Input: 4 household displacement and the destruction of household dwellings during the violent events. We are also able to measure conflict intensity across time – including peaks of violence at various stages of the conflict – at the district level from event data on violence intensity during the conflict in Timor Leste. We focus on primary school effects because only a small percentage of the Timorese population attended secondary school. Our results show mixed evidence for the impact of violent conflict on educational outcomes. Mirroring some of the findings of Bellows and Miguel (2006) and others, we find evidence for a rapid recovery of the education sector in Timor Leste, and of educational outcomes, particularly for girls. However, in line with emerging results in the micro-level literature, we find that the 1999 wave of violence in Timor Leste – as well as peaks of violence in the 1970s and 1980s – resulted in negative effects on primary school attendance and attainment. This effect is particularly strong for boys. We attribute the first result to a process of educational catch-up among girls in Timor Leste that started before the conflict and continued despite the conflict. Usage context: primary mention, background mention, supporting mention.

event data on violence intensity during the conflict

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Input: If registration is linked to the provision of services or other entitlements, there may be strong incentives to register births and new arrivals and weak incentives to deregister, leading to the inflation of the register over time or even instances of fraud and abuse (e. g. multiple registration, “ borrowing children ” etc.) (UNHCR 2003). Consequently, data from a refugee register may overestimate the number of refugees, requiring periodic corrective action through the verification of records. For example, in 2014 a verification of registration records for Somali refugees in the Dadaab camps in Kenya led to the deactivation of tens of thousands of records for individuals that are believed to have returned spontaneously to Somalia (UNHCR 2015). Additional problems with refugee registers include security concerns or inclement weather preventing refugees from accessing registration sites (UNHCR 2003) and the application of data protection principles. Registration of IDPs Individual registration is not as common a method of estimating numbers of IDPs as it is for refugees. Usage context: background mention, supporting mention, primary mention.

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Input:
**Figure** **2.** Source: WDR 2020 team, based on World Bank's World Development Indicators (database).
Note: The blue line represents the average of all pair-wise GDP correlation taken over all country-pairs
that include China. The orange line represents the average taken over all countries that include the
United States. The grey line represents country-pairs that contain neither the United States nor China.
The date corresponds to the midpoint of a 10-year rolling window.

Change in Production Connectivity

**Figure 4.** WDR 2020 team, based on World Bank's World Development Indicators (database) and World
Integrated Trade Solution (database). Note: Each dot represents a pair of regions-for example, East
Asia and Pacific and Sub-Saharan Africa, and Latin America and Caribbean and South Asia are two
different observations). The horizontal axis measures the change over time in production connectivity
defined as the total trade in intermediates as a share of GDP of both regions. The vertical axis measures
the proportional change in GDP correlation over time.

Source: WDR 2020 team, based on World Bank's World Development Indicators (database) and a classification of sticky vs. non sticky trade from Martin et al. (2018).

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Input: increase in earnings. Most importantly, the relationship between completing secondary and post-secondary schooling and wage earnings becomes significant only when the refugee sample is restricted to workers outside the camps (see Annex D, Table D.7). This indicates that refugees only benefit from education and are incentivized to invest in education if they can access work outside the camps. This highlights the importance of refugees’ access to the labor market without restrictions, particularly outside the camps, as a critical component to achieving positive long- term effects. Refugee outcomes in the labor market do not improve over time in Ethiopia. Annex D, Table D.7 also shows that, after adjusting for domain and demographic characteristics, there is a slight increase in the probability of working for each year that a refugee is in Ethiopia, by around one percentage point per year, but no change in the likelihood of being in a high-skill occupation, likelihood of working outside the camp, or in monthly earnings. Agriculture is an important source of livelihood for host households, but refugee households have low agricultural holdings, reflecting their inability to own land legally. Refugee households are less than half as likely as hosts to report an agricultural holding with

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Input: A map highlighting Medell ´ ın ’ s geographic position and the locations of the households interviewed for this study is provided in Figure 2, offering visual context to our research setting. Representativeness and stratification. VenRepS-Kids is designed to be representative of two groups of youth. The first group consists of Colombian children and adolescents, aged 5 to 17, born to Colombian parents. The second group encompasses Venezuelan migrant children and adolescents of the same age range, born to Venezuelan parents, who mi- grated to Colombia between 2016 and 2020. The sample was further stratified by gender and socioeconomic levels, using Colombia ’ s neighborhood income-based classification system that ranges from 1 to 6, where six indicates the wealthiest neighborhoods. Our 13 Usage context: primary mention, supporting mention, background mention.

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Input:
Global Public Health, June 2006; 1(2): 147�156

# HIV behavioural surveillance surveys in conflict and post-conflict situations: A call for improvement

P. B. SPIEGEL & P. V. LE

United Nations High Commissioner for Refugees

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

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Input: A recent global hazard analysis generated a comprehensive database of hazard events during 1975- 2007 from observed data and of event probabilities from geo-physical models (ISDR 2009). We combined this hazard information with city-specific population projections 2 It should be noted that well-documented evidence for such externalities is quite scarce. Their importance is usually taken as given: “ A building collapse may create externalities in the form of economic dislocations and other social costs in addition to the economic loss suffered by the owner. The owners may not have taken these consequences into account when evaluating specific mitigation measures. Consider the following example. A building toppling off its foundation after an earthquake could break a pipeline and cause a major fire, which would damage other homes that had not been affected by the earthquake in the first place. “ Kuenreuther and Roth (1998). See also www. quakesmart. org / index. php? option = com_content & view = article & id = 92 & Itemid = 209. But some experiences have been documented: “ As shown by research on the Great Hanshin-Awaji Earthquake, including that conducted by the Architectural Institute of Japan, Architectural Institute of Japan (1997), houses with inferior earthquake-resistant quality triggered large negative externalities in the neighborhood. For example, broken fragile houses blocked transportation networks, thereby preventing effective fire fighting and, by severing lifelines, they made recovery more difficult. ” (Nakagawaa et al. 2007). Usage context: background mention, supporting mention, primary mention.

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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).

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Input: In the third (Rahim Yar Khan) there is a large difference, with the census reporting that 1 percent of all school-going children attended madrassas, and the LEAPS showing that the fraction is closer to 3. 7 percent (Table II). There are three potential explanations for this difference. First, the LEAPS data is not representative of the district and could be off the mark for districts with wide variation in madrassa enrollment across rural and urban samples. Second, the experience of the last five years could have varied dramatically across districts — in some, the enrollment fractions did not change and in others it increased substantially. Third, the data could point to systematic problems with the census estimates from certain districts, or the statistical problems that arise when we try to estimate low-probability events. 3. 3 Explaining the Differences A number of reasons could account for differences between the estimates presented here and those in the popular press. 1. Differences in the sampling unit. Our estimates are all based on household surveys — an interviewer goes to a household and asks about the enrollment status of every child. Some census estimates of home rather than religious schooling in the United States — the former ranges from 1 to 2 percent (Bauman 2001) while the latter is closer to 8 percent (National Center for Education Statistics, 2001). 10 In our own analysis, we find the quality of the data generated by the Federal Bureau of Statistics in Pakistan to be consistently high. We have used the FBS Census of Private Schools (PEIP, 2000) to guide our fieldwork and feasibility study for LEAPS and found it tallied with the situation on the ground quite well, even in remote villages. Usage context: background mention, primary mention, supporting mention.

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Input: The third graph represents the kernel density of our productivity loss measure for observations with positive loss, which represents around 11 percent of country-year observations in our dataset. It gives an idea of the distribution of this variable across country-years. The distribution shows a long and thin upper tail driven by countries with repetitive and highly intense conﬂict history like Afghanistan or the Lebanon. The average productivity loss is 15 percent in this sample and one fourth of all country-year observations are associated with losses of more than 20 percent of productivity. Even if these estimates were drastically overestimated they indicate that the long run impact of mass violence through this channel could be substantial. 5. 2 Macro Evidence In this subsection, we investigate the correlation between the aggregate loss measure and output. For this purpose, we use the height loss measure from the previous sub- section to estimate the marginal eﬀect of an extra cm loss on log GDP. This serves two objectives. First, we explore whether the micro evidence can be used as a conduit for understanding the long-term damage to output from conﬂict. Second, we check whether the aggregate loss in output that we get is consistent with the micro estimates of marginal economic return to health. Usage context: background mention, primary mention, supporting mention.

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Input:
The
 ongoing
 presence
 of
 armed
 actors
 in
 places
 of
 displacement
 and
 potential
 return
remains
 a
 key
 concern.
 Communities
 have
 been
 subject
 to
 protection
 risks
 associated
with
 the
 presence
 of
 military
 units
 including
 forced
 labour,
 forced
 recruitment
 and
 the
payment
 of
 “taxes.”
 In
 addition,
 Myanmar
 is
 believed
 to
 have
 a
 large
 number
 of
 children
in
 armed
 conflict,
 including
 child
 soldiers,
 with
 both
 the
 Government
 and
 various
 non-‐
state
 armed
 actors
 having
 been
 responsible
 for
 the
 recruitment
 of
 minors.
 On
 27 [th] June
2012,
 the
 United
 Nations
 Country
 Task
 Force
 on
 Monitoring
 and
 Reporting
 (CTFMR)
and
 the
 Government
 signed
 a
 Plan
 of
 Action
 with
 regards
 to
 underage
 recruitment
 in
 the
Myanmar
 Army.
 Procedures
 are
 underway
 for
 the
 systematic
 identification
 and
discharge
 of
 verified
 minors
 from
 the
 national
 forces.
 However,
 plans
 of
 action
 with
non-‐state
 armed
 groups
 in
 the
 South-‐East
 have
 not
 yet
 been
 agreed
 and
 it
 remains
 to
 be
seen
 whether
 the
 Plan
 of
 Action
 with
 the
 Government
 will
 be
 comprehensively
implemented.

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Input: 11 There may be grounds for skepticism about these estimates for madrassa enrollment. Since the data were collected prior to 2001, geopolitical changes after September 11 could have led to greater madrassa enrollment. In addition, the household-based survey faces the usual problems of accurately estimating a low-probability event — although enrollment is less than 1 percent in these surveys, the sampling error is large (see Bauman, 2001, for a description of similar problems in estimating home-schooling in the United States). Finally, while the census of populations does not face the problem of small samples, it is not that recent (1998) and some may have reservations regarding the quality of government data. 10 The LEAPS census of schooling choice conducted in 2003 provides a rough check on these numbers (see appendix for details). This census was conducted in three districts of Punjab and villages were chosen randomly based on the criterion that each village must have at least one private school. Typically, this means that the villages lies somewhere between fully urban and fully rural populations and are not representative of the districts that they are in. Estimates from the LEAPS census show that as a percentage of enrolled children, the numbers in two of the three districts are slightly higher than those of the population census.

census of populations
household-based survey

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Input: The Disaster and Emergency Management Presidency of Turkey (AFAD) provides information on the number of Syrian refugees. The numbers used in this paper are taken from Erdogan (2014), who draws on information from AFAD and the Ministry of Interior and reports the number of refugees by NUTS 2 subregion. To construct our instrument we use the Syrian Labor Force Survey for 2010 (the year before the beginning of the war). Finally, Google Maps was used to derive the travel distance between each governorate in Syria and the most populous city in each NUTS 2 subregion in Turkey. 14 Most recently, in January 2016, labor market access for Syrian refugees in Turkey was eased considerably. Importantly, they now can benefit from vocational training under the Turkish Employment Agency, employers will be able have to Syrians comprise up to 10 percent of their staff, and seasonal workers are exempted from the work permit, see http: / / www. resmigazete. gov. tr / eskiler / 2016 / 01 / 20160115-23. pdf. It is of course too early to evaluate the impact of these legislative changes. 15 Hurriyet Daily News (February 2015) http: / / www. hurriyetdailynews. com / turkey-urges-worlds-help-on- syrian-refugees-as-spending-reaches-6-billion. aspx? pageID = 238 & nID = 78951 & NewsCatID = 359. 16 Starting with 2014 there was a change in the design of the Household Labour Force Survey to ensure full compliance with European Union standards. This has caused some difficulty in making comparisons across years. However, our identification strategy does not use aggregate variation across years for identification and should hence be unaffected by the changes to the design of the survey. Usage context: supporting mention, primary mention, background mention.

Household Labour Force Survey
Syrian Labor Force Survey

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

Pakistan Integrated Household Survey
1998 Census of Population

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

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Input:
HIV behavioural surveillance surveys 151

Results

A total of 40 BSS or KAP surveys were identified, of which 31 (77.5%) were
eligible according to the inclusion criteria. The 31 eligible surveys were undertaken between 1998 and 2005 in 14 countries. There were 12 countries (25
surveys) in Africa: Angola (1), Eritrea (1), Ethiopia (2), Kenya (2), Rwanda (2),
Sierra Leone (3), Somalia (1), South Africa (1), Sudan (2), Tanzania (3), Uganda
(5) and Zambia (2); and 2 countries (six surveys) in Asia: Nepal (2) and Thailand
(4). Eight (25.8%) surveys were undertaken in conflict settings, nine (29.0%) in
post-conflict settings and 14 (45.2%) in relatively stable countries hosting
refugees. Among some of the eligible surveys, more than one affected population
was studied; refugees were included in 28 (90.3%) surveys, IDPs in six (19.4%)
surveys, returnees in three (9.7%) surveys and surrounding host populations
in six (19.4%) surveys. The primary organizations responsible for the surveys
were NGOs, (23 surveys, 74.2%), CDC four surveys (12.9%), a United Nations
agency three surveys (9.7%) and one government survey (3.2%). The sample
sizes of the surveys ranged from 148 to 7,484, with a mean of 1,261 and a median
of 549 persons. Fourteen (45.2%) of the 31 surveys were classified as
reproducible (see Table II). Surveys undertaken by NGOs were significantly
less reproducible than those undertaken by non-NGOs (chi-square test,
p �/0.05).

HIV behavioural surveillance surveys
BSS or KAP surveys

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

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Input: 25 less cohesion. The increase in solidarity is less apparent among refugees where the majority (53 %) stated that the crisis had no effect on solidarity. Figure 18: Levels of trust, by group (June) (%) Source: Listening to Displaced People Survey, 2014. Perceptions that different groups have of others are important elements of peace. When asking for the degree to which neighbors, other villagers and people from other ethnic groups can be trusted the survey finds positive outcomes. Although all groups trust people from other ethnic groups slightly less, the general level of trust is high and it remains stable over time. Finally, consider how IDPs, refugees and returnees envision the future of Mali. The majority of refugees in Mauritania vie for an independent or autonomous North, while the majority of IDPs, returnees and refugees in Niger wish to see full government control over the North. 20 20This contradicts, in part, findings of an Afrobarometer perception survey on causes and consequences of the conflict in Mali conducted in December 2013.

Displaced People Survey
Afrobarometer perception survey

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Input: According to the 2012 Institutional Profiles report, the quality of public services and its territorial coverage, which was weak to being with, have significantly deteriorated since 2006. 1 A combination of rising poverty, rising insecurity, and deteriorating public services have further strained inter-communal relations and contributed to deteriorations in social cohesion. Many Lebanese youth do not trust their state and become disillusioned as they are not able to affect their own life or contribute productively to society at large. 2 Political and civic engagement is reported to be low (Status of Women in the Middle East and North Africa Survey Project, 2010). 3 In an already fragile context with a highly complex political, religious and social landscape consisting of 18 religious sects, numerous political parties, and large numbers of refugees, many Lebanese 1 On the quality of public services indicator, Lebanon ’ s score declined from 2. 5 in 2006 to 0. 8 in 2012 on a 4-point scale. On the territorial coverage indicator, its score went down from 2. 7 in 2006 to 1. 5 in 2012. 2In a Gallup World Poll, Lebanese reported low confidence in (a) their national government (37 percent) and the judiciary, (b) the honesty of elections (15 percent), and (c) the honesty of government (4 percent) (World Bank, 2016). 3 According to the SWMENA survey, only 18 percent of Lebanese women are members of an organization, compared to 34 percent of men. Men are more likely to be members of a political organization than women (21 percent of men vs. 7 percent of women), whereas women are more likely to be active in religious groups and charity organizations than men. Usage context: supporting mention, background mention, primary mention.

Middle East and North Africa Survey Project

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Input: 20 between 1948 and 1965, with increases in the percentage of adults with religious education in the cohorts born after this date. There is also wide geographical dispersion in the prevalence of madrassa education in Pakistan. Although all districts report that less than 2. 5 percent of children in the relevant age group (children between the ages of 5 and 19) are going to madrassas, the Pashto speaking belt that borders Afghanistan stands out in terms of the popularity of madrassas as an educational choice. The notion that the madrassa movement coincided with resistance to the Soviet invasion of Afghanistan is supported by the 1998 data from the population census. The increase in the stock of religiously educated individuals starts with the cohort that came of age in 1979 (the year of the Soviet invasion of Afghanistan) and the largest increase is for the cohort co-terminus with the rise of the Taliban. Combined with the fact that the largest enrollment percentage in Pakistan is in the Pashtun belt bordering Afghanistan, this suggests events in neighboring Afghanistan influence madrassa enrollment. Is there something intrinsic about Pashtun sensibility or tribal culture that leads to higher madrassa enrollment? The differentiation of the Pashtun and non-Pashtun districts does not extend to Pashtun and non-Pashtun households in the LEAPS data. Usage context: primary mention, background mention, supporting mention.

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Input: Our evaluation explicitly investigated these spillovers by including household-level indicators such as food security and attitudes of the household head toward gender norms. Our results show strong impacts on economic outcomes, including large and statistically significant increases in employment and earnings of EPAG participants. We show mixed results on empowerment- related outcomes, and very little evidence of spillovers on non-participants. Self-assessed measures of self-confidence show huge gains, as does ownership and control over monetary resources such as savings. The remainder of the paper is organized as follows: Section 2 describes the EPAG project including some of its innovative design features and implementation details. Section 3 reviews the methodology of the evaluation and Section 4 presents results on the three groups of outcomes discussed above: economic, empowerment, and spillovers. Section 5 includes a short discussion of cost-effectiveness. Section 6 presents a series of robustness checks and Section 7 concludes with a discussion of next steps and policy implications. 2. The EPAG Project The EPAG project is part of a larger Adolescent Girls Initiative (AGI) administered by the World Bank with support from the Nike Foundation and the Governments of Australia, the United Kingdom, Norway, Denmark, and Sweden. Launched in Washington DC in October 2008, the AGI was spearheaded by President Ellen Johnson Sirleaf, who signed on to undertake the initiative ’ s first pilot project in Liberia. The Liberian pilot was launched in March 2010 and has served as a role model to seven subsequent pilot projects in Rwanda, South Sudan, Nepal, Afghanistan, Haiti, Jordan, and Lao PDR. Under the global AGI, young women and adolescent girls are given a package of skills training and complementary services in order to facilitate their successful transition to employment. In the case of EPAG, the intervention consisted of a six month phase of classroom-based training, followed by a six 4

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Input: 5.1.3 Multidimensional poverty ............................................................................................................................................................................................................. 46 5.1.4 Food security........................................................................................................................................................................................................................................... 47 5.1.5 Shocks and coping strategies....................................................................................................................................................................................................... 48 5.2 Determinants of welfare......................................................................................................................................................................................................................................... 49 5.3 Cost of basic needs for refugees ..................................................................................................................................................................................................................... 53 6. Markets and Opportunities ....................................................................................................................................................................................................................................... 56 6.1 Spatial disparities in refugees labor market access and outcomes...................................................................................................................................... 57 6.2 Effects of local factors on refugees’ labor market outcomes...................................................................................................................................................... 61 7. Social Cohesion...................................................................................................................................................................................................................................................................... 63 7.1 Attitudes between refugees and hosts...................................................................................................................................................................................................... 64 7.2 Social interactions ...................................................................................................................................................................................................................................................... 68 8. Policy Recommendations ........................................................................................................................................................................................................................................... 72 References ............................................................................................................................................................................................................................. 77 Annexes ................................................................................................................................................................................................................................. 82 Annex A: Description of Refugees by Country of Origin.............................................................................................................................................. 83 Annex B: Refugee Policies in Ethiopia.............................................................................................................................................................................. 85 Annex C: Survey Design and Methodology.................................................................................................................................................................... 92 Annex D: Descriptive Statistics and Regression Results............................................................................................................................................. 97 Annex E: Robustness Checks of Refugees’ Consumption.......................................................................................................................................... 124 Annex F: Comparison of Results from Skills Profile Survey and SESRE................................................................................................................. 128 TABLE OF CONTENTS Figure ES.1: Desired location in three years ����������������������������������������������������� iv Figure ES.2: Expected location in three years ��������������������������������������������������� iv Figure ES.3: Poverty incidence........................................................................... v Figure ES.4: Food insecurity scale...................................................................... v Figure ES.5: Refugee employment and proximity to resource hubs .................. vi Figure ES.6: Host response to “Refugees are good people” ............................ vii Figure ES.7: Host response to “Would you feel comfortable having

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: informal sector in surrounding communities or the camps., this may include selling aid rations on the local market, informal trade, and economic exchange, or working for local NGOs and UN agencies (ReDSS, 2018). Extensive research has shown that not being able to enter local labor markets legally is detrimental to refugees’ ability to earn for their families, and for them to find an occupational match that maximizes the benefits they contribute to Ethiopia (World Bank, 2023). Because of conflict, the SESRE data collection could not include refugees in the Tigray region in Ethiopia, where most Eritrean refugees were hosted before the conflict. Since outbreak of the conflict in November 2020, many Eritrean refugees moved to Addis Ababa, and many fled from the Mai Ani and Adi Harush refugee camps in Tigray to the newly established refugee hosting site of Alemwach, Dabat in the Amhara region. Between February and July 2022, over 15,000 refugees relocated from the Tigray camps to Alemwach, and an additional 7,000 refugees were resettled in November 2022 following the cessation of hostilities (UNHCR, 2022). Before the conflict, 64 percent of all Eritrean refugees were hosted in camps in Tigray and 36 percent in camps in Afar (UNHCR,

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

UNHCR statistical population online dataset

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Input: Combining almost 50, 000 responses to 11 cross-sectional surveys between 2017 and 2021, displacement is negatively associated with perceptions of social cohesion in aggregate. But at the individual level, those who report hosting displaced populations in their communities often have higher perceptions of social cohesion. These results are strongest among respondents who self-report hosting IDPs as opposed to refugees, but important heterogeneity across indicators, local context, and gender should guide policy meant to promote social cohesion in forced displacement. This paper is a product of the Social Sustainability and Inclusion Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http: / / www. worldbank. org / prwp. The authors may be contacted at ppham @ hsph. harvard. edu. Usage context: primary mention, supporting mention, background mention.

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Input: The resulting migration matrices should be viewed as work in progress, but they are an important step in an ongoing global effort to improve migration data. The matrices can be readily updated as additional or superior information surfaces, and they can easily be extended to include future census rounds. Bilateral datasets of international migration are rare. Attempts to create them have focused almost exclusively on industrialized countries as destinations because these countries have more accurate and more frequently produced data. Harrison and others (2003) calculate bilateral remittances for the countries of the Organisation for Economic Co-operation and Development (OECD) together with the 27 largest nonmembers. These estimates are based on international bilateral migrant stock data that the authors also provide, although many of the data are derived from the Trends in International Migration (OECD 2002). This report, published annually since 1973, was arguably the most comprehensive guide to international migration for many years and has been the basis for many studies (see, for example, Mayda 2007). More recently, the OECD has developed a database that provides a comprehensive overview of migration to OECD countries in 2000 (OECD 2008). These data are disaggregated by a number of covariates including age, gender, educational attainment, and place of birth.

international bilateral migrant stock data

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Input: 15 Source: Authors ’ calculations based on data from the High Frequency Surveys of Ethiopia (2017), Nigeria (2018), Somalia (2017), South Sudan (2017) and Sudan (2017). As the Sudanese sample surveys IDPs living in the Abu Shouk and El Salam camps, we must understand these deprivations with the background that these settlements were created as emergency and crisis responses rather than durable, long-term solutions (Sudanese Government ’ s Joint Mechanism for Durable Solutions 2019). Although Sudan does have a national electric grid that supplies electricity to the urban and peri-urban areas of the nearby city El Fasher, IDP communities living in the camps report limited connection to the city ’ s electricity supply, reflected in the high deprivations in the electricity and cooking fuel indicators. The ad-hoc construction of dwellings in the two camps explains why 71 % of the IDP households in Abu Shouk and 65 % in El Salam live in tukuls or other permanent mud or wood structures (Sudanese Government ’ s Joint Mechanism for Durable Solutions 2019: p. 50), both of which register as unimproved housing types. Usage context: primary mention, background mention, supporting mention.

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Input:
data source listed most prominently in the announcement was the Emergency Food Security  and Nutrition Assessment (EFSNA), which was conducted between November and December

the IPC classification. For example, the EFSNA avoided the two most conflict-affected gover norates, was potentially plagued by a host of logistical difficulties given the security situation

by the WFP used in this analysis and the Gallup World Poll both find that the size of the

displaced population is up to three times as large as is being identified by the Task Force for  Population Movement (TFPM), which is the official source used in the IPC 2017 classification

occur. This article utilizes the mobile Vulnerability and Assessment Mapping Survey (mVAM)

Emergency Food Security  and Nutrition Assessment (EFSNA)

Emergency Food Security  and Nutrition Assessment

Task Force for  Population Movement (TFPM)

mobile Vulnerability and Assessment Mapping Survey (mVAM)

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Input: UNICEF (2017) reports that for boys, child labor, school violence, and the high costs of schooling (for transportation and stationery supplies) are the main barriers to their enrollment. For girls, barriers include the distance to the nearest school, the high cost of transportation, the need to help with household chores, health problems, and families refusing to educate their daughters. According to the JD ‐ HV database, the most common reasons parents gave for their children not attending school were financial constraints (35 percent), lack of capacity in schools (29 percent), or that children were required to work to support their family (14 percent). By 2016, the enrolment rate of Syrian refugee school ‐ age children in Jordan was 83 percent, 54 percent in formal education, and 29 percent in nonformal education (World Bank 2017b). 10 Refugee Employment It has been hard for refugees to find work in Jordan. The slowdown in growth in Jordan pre ‐ dates the arrival of Syrian refugees and the economy has been increasingly unable to absorb new labor market entrants. Between 2010 and 2016, labor force inactivity increased, employment decreased, and unemployment increased in Jordan (Malaeb and Wahba, 2018).

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:
Our main specification for the poverty line estimations defines an expenditure threshold of R$500 to
classify lumpy (all above) and not lumpy (all below) items. Items that are above the threshold are thus not
included in the consumption aggregate as it is assumed that they are infrequently purchased, and in many
cases, an accurate incorporation into the poverty line calculation would be by estimating a value of the
flow of services they provide to the owner. The data required to run those estimations is not available in
POF 2017/18.

Below we list the items that were excluded in our main specification by POF module.

by floods, and which strategies they use to cope and adapt.
These insights are based on firm survey data collected in

2018 using a tailored questionnaire, covering a sample of

more than 800 firms. To assess the impact of disasters on
businesses, the study considers direct damages and indirect
effects through infrastructure systems, supply chains, and
workers.

This study presents evidence from a dedicated Tanzanian firm survey conducted with 837 businesses in Dar es Salaam and the provinces of Tanga and Dodoma.

The survey's target population was all 58,959 firms in Dar es Salaam, Tanga, and Dodoma that were registered with the National Bureau of Statistics' (NBS) in 2015.

firm survey data
dedicated Tanzanian firm survey

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Input: using a regression analysis to compare the earnings of refugees and hosts and how this wage gap changes after adjusting for the effects of demographic and job characteristics. Column 1, Annex D, Table D.6 shows that, after controlling for the domain, monthly earnings is 70 percent lower for refugees than for hosts. After controlling for age, gender, and education in Column 2, this earnings gap remains at 64 percent. This means 0 20 40 60 80 100 Camp Hosts Male Camp Refugees Male Camp Hosts Female Camp Refugees Female Employed Unemployed, searching Percent Unemployed, not searching Inactive not in school Inactive in school Figure 3.5: Work status by gender Source: World Bank Staff based on SESRE 2023. 0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 Female Male Figure 3.6: In-camp refugee share employed by age Source: World Bank Staff based on SESRE 2023. Jobs and Livelihoods 30 that, after adjusting for any differences explained by age, gender, and education, refugees still earn significantly less than hosts. Column 3 indicates that refugees face this same earnings gap even after adjusting for differences explained by occupation and industry. Only after restricting the

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Input: First, there is reason to believe that better service delivery may aﬀect citizens ’ willingness to defer to the tax department only through its eﬀect on improved outcomes that matter for citizens ’ livelihoods. Unless improved services and infrastructure have a positive impact on citizens ’ welfare, indi- viduals are unlikely to credit the government for these outputs (Sacks and Levi, 2010). The Afrobarometer ’ s objective measures of service delivery only denote the presence or absence of infrastructure and services. The data do not indicate the condition of the services and infrastructure. Citizens may perceive and reward relative improvements or sanction de- teriorations in services, rather than the absolute level of service quality they receive. If services deteriorate or improve, taxpayers may alter their beliefs about governments ’ performance and should attempt to adjust their terms 10I also tested whether there is a relationship between the presence of a concrete road, health clinic, post oﬃce and electricity grid in the enumeration areas and respondents ’ willingness to pay taxes. None of these objective indicators except for the presence of an electricity grid were signiﬁcant at the p < 0. 05 level. The presence of an electricity grid is negatively associated with the willingness to defer to the tax department. 17

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: 3 restrictions on job search, but they do not benefit from the same humanitarian assistance refugees in camps benefit from (Betts et al., 2017b). We investigate the determinants of the vulnerability of Syrian refugees to the COVID-19 shock in Jordan. In particular, we examine whether Syrian disadvantage during the shock is completely explained by institutional barriers reflected in precarious jobs and residency in camps, or if they experience added vulnerability by virtue of their refugee status. We use retrospective data on the job histories of young Jordanian and Syrian men between the ages of 16 and 30 years from the Survey of Young People in Jordan (SYPJ) (Assaad et al., 2021a; OAMDI, 2022) to construct a synthetic semi-annual panel dataset that tracks the job finding and separation experiences of respondents. We compare the trends of job finding and separation across the two populations before and after the onset of the COVID-19 pandemic. We find that Syrians have generally experienced lower job finding rates and higher job separation rates compared to Jordanians, although the differences were generally not statistically significant prior to the pandemic. With the onset of the pandemic, Syrians became significantly disadvantaged on both measures. Controlling for the type of employment showed that workers whose last job was informal were disadvantaged on both measures compared to formal workers regardless of nationality. Usage context: supporting mention, primary mention, background mention.

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Input:
Score Grade 6 512.2 527.3 550.0 527.8 515.6 (100.8) (98.96) (95.74) (105.8) (100.7) Enlace taker Grade 9 0.712 1 1 0.769 0.764 (0.453) (0) (0) (0.421) (0.425) Enlace taker Grade 12 0.323 0.453 1 0.370 0.379 (0.468) (0.498) (0) (0.483) (0.485) Girl 0.469 0.498 0.524 0.473 0.535 (0.499) (0.500) (0.499) (0.499) (0.499) Private School Grade 6 0.0822 0.0970 0.119 0.0578 0.0954 (0.275) (0.296) (0.323) (0.233) (0.294) Mother has lower secondary 0.539 (0.499) Father has lower secondary 0.586 (0.493) Mother is white collar 0.114 (0.318) Father is white collar 0.207 (0.405)

Notes: The table shows the mean and standard deviations of all students matched in the ENLACE panel in 2007
(column 1), 2010 (column 2) and 2013 (column 3). Column 4 displays additional variables from student and parents
surveys that were applied to a sample of ENLACE takers. Column 5 reports statistics for the sample of identified
twins in grade 6. Data: ENLACE panel.

Enlace Score 0.213 0.375 -0.0630 0.114 (0.854) (0.856) (0.778) (0.808) College Student 0.630 1 0 0.437 (0.483) (0) (0) (0.496) Employed 0.379 0.263 0.577 1 (0.485) (0.440) (0.494) (0) Upper Secondary GPA -0.0219 0.135 -0.289 -0.0835 (1.007) (0.995) (0.970) (0.987) Girl 0.564 0.546 0.596 0.502 (0.496) (0.498) (0.491) (0.500) Private Upper Secondary 0.175 0.203 0.129 0.134 (0.380) (0.402) (0.335) (0.340) Urban resident 0.848 0.912 0.740 0.814 (0.359) (0.283) (0.439) (0.389) Age 19.18 19.16 19.21 19.23 (

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Input:
However, specifying a control variable for which national accounts or survey data is needed (such as the share of agriculture in GDP or the share of the population engaged in agriculture) would run counter to the purpose of this study, which is to see whether proxies such as nightlights can be used to estimate growth in areas (sub-national or supra-national) for which there are no national accounts or survey data. One option is to use rainfall or vegetation data, which share many of the desirable features of nightlights data, to proxy the performance of the agricultural sector.

In the first step, we estimate national GDP based on specification (1). The estimated GDP is divided into two parts based on the share of agriculture in the economy (based on actual national accounts data): Agricultural GDP and industrial and services GDP. In the second step, we distribute industrial and services GDP among the subnational units in proportion to their share of national nightlights.

6 This is in contrast to Ghosh and others (2010) who use the Landscan data to distribute agricultural GDP among
sub-units.

16

<!-- PAGE 19 -->
##### **5.1 Kenya**

survey data
rainfall or vegetation data
nightlights data
national accounts data

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

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

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Input:
For this reason, the World Bank's Development Economics Vice Presidency (DEC) has established an open web facility, the XCO2 database, [19] that pre-filters the OCO-2 data and publishes monthly mean concentration anomalies for all terrestrial cells of a 25 km global grid (G25). The website will also publish annual change estimates for urban areas by statistical significance class and provide information that links G25 grid cell IDs to IDs for urban areas and national administrative units (levels 0, 1 and 2). We believe that this web facility will contribute to the global effort to reduce CO2 emissions as rapidly as possible.

Byers, L., J. Friedrich et al. 2021. A Global Database of Power Plants. World Resources
Institute.

JPL/NASA. 2021. OCO-2 Data Set. Jet Propulsion Laboratory, California Institute of
Technology. https://co2.jpl.nasa.gov/?mission=oco-2

XCO2 database
Global Database of Power Plants

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Input:
survey, which did not include a benchmark measure as did the Dantlait survey. Figure 3

Dantlait survey results can be extrapolated to a sample of households in other parts of Niger,

It is important to note, however, that the Dantlait survey was limited to cattle. Small

precision of these estimates, and the Dantlait survey only collected data on cattle. Throughout

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Input:
using spatial information. Geographical coordinates of enumeration areas in GLSS are from

Ghana Statistical Services (GSS). [2] Point coordinates (global positioning system [GPS]) for the

The Raw Materials Data are from InterraRMG (2013). The data set contains information on

past or current industrial mines. All mines have information on annual production volumes,

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

Labor Force Surveys
Multiple Indicator Cluster Surveys
Living Standards Measurement Study

individual registration of refugees and asylum seekers

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Input: 23 and females. 10 The results are shown in table S. 1 in the supplemental appendix. The baseline effects of basic schools on educational attainment and their effects on mobility are stronger and often more significant than those estimated in table 4 for both males and females. A second concern is that Jordan received a large influx of Palestinian refugees in the aftermath of the 1967 Arab-Israeli War. While refugees benefited from the UNRWA basic schools, their educational attainment and intergenerational educational mobility were perhaps subject to a different set of constraints than those facing other Jordanians. Thus, as a robustness check, individuals who are likely to be Palestinian refugees were excluded from the sample. Since the JLMPS 2010 does not allow directly identifying Palestinian refugees who are now mostly Jordanian citizens, two indirect methods were employed to identify individuals who are likely to be Palestinian refugees. Method 1 excludes individuals born in subdistricts where the percentage of individuals who were ever enrolled (or are currently enrolled) in an UNRWA school exceeds ten percent out of all individuals below 36 years of age in the sample. Method 2 excludes individuals born in subdistricts where the percentage of UNRWA schools exceeds ten percent of the total number of schools. The results for the restricted sample according to both methods are shown in tables S. 2 and S. 3 respectively.

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: Historical trends and patterns of forced displacement: Insights from available global data This section provides an overview of the available global data on conflict-induced forced displacement, drawing largely on UNHCR ’ s published data on asylum-seekers, refugees and IDPs. 41 Data are presented visually in a series of figures to highlight the scope and character of the current global forced displacement crisis and identify historical trends and anomalies. These data largely focus on the scale and trends in conflict-induced displacement (i. e. the numbers of forced displaced) with some coverage of other elements such as demographics, location and accommodation. Globally, there has been an unprecedented increase in the numbers of displaced people over the last decade, largely explained by the expansion in the number of reported IDPs. Historical data show a substantial increase in the numbers of forced displaced (see Figure 3), however the expanding geographical scope and quality of displacement monitoring systems are likely to account for much of the increase in forced displacement figures. The numbers of refugees under UNHCR ’ s mandate have recorded a number of variations over time, peaking in the early 1990s (at a level 10 percent over 2015 numbers) with the conflict and displacement associated with the end of the Cold War. The number of Palestinian refugees steadily has increased steadily over time, largely as a result of natural growth. IDP numbers (for which the underlying data are the least robust) have recorded the largest progression as a consequence of: (a) the expanded scope of monitoring efforts (IDPs were not counted before 1989 and methodologies were 41 UNHCR ’ s data only include IDPs protected or assisted by the agency. Usage context: background mention, supporting 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

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Input: Figure A2: Refugees a burden for SSA? Panel A: Not weighted by economic capacity Usage context: background mention, supporting mention, primary mention.

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Input: The employment arm also signiﬁcantly improves cognitive function as measured through an index of memory and basic arithmetic tests, a ﬁnding consistent with a large psychol- ogy literature documenting the relationship between cognitive processes and depression (Semkovska et al., 2019). As with physical health, improvements to cognitive function are unlikely to be a direct product of the employment task itself, which was speciﬁcally de- signed to require no literacy or mathematical skill. Rather, these results are suggestive of a downstream impact to reducing depression through the experience of employment. Finally, we ﬁnd no change in time preferences: treated individuals are no more or less likely to discount the future relative to control counterparts, although results may have diﬀered had we engaged participants in an eﬀort or consumption-based time preference game rather than a ﬁnancial one. However, we ﬁnd a substantial increase in risk tolerance among the employed. A greater preference for risk-taking may be indicative of employment serving as a form of psychological ‘ insurance ’ that allows participants the mental bandwidth to exercise greater risk. This is consistent with the positive impacts of employment on stability as well as with a key motive underlying universal basic income (UBI) in the developing world (Banerjee, Niehaus, and Suri, 2019). Interestingly, however, we document no parallel increase in risk tolerance in the cash transfer arm. Our result on risk preference also echoes a potential consequence of depression and anxiety described in Ridley et al. (2020), although empirical 15 Usage context: supporting mention, primary mention, background mention.

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Input: The third graph represents the kernel density of our productivity loss measure for observations with positive loss, which represents around 11 percent of country-year observations in our dataset. It gives an idea of the distribution of this variable across country-years. The distribution shows a long and thin upper tail driven by countries with repetitive and highly intense conﬂict history like Afghanistan or the Lebanon. The average productivity loss is 15 percent in this sample and one fourth of all country-year observations are associated with losses of more than 20 percent of productivity. Even if these estimates were drastically overestimated they indicate that the long run impact of mass violence through this channel could be substantial. 5. 2 Macro Evidence In this subsection, we investigate the correlation between the aggregate loss measure and output. For this purpose, we use the height loss measure from the previous sub- section to estimate the marginal eﬀect of an extra cm loss on log GDP. This serves two objectives. First, we explore whether the micro evidence can be used as a conduit for understanding the long-term damage to output from conﬂict. Second, we check whether the aggregate loss in output that we get is consistent with the micro estimates of marginal economic return to health.

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 majority of surveys reported the same or similarly worded internationallyaccepted HIV indicators for prevention and misconception (except for the
misconception question on the possibility of getting HIV from sharing a meal with
someone who is infected with HIV); however, few reported disaggregated
indicators by age and gender (Table III). The majority of surveys did not report
the same or similarly worded internationally-accepted HIV indicators for practice
and attitudes; few reported disaggregated indicators by age or gender (Table III).
Twenty-six (83.9%) of the surveys asked an HIV practice question with 14
(45.2%) asking the question that was the same as or similar to the internationallyaccepted practice indicator that we chose (Table I); five (35.7%) disaggregated
the indicator by gender and age (Table III). Twenty-one (67.7%) of the surveys
asked HIV attitude questions with less than the majority asking at least one
question that was the same as or similar to the internationally-accepted attitude
indicators (Table I); few disaggregated by gender and age (Table III).

internationallyaccepted HIV indicators for prevention and misconception

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Input: destination. Building on a growing literature documenting the relationship between subjective welfare and relative income, Fafchamps and Shilpi (2008) show that Nepalese households care about their consumption level relative to that of others in the same location. If this is the case, it is conceivable that migrants choose their destination not so much for the absolute gain in income it may provide but for the gain in relative status that would ensue. For instance, if returns to education and ability are higher in an urban setting, an educated individual may improve his relative position in society by moving from a rural to an urban setting. To investigate this possibility, we estimate equation (4) using the log of relative income (or relative consumption) as dependent variable and construct a predicted relative income measure using the same formula (5). These are shown in the second panel of Table 1. Theories of work migration predict that individuals move to increase their utility or welfare. The 1995 / 96 NLSS asked respondents a number of questions regarding their subjective satisfac- tion level with various dimensions of consumption — namely, food, clothing, housing, health care, and child schooling. They were also asked their subjective satisfaction with their level of total income. Usage context: background mention, primary mention, supporting mention.

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Input: violent conﬂict. Besley and Mueller (2015a) argue that foreign investors seem to know that growth volatility changes with strong executive constraints and therefore react signiﬁcantly to their adoption. In summary, the literature suggests that a lack of constraints on executive power at the country level could play a key role in building inequalities across regions and ethnic groups. In the absence of strong executive constraint, we expect regions populated by ethnic groups that have access to executive power to perform better relative to others due to ethnic favoritism. Conversely, excluded ethnic groups should experience relatively worse economic performance compared to other groups in the absence of such constraints. 46 To test these hypothesis we use data on ethnic groups ’ access to executive power and night light intensity from the GROWup Research Front-End (RFE Release 2. 0) dataset and executive constraint data from the Polity IV dataset. We use night light intensity as a proxy for economic activity at the ethnic group level. 47 Night light data has the beneﬁt of being available on a yearly basis and of being measured at the local level where there is poor availability of statistical data. Usage context: primary mention, supporting mention, background mention.

GROWup Research Front-End
Polity IV dataset

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Input: (2009) have shown that, in Nepal, subjective welfare is negatively associated with geographical isolation. Census data on total population and population density in each district are used as proxies for urbanization and geographical proximity: the denser the population, the less geographically isolated individuals are likely to be. We also include data on the average elevation in each district. Nepal being a mountainous country, the higher the average elevation of a district, the more costly it is to build roads, raising transport and delivery costs to the district. Ceteris paribus, we expect migrants to seek out districts with a higher population density and a lower elevation. 4 Econometric results 4. 1 Univariate analysis We now investigate the choice of migration destination. We begin with simple univariate analysis. Variables are of the form ∆ h is = xh s − xh i where i is the district of origin of migrant h and s is each of 74 possible districts of destination. We examine the average value of ∆ h is for the destination district and compare it to the value of ∆ h is for alternative destinations. For instance, let xh s be population density in district s. The average value of ∆ h is for the actual destination of the migrant tells us whether the destination district is more densely populated than the district of origin. Usage context: background mention, supporting mention, primary mention.

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

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Input: If that person is a 10, where would you put yourself? ” Locus of Control The standardized total score from responses to four locus of control questions. “ In the last 7 days, how many days did you feel that to a great extent your life is controlled by accidental / chance happenings... ” Allocation Decision Game Indicator (yes / no) for response to an oﬀer to participate an allocation committee to decide how money is spent. Participants are oﬀered the opportunity to make a resource allocation decision for their community or have another individual (an NGO worker, an “ expert ”, or another refugee) make the decision. Stability Index The standardized total score from responses to two stability questions using a Cantril ladder. “ How secure [do you feel / think you will feel] [at present / ﬁve years from now] ” Physiological Index An inverse-covariance weighted average of PHQ, Stress, Life Satisfac- tion, Sociability (Total), Self-Worth, Locus of Control, and Stability indices. Gender Dynamics Gender Perceptions- Work The standardized total score of two questions regarding women ’ s work, “ How often would you agree that women should be allowed to work for a living [inside / outside] the block? ” 64 Usage context: supporting mention, primary mention, background mention.

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Input:
HIV behavioural surveillance surveys 153

Table III. HIV/AIDS knowledge, practices and attitudes questions and indicators (N �/31).

Number* Percent

Knowledge
Did the study include prevention questions, even if 26 83.9%
they did not include the standard questions below?

1) Sex with only 1 partner
Same or similar wording 21 67.7%
Disaggregated by gender and age 6 (N�/20) [�] 30.0%

2) Using condoms
Same or similar wording 26 83.9%
Disaggregated by gender and age 6 (N�/25) [�] 24.0%
Did study include misconception questions, even if 20 64.5%
they did not include standard questions below?

1) Mosquito bites
Same or similar wording 16 51.6%
Disaggregated by gender and age 3 (N�/15) [�] 20.0%

2) Sharing a meal
Same or similar wording 14 45.2%
Disaggregated by gender and age 5 (N�/13) [�] 38.4%

3) Healthy-looking person can have/transmit HIV
Same or similar wording 18 58.1%
Disaggregated by gender and age 4 (N�/17) [�] 23.5%

Practices
Did the study include practice questions, even if they 26 83.9%
did not include standard questions below?

1) Condom at last sex with a high risk partner
Same or similar wording 14 45.2%
Disaggregated by gender and age 5 (N�/14) 35.7%

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

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