variety of estimation methods for producing statistics when adequate and reliable data on individuals are unavailable (UNSD 2014). Several of these data sources might be used together to triangulate estimates of stocks and flows for a particular displacement situation. Usage context: primary mention, background mention, supporting mention.

sample surveys
general population registers

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Input:
Several of the refugees interviewed for this research indicated that no one wanted to give them
work because of their status as a refugee in Cameroon. When discussing the treatment they
received from the host population and the ability to find a job, all refugees interviewed explained
that it was difficult for them “because I am a stranger”, “from the outside” or because “I am
different”.

Although there are many similarities between the refugee population and the host community,
there is also a clear distinction that exists; all refugee interviewed indicated that they experienced
some sort of harassment and/or discrimination because they were refugees, and most connected
this directly to their ability to find wage-earning work in Yaoundé. However, several refugees
stated that the discrimination they face is not experienced with all Cameroonians, in some cases
they indicated that the locals supported them and treated them well; simply put by one refugee
from CAR, “some Cameroonians are nice, some are not.”

As discussed previously, identity documentation is a big problem for refugees living in
Cameroon, as many authorities and institutions do not recognise UNHCR identity cards and

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Input: This distinction is also applied to foreign students, with those entering the system after February 2022 referred to as “ Migrant post-Feb 2022 ” and others referred as “ Migrant pre-Feb 2022 ”. 7 Administrative data from MoE. The Ministry data includes information for all students who enrolled at any point during the academic year. 8 This information covers academic year, grade, gender, birth date, birthplace, citizenship. They also include school-speciϐic information such as the name and identifying code of the institution where the student is enrolled. Furthermore, the dataset includes a variety of school outcome variables, including grades in English, Italian, Mathematics, overall GPA calculated as the average across all subjects, behavior scores from grade 9 to grade 12, guidance council evaluations from lower secondary school, records of absences, late entries, and early exits. Given the timing of this study, data for academic year 2022-23 are the most complete. For academic year 2022-2023, school enrollment data at the provincial level was provided for 4, 269, 348 enrolled students across the 8 years of Italian lower and upper secondary school, encompassing both public and private institutions. The dataset includes nearly all students in the country irrespective of their citizenship. 9 Table 1 shows the distribution of the different groups of students by grade. In the 7 For ease of reference, we refer to non-Italian and non-Ukrainian students as migrants. However, we acknowledge that some of these students may be refugees or displaced students. 8 At the time of writing this paper, both MoE and INVALSI data were not fully available and, as such, only the information on enrollment was used for the academic year 2023-24. 9These numbers do not include students enrolled in Provincial centers for adult education (CPIA). See footnote 5. Usage context: background mention, supporting mention, primary mention.

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Input: When national or international actors provide assistance, there may be an incentive for people to register in camps even if they are staying elsewhere, or to register in multiple locations (Brookings 2011). 69 Furthermore, registration data provide only a snapshot of the stock of IDPs at a particular point in time and may be out of date if registers are not maintained regularly. Registration methodologies can vary across displacement situations. For example, families may be registered rather than individuals and the population estimated based on an assumption of average family size, which can differ among organizations (UNSD 2014). IDPs may be required to present documentation, meet specific criteria or re-register periodically to maintain their benefits, which affects aggregate numbers (IDMC 2015). For example, in Ukraine, pre-requisites for IDP registration (including valid documentation, arrival from a recognized conflict zone and permanent residence registration in recognized conflict zone) means that people displaced within a non-government controlled area, people displaced from a non- recognized conflict zone in a government controlled area, unaccompanied children or people without current / valid identification are not counted as IDPs (IDMC 2015). Usage context: primary mention, supporting mention, background mention.

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

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Input: Because the DHS cluster displacement algorithm can misassign households at cluster boundaries to the wrong treatment group, we conduct a robustness check in which we exclude all DHS clusters located within 10 km of the treatment threshold. This boundary exclusion sample represents 74 percent of the original sample. Point estimates in this restricted sample are almost identical to those in the full sample, and the exclusion of boundary clusters reduces rather than inflates the estimated treatment effect, allaying concerns about bias from spatial misassignment.

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Input: Compared to the baseline year of 2001, residents were more fearful of crime by 0. 17 sd. These fears are not necessarily unfounded, as we ﬁnd some weak evidence of changes in levels of violence in their parishes. Compared to 2001, a 1-SD increase in refugee presence in 2011 is associated with a 1. 26 percentage point increase in likelihood of a violent event, and in 2016, a 1. 11 percentage point increase. These ﬁndings are in line with our predictions for Uganda. As in Global North contexts, we recognize that out-group members can elicit fears and insecurity. It is unclear from the ACLED dataset, however, whether these violent events involve refugees. It is also possible that ACLED underreports violent incidences that are not reported by the media. Recent scholarship on the relationship between refugees and violent conﬂict ﬁnds that hosting generally has null eﬀects on conﬂict (Zhou and Shaver, 2021); when conﬂicts do occur, refugees tend to be the victims (Savun and Gineste, 2019). Nevertheless, by 2020, like with Afrobarometer respondents reporting feeling more safe, these fears of crime reverse with a negative eﬀect of- 0. 13 sd. Usage context: background mention, supporting mention, primary mention.

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Input: A growing number of low and middle-income countries have tried to improve the law enforcement response to gender-based violence by training professionals, reorganizing police and courts, and trying to provide a more comprehensive response to survivors. Evidence of effectiveness is relatively limited; most well-evaluated initiatives come from high-income countries, and the lessons learned may not be applicable to developing countries. Evaluations of law enforcement reforms in low and middle income countries have typically been limited to case study approaches drawing from police records (notorious for under-reporting), qualitative perspectives from key informant interviews, intermediate outcomes such as changes in attitudes and knowledge among police and judges, and interviews with small numbers of women who have sought legal redress. Population-based data collection, control groups, or follow-up among more than a handful of survivors are rare. Nonetheless, the following initiatives illustrate the types of efforts that have produced important lessons learned. Training personnel in the police and judiciary and other parts of the justice system Throughout the world, organizations have launched efforts to improve the knowledge, attitudes, and practices of justice sector personnel regarding gender-based violence. Some law enforcement institutions organize training internally, as did South Africa following passage of the 1998 Domestic Violence Act (Usdin et al., 2000).

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input:
Data for these measures of German influence are obtained from Eurostat, OECD and UNIDO. Finally, we use data on exports from COMTRADE to construct a measure of Germany's revealed comparative advantage (RCA) relative to Poland and to the world.

Results in this section draw on the Orbis data set, and for this reason refer only to
employment as the outcome variable. Unfortunately, the variable turnover presents
an excessive amount of missing values, which makes it unreliable.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: Afrobarometer finds that the vast majority of Malians want their country to remain a single and unified nation and that the attempt by armed groups to create a breakaway state in Mali ’ s northern territories is decisively rejected. See Afrobarometer Policy Paper 10 (Dec 2013). This difference with the Afrobarometer survey can be explained by the fact that the latter survey only focused on Malians inside the country and did not take the views of refugees into account. 5 93 2 6 86 75 20 2 3 94 Independence of the North Autonomy of the North Establish full government control over the North Figure 19: How do you envision the future of Mali? IDPs Refugees Niger Refguees Mauritania Returnees Usage context: supporting mention, background mention, primary mention.

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Input: integrate into the surrounding community and labor market. Among Eritreans in Afar and Amhara, the share working is 43 percent and 9 percent, respectively. Among workers, Eritreans in Amhara are three times as likely to work for NGOs or RRS, and very few work outside the camp. Box 3.1: Eritrean refugee sample in the SESRE Jobs and Livelihoods 27 Ethiopia relies on a camp-based model, with 88 percent of refugees hosted in camps. As outlined, in-camp refugees generally do not have work permits or business licenses and largely depend on work inside the camp or informal work outside the camp. On the other hand, the GoE introduced an out-of- camp policy (OCP)39 in 2010 that provides refugees the opportunities to live in Addis Ababa and different non-camp locations of their choice. Roughly 71,000 Eritreans were under the OCP regime as of 2022, with over 90 percent living in Addis Ababa. 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

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: 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.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: Figure 3. Wealth Index Distribution (a) Wealth Index- Total 0. 05. 1. 15. 2. 25 k-Density- 5 0 5 10 15 Wealth Index Colombian Venezuelan Venezuelan: Before migrating (b) Adequate Housing Materials (% of Total) 0 1 2 3 4 k-Density 0. 2. 4. 6. 8 1 Average- Dwelling Material Colombian Venezuelan Venezuelan: Before migrating (c) Asset Ownership (# Total) 0. 05. 1. 15 k-Density 0 10 20 30 40 Total Assets Colombian Venezuelan Venezuelan: Before migrating (d) Access to Services (% of Total) 0 1 2 3 k-Density 0. 2. 4. 6. 8 1 Average- Access to Services Colombian Venezuelan Venezuelan: Before migrating Notes: Panel (a) presents the distribution of the wealth index for Colombian and Venezuelan households in our sample in 2022 and pre-migration. Wealth Index is an index measure of the household ’ s cumula- tive living standard constructed following The Demographic and Health Surveys (DHS) methodology. Usage context: supporting mention, primary mention, background mention.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: Page 14 of 51 Source: Own calculations based on Household surveys From the education perspective, an improvement in the profile of workers employed as NSE can be observed in the countries analyzed, even though there are some exceptions. In fact, in most of the countries of our sample, the prevalence of workers with secondary and tertiary education increases in detriment of workers with a lower educational level. However, there are some differences by type of non-standard employment. In the case of part-time employment (Figure 10), several countries show an obvious rise in the prevalence of workers with secondary and tertiary education (Argentina, Brazil, Peru, and Mexico). There is a second group of countries that presents a decrease in the prevalence of workers at the secondary level, but, this decrease is more than compensated by the greater incidence of tertiary workers, so that, taken together, workers with secondary or higher education increased their share within part-time employees (Uruguay and Chile). Therefore, we can also conclude from this group that part-time employment presents a better educational profile today than two decades ago. In the Dominican Republic and El Salvador, we find a rise in the prevalence of workers with secondary education but a decrease in the share of workers at the tertiary level. Usage context: background mention, primary mention, supporting mention.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

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Input: of trade with government. Because the dataset used for this study is cross- sectional rather than longitudinal, I am unable to examine whether citizens adjust their beliefs and behavior to relative changes in service delivery. I was only able to test whether there are associations between the absolute service quality across neighborhoods, countries and ethnic groups and deference to the tax department, police and courts. Further, citizens may not be attributing goods and services to the gov- ernment. Rather, citizens may be attributing goods and services, such as roads, electricity grids, sewage systems, health care and education to vari- ous non-state actors including the following: the private sector; NGOs and community-based groups; churches, mosques and other religious institutions; traditional leaders; and, bilateral and multilateral donors. Survey questions on the Afrobarometer only indicate the presence or absence of services and infrastructure, and the quality of these services, but these questions do not probe respondents on who they believe are providing these services. Each of the indicators of perceptions of government performance is sig- niﬁcant at the p < 0. 05 level. Food security is positively associated with a willingness to defer to the tax department.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

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Input: These include topics like labor, finance (e. g., credit, debt, banking), agriculture / livestock / fishery, and education whereas FDP datasets are relatively rich in health, food insecurity, and water and sanitation in addition to coping strategies and protection. Furthermore, a large majority of questionnaires for these existing micro-level datasets do not include a core set of questions needed for proper identification of displacement status. This calls for further efforts 2 See https: / / www. unhcr. org / news / stories / unhcr-s-grandi-110-million-displaced-indictment-our-world. 3 The UNHCR MDL is available at https: / / microdata. unhcr. org / index. php / about. 4 The WB MDL is available at https: / / microdata. worldbank. org / index. php / about. 5 We focus on low-income and middle-income countries because they account for roughly 95 percent of FDP (refugees + IDPs) in the world based on data from UNHCR Refugee Finder and IDMC. 6 A representative sample means that when analyzed, the observed characteristics of the sample reflect the true characteristics in the target population that is being researched (Baal and Ronkainen, 2017). Usage context: primary mention, supporting mention, background mention.

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

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Input:
- Advocacy vis-à-vis allied, Government and AGEs with regards to the use of weaponry that may
leave ERW in heavily populated areas;

- Advocacy on the need to clear battle sites post kinetic engagement, especially in populated
areas;

- Strengthen resource mobilization efforts to ensure the sector can function at full capacity. The
total funding for mine action requested through the HRP is $3,080,676 (across MRE,
EOD/survey and coordination), of which 80% ($2,485,695) has been mobilised.

**Child protection**

During displacement and emergencies and conflict, violations of child rights occur in multiple forms.
The increased insecurity caused by violence and conflict has exacted an increasing toll on children in
terms of the number of civilian casualties along with serious child protection concerns.

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A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

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Input: occupation. Regression results (see Annex D, Table D.7) also confirm that, for hosts, older and more educated people are, in addition to having higher monthly earnings, more likely to work in a high-skill occupation (managerial or professional occupations). For refugees, older and more educated people are no more likely to work outside the camp. Yet, refugees with higher levels of education are more likely to be in a high-skill occupation when they are able to find work. 0 20 40 60 80 100 Camp Refugees Male Camp Refugees Female Inside the camp Outside the camp Percent Figure 3.9: Refugee work location Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 90 100 Camp Hosts Female Camp Refugees Female Self-employed Employee Public NGO/RRS Private household Unpaid Percent Figure 3.7: Female work type Source: World Bank Staff based on SESRE 2023. 0 20 40 60 80 100 Camp Hosts Female Camp Refugees Female Elementary occupations Machine operators/assemblers Craf/related trade workers Skilled agricultural workers Service/sales workers Clerical support workers Tech/associate professionals Managers/professionals Percent Figure 3.8: Female occupations Source: World Bank Staff based on SESRE 2023. Jobs and Livelihoods 31 0 10 20 30 40 50

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

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Input:
For rainfall data, I use a historical daily grid of rainfall, which is interpolated based on readings

that suddenly drop to zero purchasers is suspicious, especially since the BASIX data does not contain

error I run simulations where I assume that the BASIX data has been matched completely correctly,

I start by examining whether there is actual autocorrelation in the rainfall data. To test for

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source


Input: 11 Figure 3: Location of refugee camps in Ethiopia and the Ethiopia Development Response to Displacement Impacts Project (DRDIP) sample households Source: Authors ’ compilation using the database of the Global Administrative Areas (GADM) (https: / / gadm. org / data. html, accessed November 20, 2020) and the Humanitarian Data Exchange (HDX) database for the refugee location (https: / / data. humdata. org / dataset / ethiopia- refugee-camp-locations, accessed November 20, 2020). From the Ethiopia DRDIP data set, we derive two measures of livelihood diversification and two measures of agricultural commercialization (all at household level). The measures of diversification include: (i) the degree of labor diversification in different productive livelihood activities (e. g., farming, wage employment) as a primary activity (occupation), and (ii) the degree of labor diversification in different livelihood activities as a secondary activity (occupation). 13 These two outcomes were constructed using the inverse Simpson diversity index as 1 ∑ 𝑛𝑛 𝑖𝑖 𝑆𝑆𝑖𝑖 2, where 𝑆𝑆𝑖𝑖 is the share of the number of adult labor engages in 𝑖𝑖𝑡𝑡ℎ livelihood activity to total active adult household labor and 𝑖𝑖 ranges from 1 to the number of livelihood activities that a household engages in (Valdivia et al. 1996).

database of the Global Administrative Areas

A dataset, survey, database, index, census, registry, or information system with a specific proper name that can be cited, queried, or downloaded as a data source

A data source described by its characteristics or producer rather than a proper name, containing a data noun and at least one identifying descriptor

A general reference to data, information, or statistics that contains a data noun but lacks enough specificity to identify the exact source