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

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Input: (a) High frequency sample surveys using smartphone and cellular technologies. For example, a high-frequency survey initiative in Somalia employs a dynamic questionnaire loaded onto smartphones, which enables data to be collected from household interviews in 60 minutes. This approach was developed to overcome the challenges of insecurity, limited data gathering capacity and budgetary constraints. (b) The use of mobile phones to conduct surveys or follow up interviews following face-to-face household surveys. For example, a Bank paper on the impact of the 2012 crisis in Mali on IDPs, refugees and returnees used information from a face-to-face household survey as well as follow-up interviews with its respondents via mobile phones. This combination provided a mechanism to monitor the impact of conflict on hard-to-reach populations who at times live in areas inaccessible to enumerators. And in Sierra Leone and Liberia, the Bank supported the use of mobile phones to collect key socio-economic data on the effects of the Ebola virus. (c) Crowdsourcing data on displacement. Platforms such as the Kenyan Ushahidi has crowd- sourced data on displacement in Kenya and eastern DRC by encouraging IDPs and host communities to report incidents using their mobile phones or the internet, including information about living conditions. The platform references these reports geo-spatially. (d) Geo-mapping of data on displaced populations and affected host communities.

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Input: Bank and Israel and occupied territories strongly suggest that commuters would be differently affected during the pandemic when border closures were enacted. Another unique feature is the presence of a large refugee population in the West Bank and Gaza. However, it is important to note that refugees in this context are de- fined quite differently from other contexts. Here, not only the individuals immediately displaced are considered refugees, but also their patrilineal descendants, even if born many decades later. In particular, the LFS dataset follows the United Nations Relief and Works Agency (UNRWA) definition of refugees, which is “ persons whose normal place of residence was Palestine during the period 1 June 1946 to 15 May 1948, and who lost both home and means of livelihood as a result of the 1948 conflict, ” as well as “ the descendants of Palestine refugee males, including adopted children ” (UNRWA, 2023). Consequently, most refugees are indistinguishable in socio-economic outcomes and labor market behavior from non-refugees. However, residence in refugee camps does make a significant difference. As of 2019Q4, 5 % of the West Bank ’ s residents live in refugee camps, as do 14 % in Gaza.

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Input: Percentage of women who reported sexual violence by an intimate partner (ever), physical violence by an intimate partner (ever), and physical violence by an intimate partner in the past 12 months. 50 % 59 % 30 % 27 % 34 % 13 % 31 % 50 % 62 % 34 % 33 % 47 % 23 % 41 % 37 % 20 % 10 % 14 % 6 % 17 % 23 % 47 % 23 % 29 % 31 % 6 % 23 % 40 % 42 % 49 % 3 % 18 % 19 % 16 % 8 % 19 % 16 % 8 % 13 % 29 % 3 % 17 % 25 % 13 % 15 % Bangladesh (Urban) Bangladesh (Province) Brazil (Urban) Brazil (Province) Ethiopia (Province) Japan (Urban) Namibia (Urban) Peru (Urban) Peru (Province) Thailand (Urban) Thailand (Province) Tanzania (Urban) Tanzania (Province) Serbia Samoa sexual violence ever physical violence ever physical violence past 12 months Source: Unpublished data from the WHO Multi-Country Study on Women ’ s Health and Domestic Violence Against Women. The final published comparative report is forthcoming. Cited with permission. Prevalence data on sexual violence is even more limited than physical violence. However, evidence suggests that a substantial proportion of girls and women have experienced child sexual abuse, forced sex and other forms of sexual coercion in virtually every setting of the world. For example, population-based studies have asked about “ forced ” sexual debut among sexually experienced young people and found rates from 7 % (New Zealand), to 46 % (in the Caribbean) (Heise and Garcia Moreno, 2002). Usage context: primary mention, supporting mention, background mention.

WHO Multi-Country Study on Women ’ s Health and Domestic Violence Against Women

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Input: Formula (5) can be decomposed into two parts: eδs, which measures the average income level in district s, and eηszh ≡ eβs (Eh s − Es) + eχs (Hh s − Hs) which captures individual-speciﬁc variation in income. Migration models predict that, other things being equal, the choice of migration destination should depend on g E [yhs | zh]. This means that if we regress the choice of destination separately on eδs and eηszh, they should have the same coeﬃcient. The same methodology is used to construct other variables that may aﬀect the choice of 9The literature has often emphasized that migrations often serve an important role in household formation. For migrants, the prospect of forming a large, successful household is likely to be one of the purposes of migration. 10The 1995 / 96 NLSS survey adopted the following sampling strategy. Within each district a small number of wards were selected at random. Within each ward, 12 randomly selected households were interviewed. Because the wards diﬀer widely in terms of population, applying sampling weights is essential in order to obtain consistent estimates of δs. 16 Usage context: supporting mention, background mention, primary mention.

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Input: The MHPSS program evaluation conducted at 18 months assessed changes in functional impairment, social participation, and perceived support among beneficiaries who received structured psychosocial support compared with a waitlist control group. Facilitators documented session attendance and content coverage using a standardized session log. The evaluation found meaningful reductions in psychological distress scores among participants, though the absence of clinical diagnostic instruments limited the ability to measure changes in diagnosable mental health conditions.

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

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Input:
**Total Population**

**11,735 Individuals**

**(6,548 Cases)**

**Vulnerabilities***

Unaccompanied or

separated child

Woman at risk

Single parent

Child at Risk

Disability

Chronic Illness

**136**

_*One individual may have multiple specific needs_

**2,288**

2020 2021 2022 2023 2024

_*Pre-registration data refers to a headcount upon arrival or at disembarkation sites. Some individuals departed prior to registration with UNHCR._

UNHCR / 1 November 2024 3

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Input: The SEIS was designed as a nationally representative survey of households with at least one member holding refugee or asylum-seeker status, and the sampling frame was constructed from UNHCR's biometric registration database. SEIS enumeration areas were selected with probability proportional to size, stratified by settlement type (camp, urban, rural dispersed). Questionnaire modules cover household composition, labor market participation, housing conditions, access to education and health services, and subjective well-being. The SEIS sampling methodology ensures that estimates are representative at the national level and by settlement type.

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Input: 22 Source: Authors ’ calculations based on data from the High Frequency Surveys of Ethiopia (2017), Nigeria (2018), Somalia (2017), South Sudan (2017) and Sudan (2017). To uncover the main drivers of the observed gender based differences in multidimensional poverty at country level, we study the absolute contribution of the gender difference in each indicator to the overall household gender gap (see Figure 6), calculated as the difference between the censored headcount ratio for males versus females. We find that in Ethiopia, the gender gap that disadvantages female-headed households is mostly driven by the difference in financial insecurity measures (lack of legal ID and bank account) and health measures (early marriage, physical safety, and food insecurity), which is further reinforced by the differences in the living standard and education measures. Female-headed refugee households are more food insecure, live in unimproved housing, have lower access to electricity, are more likely to be married at an early age, and have lower access to legal identification and a bank account. In South Sudan, gender gap that disadvantages female-headed households is mainly explained by the differential in the financial insecurity and health measures, but cumulative gaps in the living standard and education indicators also contribute to the overall gap at the household level. Usage context: supporting mention, background mention, primary mention.

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

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Input: Evidence for Sub-Saharan Africa shows that female-headed households that have previously been highly dependent on male income – notably widow-headed households – are particularly prone to poverty, although other types of female-headed households may not be more likely to be poor than male-headed households (Brown & Van der Walle, 2020). For this reason, while it is important to analyze differences in poverty risk between households with female and male heads, it is also important to understand how different routes to female headship, and the changes in the household composition more broadly, impact poverty risks and expenditure levels. This paper explores level and distributional changes in expenditure among Syrian refugee households in Jordan between 2013 and 2018 using a gender lens. By the end of 2018, UNHCR had registered more than 671, 000 Syrians1 who had fled their homes and settled in Jordan. At the end of the time period covered by this research, UNHCR ’ s 2019 Vulnerability Assessment Framework (VAF) 1 UNHCR ’ s data portal records 671, 551 registered Syrian refugees residing in Jordan on January 13, 2019. See UNHCR (2022b) available at https: / / data. unhcr. org / en / situations / syria / location / 36. Usage context: background mention, supporting mention, primary mention.

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Input: Another ex- planation of these results could be the vulnerability of the Colombian population who in many cases has also a long history of internal forced displacement and violence. V. D Social Cohesion We also delve into the differences in secondary outcomes among Colombian and Venezue- lan adolescents concerning social cohesion. We focus on assessing altruism, trust, iden- tity towards specific domains, networks, and experiences of discrimination. To measure altruism and trust, we employ the questions from the Global Preference Survey, a tool developed by Falk et al. (2022) to elicit risk, time, and social preferences. Specifically, to measure altruism we ask the adolescents how much of a fictional endowment would they be willing to donate to a good cause. To measure trust, we include the 7-itme ques- 38

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Input: Due to the variations in weight and height ratios among children and adolescents according to gender and age, the benchmarks for determining nutritional status are specifically tailored to these factors. We adhere to WHO guidelines to calculate the standardized BMI values for minors. A BMI exceeding one standard deviation (SD) from the mean suggests overweight, while a BMI less than minus one SD indicates underweight. 16 Health status is assessed through a binary variable, assigned a value of one if the caregiver has reported any health issues such as disease or chronic pain, accidents, dental pain, surgical interventions, or preg- 14For the Colombian households the wealth index is measured with contemporaneous data. 15This procedure restricts the sample to the common support of the propensity score for being a forced migrant and weights observations for Colombian kids by a non-parametric function of the propensity score. This procedure has been shown to increase the estimate ’ s efficiency. 16Furthermore, a BMI greater than 2SD is indicative of obesity risk, and less than- 2SD signals a risk of severe thinness. 33 Usage context: background mention, primary mention, supporting mention.

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Input: Page 13 of 51 Figure 8: Temporary employment by gender. (Mid-1990s / Mid-2010s) Source: Own calculations based on Household surveys 4. 1. 2 Profile of Non-Standard Employment The next objective of this work is to investigate possible changes in the profile of non-standard employment, usually associated with lower productivity and greater vulnerability. The analysis of the employment profile was made based on access to social security benefits, education level, labor income and the task content performed by the workers. From the point of view of social security, we find that NSE shows a higher prevalence of informality compared with SE. For instance, the average prevalence of informality for our set of countries among NSE in the ending point of the study is 40 % while the prevalence among SE is 20 %. In this sense, a rise in the prevalence of NSE could be associated to a big set of workers without access to social security benefits. From a dynamic perspective, there is no a common trend across countries regarding the prevalence of informality among NSE workers (Figure 9). Indeed, several countries (Uruguay, Brazil, Chile, and Peru) registered a small decrease in the prevalence of informality among NSE but there is another set of countries for which the opposite is observed (Mexico, El Salvador, Bolivia and Argentina).

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Input: Without army protection most parts of the North, especially Kidal remain inaccessible to those working for the central and local government. 3 Armed bandits are active and IED explosions as well as violent attacks on the MINUSMA peacekeeping forces are regular occurrences. Under these circumstances, data collection is very difficult. INSTAT, the National Bureau of Statistics, has not been in a position to collect information from northern Mali since the beginning of the crisis. To our knowledge, our surveys implemented by a private survey entity, GISSE, are the only systematic and representative effort to collect data in north Mali since the crisis. They offer a unique database providing a crucial perspective that would otherwise not be reflected in academic analyses and policy level decision-making, and a perspective that is indispensable in any attempt at understanding the situation in Northern Mali. 4 Preceding the Accord on Peace and Reconciliation in Mali (Accord pour la paix et la réconciliation au Mali) (hereafter, the Peace Accord) of May and June 2015, four peace accords had been signed between the government and Toureg and Arab armed groups in 1 Kel Tamasheq (those who speak Tamasheq) is synonymous for Tuareq. 2 Francis David (2013): The regional impact of the armed conflict and French intervention in Mali. NOREF, Norwegian Peacebuilding Resource Centre. 3 Assessing Recovery and Development Priorities in Mali ’ s Conflict-Affected Regions. Draft Report of the Joint Assessment Mission for Northern Mali (January 2016), p. 15-16. 4 All data can be downloaded from www. gisse. org. Usage context: primary mention, supporting mention, background mention.

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Input: high informality. Some of these studies also ﬁnd that women and young workers were disproportionately aﬀected. More recently, researchers have shifted the focus to other dimensions of the eﬀects of Syrian refugee inﬂows into Turkey. Altindag et al. (2020) argue that refugee inﬂows had a positive impact on ﬁrm production, both in terms of the volume of production and the introduction of new product varieties. Akgunduz and Torun (2020) examine other channels by which Turkish workers and ﬁrms accommodated the inﬂows of Syrian refugees. The authors ﬁnd that skilled native workers increased their specialization in complex tasks, moving away from manual tasks, and domestic companies took advantage of the increased abundance of labor by reducing capital intensity. As shown in earlier studies, both mechanisms contribute to mitigate the eﬀects of immigration on the wages of the receiving country (Lewis (2005), Peri and Sparber (2009), Gonzalez and Ortega (2011) and Dustmann and Glitz (2015)). In the last few years, some researchers have begun to analyze the economic eﬀects of the exodus of Venezuelans on the surrounding countries but progress has been slow due to the diﬃculty of analyzing Venezuelan migrants equipped solely with government- provided data or the standard labor force surveys. Usage context: primary mention, supporting mention, background mention.

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Input: Figure A. 2: Injective relations We also isolate many-to-one (bijective) relations. In this case, we have to aggregate the Afro- barometer ethnicities with their unique and more aggregated correspondence in the UNHCR refugee camps data (See Figure A. 3). Figure A. 3: Bijective relations The remaining correspondences are either (i) one-to-many (bijective) but opposite to Figure A. 3 (i. e., many ethnicities from the UNHCR refugee camps data correspond to one ethnicity from the Afrobarometer) or (ii) many-to-many relations. For both cases, we apply a more pragmatic approach: a. In both cases, we disregard ethnicities that do not appear either in the Afrobarometer or in the UNHCR refugee camps data. This means that for the remaining ethnicity that has no counterpart in either the Afrobarometer or the UNHCR refugee camps data, we simply keep the name of the ethnicity as such, i. e., this information is not dropped. b. Then, after ignoring ethnicities that have no occurrence in our datasets, we check whether the one-to-many or the many-to-many relation has not boiled down to a one-to-one resp. many-to- one relation again. If so, we can treat them as above. c.

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Input:
The FAO estimates of the hunger rate combine aggregate food balance sheets for every country with

representative household consumption expenditure surveys (HCES) available for 129 developing

countries. [1] These HCES are already being used to monitor global poverty trends (Chen and Ravallion

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Input:
for the exam in 2007, we were able to identify 71 percent three years later in ENLACE

we use administrative data from the annual school census ( _Formato_ _911_ ) to estimate the

ENLACE panel has a survival rate that is 6 and 7 percentage points lower vis-a-vis the

<!-- PAGE 11 -->
matching. Take-up rate in the ENLACE test is high, 87.3 percent of the population

secondary in 2013. The difference in graduation or survival rates between the ENLACE

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Input:
To further control for geological and agro-ecological characteristics at the community level, elevation figures were included, taken from the GLOBE 1 kilometer elevation database (GLOBE Task Team et al. 1999). Elevation differences were also incorporated as a measure of terrain roughness. These were computed using the SRTM3 data (Jarvis et al. 2006) by subtracting the minimum elevation in a 1 kilometer grid from the maximum elevation in the 1 kilometer grid. Finally, urban/rural and regional indicator variables help capture unobserved (time invariant) location specific characteristics related to the urban and rural livelihood systems as well as those related to regional variation in the agro-ecological, economic and political environment. Year dummies were included to control for the survey year.

Given the focus here on riverine and coastal floods and to better pinpoint the locations that actually experienced riverine or coastal floods, the DFO flood maps were overlaid with the location of the rivers taken from the Hydroshed project (Lehner et al., 2008). Only the major rivers were mapped as these will have sufficiently large catchment areas exposing the downstream areas they traverse to (non-localized) flooding. Riverine and coastal flood bands were then derived by considering DFO flooded areas within 2, 5 and 8 meters elevation difference from the closest point on the major river or the coast using a Digital Elevation Model from GLOBE (GloBe Task team, 1999).

To reflect access to public services, indicator variables are included that take the value of one if clean water [32], sanitary latrines, [33] or electricity are present in the community, and zero otherwise. To proxy a household's integration in the overall economy, the community data were further augmented with the distance of the centroid of the community (in meters) to the nearest part of the nearest primary or secondary road, as designated in the VMAP0 dataset (NIMA 1997). These measures were computed that using Arc View 3.2. In addition, the estimated travel time to the nearest town or city of at least 25,000 people, the nearest city of at least 100,000 people, and the nearest city of at least 500,000 people were included. The travel times were computed in Arc View from a friction grid that assigned differing travel times to various classes of roads, urban areas, water bodies, off-road, and crossing international boundaries. [34]

The expenditure data are expressed in January 2002 prices using the CPI provided by the Government Statistical Office. They are also corrected each year for regional and rural/urban differences across the 8 regions.

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Input: Second, there are cases where the current study reports data by nationality, but the corresponding figure in the Trends in International Migrant Stock refers to the foreign born. This situation generally arises when a census does not report the number of foreign-born migrants on a bilateral basis. Examples include Austria and Côte d ‘ Ivoire. Third, differences in the years to which the data refer can generate large disparities. For example, this study uses the 1966 data for Australia, whereas Trends in International Migrant Stock reports data for 1970. Overall, however, the fact that the totals are remarkably close in every decade adds credence to the estimates here. IV. THE EVOLUTION OF GLOBAL BILATERAL MIGRATION The greatest strengths of the global migration matrices are their bilateral coverage, the number of decades covered, and the disaggregation by gender. These data are too rich for a full analysis of all movements between all pairs of countries. Instead, this section summarizes the major trends in the evolution of bilateral migrant stocks, based primarily on World Bank regions. 25 Global Trends The migration matrix for the 1960 census round reflects a realigning world in the postcolonial era. Over the 1960-2000 period, the composition of world migration 25 Appendix 1 details the World Bank regions: South Asia, East Asia and Pacific, Sub-Saharan Africa, Latin America and the Caribbean, Europe and Central Asia, and Middle East and North Africa. High-income Middle East and North Africa refers to the predominantly oil producing countries in the Persian Gulf (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia, and the United Arab Emirates) and to Israel. Usage context: supporting mention, background mention, primary mention.

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Input: there are approximately 30 refugee camps in Ethiopia, this report refers to the 24 camps included in SESRE. vii Hosts tend to support refugees’ right to work and move to locations with better economic opportunities. Hosts support increasing refugees’ economic opportunities in Ethiopia, but some perceive that refugees increase insecurity and are taking their land. Hosts’ perceptions of adverse effects from refugees are low, but they indicate the impact on economic competition, price increases, deforestation, and security issues. Trust between refugees and hosts is similar, with refugees being more trusting. Refugees are more likely to trust a host if they are culturally similar. Cultural proximity and positive perceptions of economic benefits improve the co-existence of refugees and hosts. Still, additional effort is required to improve the social integration of refugees for enhanced economic integration. Policy Recommendations Addressing challenges refugees face in Ethiopia requires a concerted effort to promote their self- reliance, economic integration, and access to education and health. By leveraging data from initiatives like SESRE and adopting a comprehensive approach that considers the needs of both refugees and host communities, Ethiopia can maximize the benefits from hosting refugees while minimizing associated costs. The Government of Ethiopia has committed to

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Input: not work and must rely solely on aid or assistance, the annual cost of basic needs per refugee is approximately US$378. Under the “current” scenario—where refugees can find opportunities to earn money or work—the amount of assistance needed to cover basic needs reduces annual costs by 44 percent to US$210 per capita. The saving can be viewed as an economic-inclusion dividend made possible by Ethiopia’s prevailing refugee policies. Under a hypothetical “full inclusion” scenario— where in-camp refugees have equal opportunities as hosts—the cost of basic needs decreases further to only US$78 per refugee, per year. 0 10 20 30 40 50 60 70 80 Poorest 2 3 4 Richest Percent Figure 5.20: Share of consumption provided in-kind or for free by consumption per capita quintiles among in-camp refugees Source: World Bank Staff based on SESRE 2023. Note: Quintiles are constructed for in-camp refugees only. 0 10 20 30 40 50 60 70 80 90 100 Hosts Refugees Hosts Refugees Hosts Refugees Addis Ababa All camp Total Total consumption Pre-assistance income Percent Figure 5.21: Poverty incidence at consumption and pre-assistance consumption levels Source: World Bank Staff based on SESRE 2023. Note: Poverty rates are calculated based on $2.15 in the 2017

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Input:
### INTRODUCTION

Within UNHCR public health covers various areas including primary health
care, nutrition and food security, reproductive health and HIV, mental
health and integrated refugee Health Information Systems (iRHIS). Sectoral
programming in a comprehensive response context means applying a wholeof-government (i.e. relevant national and local authorities for health and
nutrition response) multi-stakeholder approach and planning with relevant
partners. The overall responsibility of coordinating the health sector
response in refugee-only situations will be with the Ministry of Health, with
support of UNHCR and relevant partners. A wide range of partners play
a role in planning and delivering public health interventions in different
areas and at different stages of the refugee response. For an effective and
comprehensive response it is therefore essential to know how and when to
engage these various partners. Though the establishment of refugee-specific
services may be needed in the early phases of a refugee situation, longer
term solutions are required to ensure that refugees have access to services
through the national health system. Host countries may require assistance
from other partners, including international organizations but also local
partners, to make the necessary adjustments to comprehensively include
refugee health needs into national development and local health plans,
to strengthen/reinforce national and local resilience of national and local
health systems to meet the health needs of refugees and host communities.

integrated refugee Health Information Systems

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

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Input: the standard ethnic diversity indices to include the annual variation in refugee ethnicities. 8 We then construct a measure of proximity between the clusters in the host country and refugees in surrounding camps by defining an 80-km buffer around each cluster. 9 To control for unobserved heterogeneity and changes within a given cluster, we introduce cluster and year fixed effects, αj and δt. To minimize the risk of confounding the refugee-induced changes in diversity with the annual changes in refugee numbers, we also control for the presence of refugees based on the same buffer as the one used to construct the refugee-induced change in diversity. More specifically, the variable Refugeesjt − 1 counts the number of refugees present in cluster j at year t − 1 within the predefined buffer. The variable is also transformed into an inverse hyperbolic sine to ease interpretation. Finally, Qjt controls for yearly shocks at the cluster level, such as weather shocks. In particular, we control for rain and temperature anomalies. Standard errors are clustered at the Afrobarometer cluster level. 4. 2 Data and descriptive statistics Our analysis combines various sources of data: Afrobarometer, UNHCR refugee camp data, Armed Conflict Location and Event Data (ACLED), Uppsala Conflict Data (UCDP), and the Ethnic Power Relations- Ethnicity of Refugees (EPR-ER) 2019 dataset. Usage context: background mention, supporting mention, primary mention.

Ethnic Power Relations- Ethnicity of Refugees (EPR-ER) 2019 dataset

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Input: 18 Figure 11: Timing of Return (%) Source: Listening to Displaced People Survey, 2014. 94 % of the returnees were displaced inside Mali and 6 % outside the country. 67 % went to Bamako, 11 % in Koulikoro, 9 % to Ségou, 5 % to Mopti and 3 % went elsewhere (Kidal, Gao and Sikasso). The majority returned between June and October 2013 a period that followed the signing of a peace deal between the interim government and rebel factions to allow presidential elections to be held in July (first round) and August (second round) 2013. In October security in the North worsened again and ever since the number of people returning has been very limited. The main challenges reported by returnees in June 2014 were (i) poverty and food insecurity; (ii) lack of infrastructure (including lack of safe drinking water) and (iii) unemployment. 11 % of the returnees stated not to be facing any challenges (Figure 12). Usage context: primary mention, supporting mention, background mention.

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


Input: throughout the day prior to the survey day. We develop our own questions around self- worth rather than employing the more standard Rosenberg Self-Esteem Scale, which we found inappropriate given the Rohingya ’ s recent experiences. Speciﬁcally, we construct an index of self-worth from two questions designed to elicit respondents ’ beliefs about how they contribute to their family and community. Finally, we adapt the Cantril Self-Anchoring Striving Scale (Cantril, 1965) to measure how stable respondents feel in their present lives and in the future. We additionally examine the impacts of each treatment on physical health, cognitive function, economic decision making, time-use, and consumption. We capture respondents ’ sense of physical health by asking how many days they have fallen sick in the past thirty days and cognitive function by employing a digit-span memory test and a series of basic arithmetic problems. We explore economic decision making along two dimensions: incentivized time preferences (Andreoni and Sprenger, 2012; Gin ´ e et al., 2018) and incentivized risk preferences (Holt and Laury, 2002).

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Input:
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tracks ownership of state business entities with at least 10 percent stake in over 90 countries, including
Romania. The first part of the paper examines whether the degree of ownership and control levels of SOEs
matter for differences in performances-in terms of employment, average wages, assets per worker,
investment, and (labor) productivity-between SOEs and POEs over the 2011-2019 period.

**that justifies an SOE presence** . The taxonomy was developed by Dall'Olio et al. (2022b) in conjunction
with the BOS database. It classifies 4-digit NACE industries into three broad sectors (competitive, partially
contestable, and natural monopoly) based on the economic rationale-the intrinsic features and associated
market failures-that justifies SOE presence in an industry (see Table 2). Other NACE codes are excluded
from the sector classification of SOEs because firms in those industries provide public goods (e.g., public
administration and defense and activities of extraterritorial organizations). In contrast, others are
characterized by externalities (e.g., education and human health activities).

3.2 World Bank Global BOS Database
**The World Bank BOS database maps the footprint of the state within the corporate sector and across**
**economic activities based on a uniform definition** . The BOS dataset tracks all corporations where
national or subnational governments have an ownership stake of at least 10%, either directly or indirectly
(Dall'Olio et al. (2022a)). In this dataset, corporations are business entities that are (a) capable of generating
a profit or other financial gain for their owners, (b) recognized by law as legal entities separate from their
owners and with limited liability, and (c) set up for purposes of engaging in market production.

BOS database
World Bank BOS database
BOS dataset

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: 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.

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: The wealth index used in this analysis is computed from GLSS household asset data following the principal component analysis method developed by Filmer and Pritchett (2001). The GLSS wealth index is based on ownership of durable assets (television, refrigerator, mobile phone, bicycle, motor vehicle), housing characteristics (wall and roof materials, number of rooms per capita), and access to utilities (electricity, type of toilet, drinking water source). This index has been validated against consumption-based welfare measures in prior applications of GLSS data to poverty analysis.

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


Input: 26 value of consumption flow of durable goods. 22 While monetary poverty can measure temporal resource holdings, multidimensional poverty, as a more comprehensive measure, includes chronic and exacerbating sources of poverty. This difference explains the existence of mismatches between individuals identified as monetary versus MPI poor, which are often more prominent in poorer countries (Evans et al 2020). This section examines these differences in the contexts of displacement. Table 9. Percentage of the sample in each poverty category: Rows sum to 100 % Non-poor by both measures Only Monetary Poor Only Multidimensional Poor Monetary and multidimensional poor Ethiopia 38 % 23 % 12 % 27 % N. E Nigeria 13 % 69 % 4 % 15 % Somalia 20 % 32 % 14 % 34 % Sudan 33 % 47 % 4 % 17 % Source: Authors ’ calculations based on data from the High Frequency Surveys of Ethiopia (2017), Nigeria (2018), Somalia (2017), South Sudan (2017) and Sudan (2017). This table presents the distribution of households in each of the categories in the columns. Thus, each row adds up to 100 %. South Sudan is excluded from this analysis as monetary data is not available for the country.

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

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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). 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:
**Component 2 Update: Infrastructure Works**

Civil works under 12 of the 14 contracted sites are progressing on schedule. ESMF compliance audits conducted in March found that all sites met the LMP requirements for worker accommodation and wage payment, but two sites required corrective action on dust and noise management during construction. GIS-based photographic tracking of construction progress — using geotagged photos uploaded by site engineers — has been added to the activity monitoring dashboard, providing real-time visual verification of works completion to supplement the progress certificates issued by the supervising engineer.

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:
The only question included in the WVS related to attitudes towards immigrants - and available   for a sufficient number of survey years - is: _On this list are various groups of people.

Using household surveys for 24 countries between 2002 and 2012, we find that in most

<!-- PAGE 24 -->
Deaton, Angus. The analysis of household surveys: a microeconometric approach to

Source: Attitudes toward migrants were estimated from ESS (see data section for more details). The gap reflect the difference between the positive attitudes of

group as the majority (ESS). _Proimmigdiff_ is the average pop. share (%) who would like many or some immigrants of a _different_

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: representative sample of undocumented migrants in Colombia ’ s major cities as of 2020. 10 This survey encompasses information on the socioeconomic status, health, well-being, access to services, and labor market outcomes of adult undocumented migrants. Second, we compare our sample with the Administrative Venezuelan Migrant Registry (RAMV), a nationwide census of undocumented Venezuelan migrants conducted by the Colom- bian government in 2018. 11 This census surveyed Venezuelan households regarding their socioeconomic conditions and the labor market characteristics of the household head. We compare the household characteristics and the labor market outcomes of the house- hold heads in our sample with those in VenRePS and RAMV surveys in Table A. 3. 12 We observe that households in the VenRePS-Kids survey are smaller on average and have a greater number of children living in the household. The latter is anticipated since one of the eligibility criteria to participate in our survey is the presence of at least one child in the household. Furthermore, the household heads in our sample are disproportionately female and more likely to be married, aligning with the family structure targeted in our sampling frame. Regarding labor outcomes, household heads in our sample are more likely to be employed and engaged in the informal sector compared to those surveyed in VenRePS and the RAMV census. Usage context: supporting mention, background mention, primary mention.

Administrative Venezuelan Migrant Registry

Administrative Venezuelan Migrant Registry (RAMV)

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Input:
The monthly precipitation data comes from the Africa Rainfall and Temperature Evaluation System (ARTES) (World Bank 2003). This dataset, created by the National Oceanic and Atmospheric Association's Climate Prediction Center, is based on ground station measurements of precipitation over the period 1948-2001.

Soil data was obtained from FAO (2003). The FAO data provides information about the
major and minor soils in each location. Data concerning the hydrology was predicted from a
hydrological model for Africa (Strzepek & McCluskey 2006). The model calculated the
water flow through each district in the surveyed countries. Data on elevation at the centroid
of each district was obtained through GIS manipulation using data from the United States
Geological Survey (USGS, 2004). The USGS data are derived from a global digital elevation
model with a horizontal grid spacing of 30 arc seconds (approximately one kilometer).

Weng F & Grody N, 1998. Physical retrieval of land surface temperature using the Special Sensor Microwave Imager. _Journal of Geophysical Research_ 103: 8839-8848. World Bank, 2003. Africa rainfall and temperature evaluation system (ARTES). World Bank, Washington DC.

Africa Rainfall and Temperature Evaluation System (ARTES)

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Input: 12 though somewhat lower than that of the Turkish at 30- 50 percent. Child labor is also quite prevalent, though there have been extensive efforts made to ensure that refugee children attend school. 19 Publicly available information on refugees comes from an AFAD survey of 2, 700 households in June and July 2013. Figure 2, using data from AFAD (2013), provides an overview of the Syrian governorates from which the refugees to Turkey originated. The refugees primarily come from northwest Syria. The largest source regions are Aleppo (36 percent), Idleb (21 percent) al-Raqqah (11 percent), Lattakia (9 percent), and Hamah (8 percent). Consistent with travel distance being a good predictor of refugee flows to Turkey, 80 percent of respondents report that they chose to flee to Turkey, instead of another country, due to the ease of transportation. The refugees in Turkey, unlike the later 2015 refugee flows to Western Europe, are nearly 50 percent female. Slightly over 50 percent are minors (under the age of 18). These facts reflect that to large extent Syrian families fled to Turkey together. Usage context: primary mention, supporting mention, background mention.

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Input: 26 Buller et al. (2016) conducted a mixed methods study in Ecuador, combining secondary analysis from a field experiment on the impact of a transfer program on IPV with in-depth interviews and focus group discussions with male and female beneficiaries. The qualitative component aimed to better understand the mechanisms underlying the quantitative results, which showed substantial reductions in physical and sexual violence among beneficiaries of the cash and in-kind food transfer program. These qualitative interviews revealed a similar finding to Arugay et al. (forthcoming). Specifically, a core feature of women ’ s reported joint decision making was asking their spouse or partner for input into a decision, so that they would not be blamed if something went wrong. Similarly, an analysis of qualitative data from eight projects in Africa and Asia focused on understanding women ’ s empowerment finds that joint decision making can be empowering for women. In particular, in focus groups in Ghana, women stressed the importance of family harmony and in the individual interviews, “ women indicated that they want more input on decisions, but do not want full responsibility for decisions in case they go wrong (Meinzen-Dick et al, 2019, p. 20). The qualitative evidence provides one interpretation of our empirical results. Couples who agree that they jointly make decisions may also be sharing responsibility for these decisions. Usage context: primary mention, supporting mention, background mention.

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Input: However, another regressor indicates that security may still be pivotal: those who owned a weapon were up to 30 percentage points more likely to plan to go back. In addition to this, it is quite surprising that, if the respondent thought that the Northern Mali crisis was improving, he or she was less likely to plan a return to that area. From a technical point of view, we should point out that we have used an LPM even if the dependent variable was a binary outcome. This choice has been made since in this linear model it is straightforward to add fixed-effects. Furthermore, the coefficients can be interpreted as average partial effects. A simple logit or probit model would not have allowed the inclusion of individual fixed-effects because of the incidental parameter problem. An alternative approach would have been to estimate a conditional logit model. However, since the distribution of the fixed effects is unknown, it would not have been possible to estimate the average partial effects in this model, but only the effect of the regressors on the log-odds ratio. 13 We conclude by stressing that the monthly phone interviews were relatively short, so we did not have a rich panel data set. This may have led to omitted variable biases. Indeed, there may still be time varying factors which could have affected both the probability of being employed and the respondents ’ intentions to go back. Nevertheless, we believe that our model managed to control for 13 See (Wooldridge, 2010) page 639. Conclusions from the conditional logit model are qualitatively similar. Usage context: background mention, supporting mention, primary mention.

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Input: Our analysis exclusively uses data from the 1951-2015 UNHCR Population Statistics Reference database (extracted September 18 2015). Data were provided for 173 countries: 77 percent of these data were based on individual refugee registration, 13 percent on estimates, 5 percent on combined estimation and registration, and 5 percent on other sources. The data are structured as follows: for each situation, the database records annual numbers of persons of concern, which comprise “ Refugees (including refugee-like situations) ”, “ Asylum seekers ”, “ Internally Displaced Persons ”, “ Returnees ”, “ Stateless ” persons, and “ Others of concern ”. A situation is a pair country of origin / country of destination. For example, Somali refugees in Kenya account for one situation, Somali refugees in Ethiopia for another, and South Sudanese refugees in Kenya for yet another. Furthermore, a situation is considered major if it involves more than 25, 000 people. It is referred to as protracted if it is major for at least 5 continuous years. The database, and therefore our analysis, is limited to refugees under UNHCR protection. It does not include asylum seekers, i. e. individuals who have sought international protection under the 1951 Convention but whose claims for refugee status have not yet been determined, and persons in “ refugee-like situations ”, i. e. individuals outside their country or territory of origin who face protection risks similar to those of refugees, but for whom refugee status has, for practical or other reasons, not been ascertained (e. g., undocumented Rohingya originating from Myanmar 4 Usage context: supporting mention, background mention, primary mention.

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Input: 9 Bank Account No member has a bank or mobile money account. 1 / 12 Many of the indicators align with goals identified in the 2030 Agenda for Sustainable Development, such as no hunger, good health, access to quality education, clean water and sanitation, and decent work, as well as indicators that are especially relevant for displaced people, such as possession of legal identification, physical safety, and food security. The focus on gendered dynamics justifies health indicators related to pregnancy care, combining information on prenatal care, assisted delivery, and early marriage. A full discussion of the MPI ’ s indicator selection can be found in Admasu et al. (2021). We focus on six of these 15 indicators that use individual-level data – viz years of schooling, school attendance, pregnancy care, early marriage, legal identification, and unemployment. Our intrahousehold analysis drops the two health indicators due to data limitations; the question about age at marriage was only asked to the household head in Ethiopia, Nigeria, and South Sudan, whereas in Somalia and Sudan, it was applied to more members than the head.

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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 6832 This paper presents findings from the impact evaluation of the Economic Empowerment of Adolescent Girls and Young Women (EPAG) project in Liberia. The EPAG project was launched by the Liberian Ministry of Gender and Development in 2009 with the goal of increasing the employment and income of 2, 500 young Liberian women by providing livelihood and life skills training and facilitating their transition to productive work. The analysis in this paper is based on data collected during two rounds of quantitative surveys in 2010 and 2011, the second of which was conducted six months after the classroom-based phase of the training program ended. Usage context: supporting mention, primary mention, background mention.

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Input: two partial indices: the headcount ratio (H) and the intensity of poverty (A) i.e. (MPI = H*A). The headcount ratio is the share of poor people in the population, while the intensity shows how much deprivation poor people experience on average. A cut-off point of 0.33 is used for the multidimensional poverty headcount ratio; that is, a household is multidimensionally poor if the MPI is greater than 0.33. The population vulnerable to poverty is defined as those who experience 20-32.9 percent intensity of deprivation, and the population in severe poverty are those with an intensity of 50 percent or higher (that is, if the MPI is 0.50 or higher). Box 5.3: MPI methodology 0 10 20 30 40 50 60 70 80 90 100 Hosts Refugees Hosts Refugees Hosts Refugees In Camp Addis Ababa Total Worse Same Better Hosts Refugees Hosts Refugees Hosts Refugees In Camp Addis Ababa Total Percent 0 10 20 30 40 50 60 70 80 90 100 Percent Worse Same Better Figure 5.8: Perceived changes in household living standards Source: World Bank Staff based on SESRE 2023. Note: The survey asks how the household living standard has changed compared to last year and the last five

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Input:
set that satisfies this requirement is the World Value Survey (WVS) spanning the years from   1990 to 2011, that is, a period covering about 20 years.

in the WVS regarding immigrants are quite different from those of the ESS. Moreover, they are   not available for all years, so we end up with only two countries from the Europe area: Spain

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Input: Due to our research design and the complexity of introducing a third grouping who would play outgroup in the behavioral experiments regardless of partner identity, we exclude PRL from the main analyses presented here. 5 Data were also collected six months after the end of the training but this was heavily disrupted due to the outbreak of the COVID-19 pandemic. In Lebanon, this resulted in a change to the method of data collection (from in-person to telephone) and in Jordan, an end to data collection entirely. In Jordan, this had a more pronounced effect on the control group, due to the scheduling of data collection and implementation of restrictions in Jordan. Given these complexities, we do not present results from these analyses. 6 In addition, we attempted to collect information on the extent of social and economic interactions between hosts and refugees. At baseline, almost 95 % of respondents in both the treatment and control group reported such interactions. For this reason, we do not include this information in these analyses.

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: status Source: World Bank Staff based on SESRE 2023. Employed Unemployed, searching Unemployed, not searching Inactive not in school Inactive in school Percent 0 20 40 60 80 100 Camp Hosts Female Camp Refugees Female Addis Hosts Female Addis Refugees Female Figure 3.29: Female youth work status Source: World Bank Staff based on SESRE 2023. Jobs and Livelihoods 39 T his chapter looks at how low sociodemographic and labor market outcomes shape how refugees perceive their future prospects and aspirations. While “resettlement” to a high-income country is an attractive solution, the share of refugees resettled globally is marginal. Resettlement is considered one of the three “durable solutions” for refugee protection under the 1951 Refugee Convention, alongside naturalization and return. Yet, the share of refugees resettled globally—including private sponsorship and other complementary pathways of refugee admission to third countries outside of UNHCR processes—was below 2 percent over the past twenty years (World Bank, 2023). According to government statistics, there has also been a downward global trend in the number of resettlement opportunities, fluctuating from 99,000 in 2010 to just 34,000 in 2020, even as the number of forcibly displaced persons increases globally. In Ethiopia, resettlement numbers are similarly low; in 2022,

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: 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. Usage context: primary mention, background 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

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:
**Annex 12: CAT DDO Trigger Conditions and Drawdown Procedure**

The CAT DDO facility may be drawn down upon declaration of a state of natural disaster by the Council of Ministers, provided that the macroeconomic trigger conditions specified in the Loan Agreement are satisfied. The declaration must be accompanied by a damage and needs assessment prepared by the national disaster management agency and reviewed by a Bank-approved assessment team. Drawdown requests under the CAT DDO are processed within ten business days of receipt of a complete and satisfactory trigger documentation package.

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 sources (such as registration systems and population censuses) are more appropriate for estimating stocks of asylum-seekers, refugees and IDPs at a particular point in time, while other data sources (such as population tracking systems and border crossings) are more appropriate for estimating flows over a specific period. In general, there is a lack of comprehensive and up-to-date data available on all stocks and flows for a particular displacement situation (see Table 4). Consequently, data on flows might be used to estimate stocks, for example in the absence of government data, the stock of refugees in many industrialized countries is estimated by UNHCR based on 10 years of individual asylum-seeker recognition. And, especially in the case of IDPs, changes in the total population combined with some contextual analysis, may be used to deduce estimates of new internal displacement or returns. However, these approximations are flawed unless data on all other flows (births, deaths, repatriation etc.) are also available, which is not usually the case. Even a static figure for the stock of IDPs in a particular location might obscure substantial flows including new displacement and returns. Moreover, there are no common definitions of the various stocks and flows, and therefore the risk of double counting or gaps cannot be discounted. Usage context: primary mention, supporting mention, background mention.

population censuses
population tracking systems

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

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:
most recent year in our CRU dataset). We begin by computing average annual rainfall

and temperature for the nine datasets (CRU; 8 GCMs). Then we use a least-squares fit

generates nine benchmark annual datasets - CRU and eight GCMs - for each of the 372

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:
### 4.2 GLSS Cluster-Level Aggregation

To construct community-level outcome variables from GLSS household data, we aggregate household-level observations to the GLSS enumeration area level using survey-weighted means. We restrict this aggregation to GLSS enumeration areas with at least 10 interviewed households to limit noise from small-cluster estimates. The resulting GLSS cluster-level dataset comprises 378 enumeration areas distributed across all ten regions, with an average of 18 interviewed households per cluster.

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: This question is examined in Jordan using a unique dataset that links individual data on own schooling and parents ’ schooling for adults, from a household survey, with the supply of schools in the subdistrict of birth at the time the individual was of age to enroll, from a school census. The identification strategy exploits the variation in the supply of basic and secondary public schools across cohorts and subdistricts of birth in Jordan, controlling for year and subdistrict-of-birth fixed effects and interactions of governorate and year-of-birth fixed effects. The findings show that the local availability of basic public schools does, in fact, increase intergenerational mobility in education. For instance, a one standard deviation increase in the supply of basic public schools per 1, 000 people reduces the father- son and mother-son associations of schooling by 18 – 20 percent and the father-daughter and mother-daughter associations by 33 – 44 percent. However, an increase in the local supply of secondary public schools does not seem to have an effect on the intergenerational mobility in education.

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:
_Thailand_ . As for Thailand, it is the third largest country, fourth most populous and boasts the
second largest GDP of our countries. In terms of disasters, Thailand is mostly at risk to floods
and typhoons, but earthquakes happen occasionally, with the largest recorded being a 6.1
magnitude earthquake that occurred in May 2014. The lower risk compared to our other
countries is also mentioned by INFORM in their country profile of Thailand (INFORM 2019).

_Vietnam_ . The final country is Vietnam, which is the smallest, but has the third highest
population just below 100 million people. In terms of GDP, Vietnam rank fourth among our
five countries. When it comes to disaster risk, they are on par with Thailand in that INFORM
ranks them low and exposed primarily to floods and typhoons (INFORM 2019).

National Disaster Management Agency, B. N. P. B. 2016. "DiBi database (Data and Information
on Disaster in Indonesia)." http://dibi.bnpb.go.id/.

Rahman, Md. Mizanur, Dhyan Singh Arya, Narendra Kumar Goel, and Ashis Kumar Mitra. 2011.
"Rainfall statistics evaluation of ECMWF model and TRMM data over Bangladesh for
flood related studies." _Meteorological_ _Applications_ (Wiley) 19: 501-512.
doi:10.1002/met.293.

The underlying data are based on 2015 and combines census data with satellite images from DigitalGlobe. The population is allocated according to subdivision censuses once settlements have been identified from the satellite images.

(2018) used the underlying NPP-VIIRS DNB Daily Data to analyze selected natural disasters. They found that the images were useful for detecting damages and power outages, but that cloud coverage was a major limitation in the assessment.

The first dataset combines information on flood extent and flood depth from pluvial and fluvial flooding into one flood map. It was developed by the company Fathom, formerly known as SSBN. The map covers all of Vietnam at a resolution of about 90 by 90 meters.

satellite images from DigitalGlobe
flood map

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: Sources of information This work includes a descriptive analysis that allows us to identify how the prevalence of non- standard employment (NSE) has evolved in the last two decades in different regions of the planet, as well as the evolution of the profile of workers in those roles, in terms of their educational level, salary per hour, and type of tasks performed. This analysis was based mainly on periodic surveys of households that included information regarding the employment and educational situation of individuals. Although the denomination of this type of surveys varies from country to country, in all the cases analyzed there is usually a survey of annual or higher frequency that includes information required to identify the labor status of the individuals as well as to analyze the salary profile and education of the employed. However, it should be noted that the identification of the type of work relationship (standard or non- standard) is frequently limited in these data sources. Indeed, it is only possible to identify part-time employment and temporary employment (not in all cases) within the non-standard forms of employment mentioned in the previous section.

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: 2 Background Information 2. 1 Characteristics of West Bank and Gaza ’ s labor markets The labor markets of the West Bank and Gaza exhibit features typical of the broader Middle East and North Africa (MENA) region, but also have attributes that are highly unique. Additionally, important differences exist between the West Bank and Gaza. This section provides an overview of these characteristics. We use data from the Labor Force Surveys (LFS) of the West Bank and Gaza and we focus on 20-59 years old men. In Section 3. 1, we provide more information about the data sources and sample selection. We divide each labor market into five mutually exclusive and jointly exhaustive states: public sector employment, private formal sector employment, private informal sector employment, unemployment, and out of labor force. 1 We focus our discussion exclusively on men, as women ’ s labor force participation in both the West Bank and Gaza is very low, never reaching values above 25 %. This low participation rate is common in MENA countries and makes the role of the pandemic on women ’ s labor market outcomes relatively less important than other, more relevant structural factors.

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: 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.

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