Input:
The regional protection monitoring harmonization established a regional incident typology framework to efficiently
analyze the regional protection monitoring data. To this extent, 7,503 protection incidents with 106,673 victims were
reported in September 2022 in both countries, which affected 10 provinces in the Democratic Republic of Congo
(DRC) and 1 province in Mozambique. It is worth mentioning that of the protection incidents reported in September
2022, some occurred in the same month, and some occurred before September 2022.

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

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Input: 1. Introduction Sub-Saharan Africa is the youngest region in the world, and the world ’ s fastest-growing. Between 2010 and 2025, the number of people between 15 and 24 will grow to 250 million – a net increase of nearly 50 percent. Over the next decade, roughly one million young people will enter the labor market each month in Sub-Saharan Africa. However, these young people often enter the labor market too early and unprepared. Although access to education is growing, illiteracy remains high and schooling low: among the 32 Sub-Saharan African countries in the Barro-Lee (2010) data set, nearly 40 percent of women aged 15 and above have received no education at all; and the most recent (2007-2011) statistics in the World Bank ’ s Edstats data reveal that female literacy is less than 60 percent, on average. 1 This lack of preparedness contributes to a growing problem of youth unemployment. Quantifying the level of unemployment is bedeviled by lack of data and measurement issues. Household and labor force surveys throughout Africa usually record unemployment rates of less than 10 percent, 2 but those figures belie the extent of underemployment and vulnerability. Those same surveys indicate that the vast majority of working adults have insecure work in the informal sector, on the family farm, or in less- productive or unremunerated labor. Usage context: supporting mention, background mention, primary mention.

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Input:
From 1997-98, 274 households, randomly selected from 10 purposively sampled villages, [2] were surveyed in each of four periods, including the 1997 post-harvest and the subsequent 1998 hunger season.

availability. Women in these households were asked to recollect the quantities of

different foods consumed in the previous seven days. These data were converted into

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daily per capita caloric availability using household size and locally adapted tables that

convert physical units of food into calories. Were data available, however, the measure

The incidence and depth of current caloric shortfall can be directly calculated

from the survey data collected in November 1997. We take 2,345 kcal/person/day as

caloric threshold which corresponds to the needs of a 60 kg male, aged 30-59,

Government of Mali and the USAID sponsored [Famine Early Warning System for Mali]

use it as a leading indicator of food insecurity. Since [the availability of food is necessary]

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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: supporting mention, background mention, primary mention.

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Input: While camps have been recognized as posing serious challenges (Jacobsen and Crisp 1998), it is quite striking to observe that this organizational feature is not as spread in other regions of the world as in SSA. At best, only 28, 25 and 15 percent refugees are hosted in planned / managed camps in Asia, Americas, and the MENA region, respectively. Such figures are based on the most recent year available (2013) and may change significantly following the large inflows of Syrian refugees into Egypt, Lebanon, Iraq, Jordan and Turkey. Nonetheless, the differences are sufficiently striking to believe that this is a distinct feature of refugee hosting in SSA. 2 UNHCR defines a protracted refugee situation as “ one in which 25, 000 or more refugees of the same nationality have been in exile for five years or longer in a given asylum country ” (2012: 23). 3 The figures are based on refugees (including those in refugee ‐ like situation). Persons in refugee ‐ like situations include “ groups of persons who are outside their country or territory of origin and who face protection risks similar to refugees but for whom refugee status has, for practical or other reasons, not been ascertained ” (UNHCR 2014: 39). The number of refugees and people in refugee ‐ like situation for which demographic data is available does not necessarily equal the total number of refugees. However, for SSA, there is little difference between the two. We also restrict the number of refugees to those whose accommodation is known by the UNHCR (approximately 19 % in the world and 8 % for SSA). Usage context: supporting mention, primary mention, background mention.

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Input: refugees in Addis Ababa residing in rented houses. Most Eritrean refugee households (61 percent) live in temporary30 shelters provided by the UN or NGOs, whereas 50 percent of Somali refugee households and 71 percent of South Sudanese refugee households live in UN or NGO-provided permanent31 shelters. In Addis Ababa, 97 percent of refugee households live in rented houses. SESRE data also show that OCP refugees pay higher rents than hosts; on average, refugees pay roughly ETB 31,600 per year per adult equivalent, while hosts pay slightly less than half of that (ETB 18,700) (Annex D, Figure D.14). Refugees do not qualify for government 29 At least having difficulty with seeing, hearing, walking, remembering, selfcare or communicating. 30 Temporary shelters have walls mainly made of tent, plastic cover, and irons sheet. 31 Permanent shelters have walls mainly made of wood, mud, non-plastered blocks. 0 5 10 15 20 25 30 35 40 In camp Addis Ababa Total In camp Addis Ababa Total In camp Addis Ababa Total Stunted Underweight Wasted Hosts Refugees Percent Figure 2.18: Child nutritional indicators Source: World Bank Staff based on SESRE 2023. 0 1 2 3 4 5 6 Hosts Refugees Hosts Refugees Hosts Refugees In camp

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Input:
Survey (UNHS) and the 2009/10 Uganda National Panel Survey (UNPS), both implemented

The 2005/06 UNHS covered all the districts in Uganda surveying 7,421 households

from 783 Enumeration Areas. The 2009/10 UNPS collected information on 2,975 households

2009/10 Uganda National Panel Survey (UNPS)

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Input: 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: / / econ. worldbank. org. The author may be contacted at asacks @ worldbank. org. and managing these resources. The author assesses these competing hypotheses using multi-level analyses of Afrobarometer survey data. The sample, drawn from a continuum of developing societies in Africa, allows for analysis of associations between donor and non-state actor service provision and the sense of obligation to comply with the tax authorities, the police and courts. The findings yield support for the hypothesis that the provision of services by donors and non-state actors is strengthening, rather than undermining, the relationship between citizens and the state. Usage context: background mention, supporting mention, primary mention.

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

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Input: These calculations conﬁrm our earlier assessment. 5 Conclusion Combining data from a household survey and an 11 % census of the population, we have estimated destination choice regressions for Nepalese internal migrants. Results show that population density, social proximity, and access to amenities exert a strong inﬂuence on migrants ’ choice of destination. These results conﬁrm earlier work on the factors aﬀecting the subjective welfare cost of isolation (Fafchamps and Shilpi, 2008). 29 Usage context: primary mention, supporting mention, background mention.

household survey
11 % census of the population

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Input:
(2022b) to supplement the World Bank BOS database.

The database was built using data from ORBIS and complemented with data from government sources, such as business registries, central depositories, central oversight bodies, and the Ministry of Finance.

EC (European Commission). 2015. "Macroeconomic imbalances Country Report - Romania 2015,"
Occasional Papers 223. Directorate-General for Economic and Financial Affairs,

Using 1995, 2004, and 2008 data from the Chinese Industrial Census, Brandt, Kambourov, and Storesletten (2020) indicate that a key factor underlying the dispersion and dynamics of aggregate total factor productivity and wages across Chinese prefectures were entry barriers, which in turn were linked to significant state presence in economic activities.

World Bank BOS database
Chinese Industrial Census

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Input: Significant among these are: (a) the lack of capacity of national statistical agencies in many developing countries to collect robust data on refugees; (b) weak or incomplete monitoring of refugees dispersed within host communities; (c) lack of capacity to maintain up to date information on refugees (reflecting new arrivals, 81 General population registers may also provide opportunities for more elaborate analysis of the integration of refugees in asylum countries, as the data could be linked to other administrative registers, for example on labor and education (UNSD 2014). 82 UNHCR collects, compiles and publishes data on asylum-seekers, refugees and IDPs protected or assisted by UNHCR, including populations in refugee-like or IDP-like situations. 83 Established in 1863, the ICRC ’ s mission is to ensure humanitarian protection and assistance for victims of armed conflict and other situations of violence.

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Input: As in previous sections we follow Henderson et al. (2012) who argue that the relationship between GDP and night light at the country level can be expressed fairly well in a constant elasticity model in which an increase of night light by 1 percent implies an increase of GDP of about 0. 25 percent. Hodler and Raschky (2014) also look at the relationship between log nighttime light intensity and log GDP at the regional level using the panel data of regional GDP per capita assembled by Gennaioli et al. (2013) 48 and they conﬁrm that the relationship is linear and also ﬁnd an elasticity of around 0. 3. Access to political power is ranked on a scale from 1 to 7 in the GROWup dataset. Ethnic groups are"powerful"(monopoly of power or dominant group in power), have access to central power through a formal system of power sharing (as"Senior"or"Ju- nior"partner) or are “ excluded ” from power (self excluded, powerless or discriminated). Strong executive constraint is measured as a dummy indicating whether or not we have executive parity or subordination of the executive at the country level, a value 7 for “ xconst ” variable in Polity IV dataset. Usage context: supporting mention, primary mention, background mention.

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Input: 27 Source: Listening to Displaced People Survey, 2014. 7. Conclusion The 2012 crisis in northern Mali led to widespread displacement. The welfare of the displaced – and those who returned – is monitored by combining a baseline survey with structured monthly follow-up interviews carried out by mobile phone. This innovative approach allows tracking changes in welfare with high frequency – even for those who returned to areas that are insecure and inaccessible to enumerators. After 6 rounds of follow-up interviews attrition rates are very low (more than 99 % response rate), demonstrating that it is possible to collect robust and representative data from hard-to-reach, conflict-affected populations. The results show that those who fled were better educated, better off and less affected by violence than the average population in the North. Those who fled lost significant amounts of durable goods (20-60 %) and livestock (50-90 %); many of their children ended up being taken out of school and their welfare (measured subjectively and by the number of meals consumed) declined considerably. Over time, the impact of the crisis on welfare has lessened and by February 2015 the majority of eligible children of the displaced were going to school and levels of employment and number of meals consumed were at pre-crisis levels. Usage context: primary mention, background mention, supporting mention.

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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).

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

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Input: a pre-sampling assessment by visiting the camps to verify on-the-ground conditions. 56 Refugees from Sudan were not included in SESRE as, at the time of sampling, there were less than 50,000 Sudanese refugees in Ethiopia and inclusion was not deemed cost effective. Annexes 93 households in a row from the list; that is, 50-200 HHs grouped as EA1 and the next 150-200 households grouped as EA2, and so on. EAs and households from each sampled EAs were selected. (b) Refugees in Addis Ababa We used a slightly different approach for refugees in Addis Ababa because of the difficulty of obtaining a reliable, complete list of locations for refugees living there. The refugee sampling frame in Addis was based on UNHCR’s proGRES registration data, sorted by location. The UNHCR list has information about how many refugee households live in each Woreda in Addis Ababa, their contact details, location, and other information. We developed pseudo-EAs from the list by location (sub-city and Woreda); some EAs covered more than one Woreda, and multiple EAs were in a single Woreda. We selected a sample of EAs and households from each EAs in collaboration with UNHCR. Finding refugees in Addis Ababa was challenging, as they

proGRES registration data
UNHCR’s proGRES registration data

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Input: 11 however, since they cannot distinguish between a country where the population is concentrated in one cluster covering 10 % of the territory and one where the population is concentrated in two clusters of 5 % each, but with a considerable geographical distance between them. Population and conflict geography in the Democratic Republic of Congo (DRC) corresponds to these arguments regarding population concentration and dispersion. Concentrations of language-based minorities are evident throughout eastern DRC. Due to the limited access of the government, the close proximity to international borders, and the dense population concentrations, these concentrated minorities have a higher potential of conflict than other, more accessible, sparsely populated areas of DRC. Figure 1 shows the population concentrations in 1990 (CIESIN data) for Central Africa. Heavily populated areas are shaded in deeper tones of red / grey. Civil conflict in DRC has overwhelmingly occurred in the eastern portion of the state, which is the most densely populated area and also geographically peripheral to the capital, Kinshasa. Of the eleven Congolese rebel groups accounted for in the dataset used in this paper, all have operated either exclusively or partially in the eastern and southern areas of DRC.

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Input: appear to be a relationship between perceptions of the helpfulness of donors and non-state actors and the willingness to defer to the police and to the courts. Individuals who believe that donors and non-state actors exert too much, rather than, too little inﬂuence over one ’ s government is associated with the willingness to defer to the court and to the police. Findings also suggest that citizens who believe non-state actors are responsible for provid- ing law and order are less likely to be willing to defer to the police and to the courts than respondents who believe the state is responsible for providing law and order. 7. 4 Conclusion This paper demonstrates that the logic of the ﬁscal contract is relevant to a wide variety of contemporary African states. Findings from a cross-national analysis of survey data from Africa link citizens ’ legitimating beliefs — in- dicated by a willingness to defer to the tax department, the police and the courts — to a government ’ s fulﬁllment of a ﬁscal contract. Citizens who are satisﬁed with their government ’ s provision of services and goods are more likely to be willing to defer to the tax department, courts and police than citizens who disapprove of government service provision. Usage context: primary mention, background mention, supporting mention.

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Input: Medium ‐ intensity, on the other hand refers to “ regular armed clashes between governments, government forces and insurgents. ” (IISS 2017) Within the first category, according to the Armed Conflict Survey in 2016 are Afghanistan, Syria, Somalia, South Sudan, and Iraq, while Myanmar, Central African Republic, Democratic Republic of the Congo, and Sudan are in medium ‐ intensity conflict. (Eritrea is not included in the Armed Conflict Survey in 2017, discussed in Annex). Minorities in Albania, Kosovo and Serbia are often the objects of discrimination but countries are not in conflict. A capsule summary of the security and social situation in each of the other countries included in this survey can be found in Annex 2. The survey illustrates how impractical return is today in the countries in conflict, such as Syria, Afghanistan, and Iraq, and voluntary return in large 36 Best practice and new methods in return policy, July 2017, http: / / www. bamf. de / SharedDocs / Meldungen / EN / 2017 / EMN / 20170504 ‐ emnjahrestagung ‐ rueckkehr. html

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Input: The model includes ϐixed effects for grade, school, and language spoken. 14 The results are presented in Table 3. We then narrow our focus to foreign students who joined Italian schools after February 2022, speciϐically comparing Ukrainian refugees to other newly arrived foreign students. This approach allows us to examine how Ukrainian refugees compare to other foreign students who entered the education system around the same time. By restricting the sample to these two categories of students, we estimate the following regression: 𝑌𝑌𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖 = 𝛽𝛽0 𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑢𝑒𝑒𝑖𝑖 + 𝐸𝐸𝐸𝐸𝐸𝐸𝑆𝑆𝑖𝑖 + 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑟𝑟𝑖𝑖 + 𝑓𝑓𝑔𝑔 + 𝑓𝑓𝑠𝑠 + 𝑓𝑓𝑙𝑙 + 𝜖𝜖𝑖𝑖𝑖𝑖𝑖𝑖 (2), with variables as deϐined in (1), and results presented in Table 4. Our analysis also aims to explore potential mechanisms that could explain results derived from equations (1) and (2). Using the administrative data, we investigate whether being placed in a smaller class inϐluences school achievement in the sample of Ukrainian refugees. The results are presented in Table 5. We then draw on ϐindings from the survey data to unpack and analyze how Ukrainian refugees feel in Italy, the challenges they face, and their aspirations. 4. Results 4. 1. Integration challenges faced by Ukrainian refugees in Italy Low enrollment and substantial dropout rates At the end of the 2021-2022 school year, the enrollment rate of Ukrainian refugee children in Italian schools was low. In the months following Russia ’ s full-scale invasion of Ukraine in 2022, 3, 320 Ukrainian refugees were enrolled into Italian secondary schools. This ϐigure constitutes 24 % of the 14, 106 Ukrainian refugees aged between 11 and 18 years who sought temporary protection as of 14 This variable is included to account for the potentially greater ease of learning experienced by students who speak languages that are considered closer to Italian.

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Input: likelihood of return. Moreover, the sensitivity of this return decision to conditions in Syria (i. e., conﬂict intensity) is also markedly diﬀerent along such characteristics. 4. 3 Conditions in Host Countries A refugee ’ s livelihood opportunities and housing conditions in the host country may also be important determinants of her return decision. In fact, this point often appears in the popular media in diﬀerent forms like"good conditions make refugees stay"and, by extension,"bad conditions make refugees return". 19 In this section, we show that our results do not necessarily support this view. First, we explore how individual return decisions are aﬀected by living conditions in the host countries by estimating equation 4. These results are reported in Table 8, where individual controls from ProGres are suppressed for ease of exposition. In column (1), we ﬁnd that more food secure households have a higher hazard rate of return, a result that is highly signiﬁcant. However, the magnitude of the eﬀect is small: a one standard deviation increase in the food security PCA index increasing the hazard rate by 0. 27 %. Moreover, Column (2) shows that better housing conditions- proxied for by the housing PCA index- also increase the hazard rate by a similar magnitude. Usage context: supporting mention, background mention, primary mention.

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

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Input: (0.04) (0.24) HH operates a nonfarm enterprise 0.07** -0.00 -0.05 0.26*** (0.03) (0.03) (0.10) (0.07) Share of employed members 0.35*** 0.57*** 0.14** 0.06 (0.08) (0.06) (0.06) (0.08) Health shock 0.07 -0.02 -0.04 -0.20 (0.06) (0.06) (0.10) (0.18) Market shock -0.01 -0.09*** -0.04 -0.19*** (0.02) (0.03) (0.04) (0.05) Employment shock 0.01 -0.11 -0.06 -0.07 (0.07) (0.11) (0.31) (0.18) Drought shock -0.03 0.08 0.24 (0.05) (0.09) (0.32) Political shock -0.05 -0.23* -0.23** -0.06 (0.05) (0.12) (0.11) (0.38) Constant 10.05*** 10.22*** 10.58*** 10.49*** (0.07) (0.09) (0.32) (0.36) Survey domain Yes Yes Yes Yes Survey time Yes Yes Yes Yes Observations 1286 1287 432 430 Source: World Bank Staff based on SESRE 2023. Note: Dependent variable is the log of total per adult equivalent consumption expenditure. All regressions include fixed effects for the survey domain and time (year

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Input: Yes Survey time Yes Yes Yes Yes Observations 1286 1287 432 430 Source: World Bank Staff based on SESRE 2023. Note: Dependent variable is the log of total per adult equivalent consumption expenditure. All regressions include fixed effects for the survey domain and time (year and month) to account for locational and temporal differences. Standard errors in parentheses; * p < 0.10, ** p < 0.05, *** p < 0.01 Annexes 114 The regression specification used is: where is the vector of control variables that include demographic characteristics (sex of household head, age of household head, family size, years of schooling completed by the head), assets and wealth (mobile phone ownership,

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Input: 24% 64% 30% 37% 10% 8% Source of lighting Electricity (meter) 74% 13% 25% 5% 29% 1% Electricity (meter, generator, solar) 89% 91% 38% 17% 34% 4% Source: World Bank Staff based on SESRE 2023. Annexes 100 0 10 20 30 40 50 60 70 80 90 100 < 15 15 to 24 25 to 44 45 to 64 >= 65 < 15 15 to 24 25 to 44 45 to 64 >= 65 < 15 15 to 24 25 to 44 45 to 64 >= 65 < 15 15 to 24 25 to 44 45 to 64 >= 65 Eritrean Somali South Sudanese Addis Ababa Male Female Percent Figure D.1: Age group by gender Source: World Bank Staff based on SESRE 2023. 0 20 40 60 80 100 Hosts Refugees Hosts Refugees Hosts Refugees Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese In camp Addis Ababa Total Average share of primary school age children in primary education Average share of secondary school age children in secondary education Percent Figure D.3: Share of school-age children in education per household Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 Eritrean Somali South

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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 11055 The paper examines the early integration of Ukrainian refugee students into Italy ’ s education system following the Russia ’ s invasion of Ukraine in 2022. Using administrative and survey data, the study presents enrollment trends, academic performance, and barriers to educational integration. Findings from the analysis indicate that Ukrainian refugees face lower enrollment rates, higher absenteeism, and lower test scores than other students, particularly in subjects requiring language proficiency. Despite these challenges, teachers often recommend Ukrainian refugee students for advanced educational tracks, thus revealing their optimism about the potential of these students.

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Input: the optimal travel time between Woredas using the transport network of 2020. The trade elasticity, has a value of 8.28 (Eaton and Kortum, 2002). Box 6.1: Measurement of proximity and market access index in Ethiopia 37 43 19 To Woreda City 1-10km 10-20km >20km 1-20km 20-100km >100km 1-30km 30-50km >50km 45 26 29 To Zone capital 18 59 23 To nearest border 44 28 11 17 Proximity to economic hub Nearest to Zone Nearest to Woreda but not Zone Nearest to border but not Zone & Woreda Remote 24 40 36 Market accessibility High accessibility Medium accessibility Low accessibility Figure 6.1: Refugee incidence Source: World Bank Staff based on SESRE 2023. Note: High, medium, and low accessibility refers to the level of market access, with >0, [-0.5, 0], and <-0.5 standard deviations from the average, respectively. a. Against distance to cities and borders b. By market accessibility, proximity to resource hub Markets and Opportunities 59 Labor market outcomes47 differ by proximity to resource hubs and connectivity. The labor force participation rate for refugees is highest in remote locations and areas with poor connectivity (Figure 6.2). Yet, most refugees in the labor force in remote and low-connected locations are unemployed, highlighting

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Input: The 10-item parenting stress scale used in this sample was found to have a high internal-consistency reliability, with a Cronbach ’ s alpha of. 85 in this sample. Independent (Stressor and Other Covariate) Variables A variety of known stressors and correlates of maternal mental health and child development were also assessed. Stressors, including food insecurity, poverty, flooding impact, experiences of domestic violence, felling unsafe in one ’ s community, discrimination, living in a rural area, lack of enrollment in ECE, and low maternal educational attainment have consistently been associated with lower levels of maternal mental health conditions and child development across contexts (e. g., Hentschel et al., 2023; Iqbal & Ali, 2021; Reed et al., 2012: Sitwat et al., 2015; Yousuf et al., 2023) Other covariates, such as refugee status and child age, were also assessed. Refugee Status. At the time of the survey, sensitivities around “ refugee status ” were particularly heightened. As such enumerators were asked to keep notes on interviews to help identify whether Usage context: supporting mention, primary mention, background mention.

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Input: The countries that are the largest source of refugees include: Afghanistan, Syria, Somalia, South Sudan, Sudan, Democratic Republic of Congo, Central African Republic, Iraq, Myanmar, and Eritrea (UNHCR, 2017). These countries account for the vast majority of refugees worldwide. We will also consider three countries in Europe that are an important source of asylum seekers in Europe, and whose recognition rate is low, and account for many returnees – these are Kosovo, Serbia and Albania. Is return possible and safe, and if so, does the economic situation bode well to provide essentials, namely a job, housing, education and reliable public services? It is helpful to identify three groups of countries: ones that are still mired in war and / or high ‐ intensity civil conflicts, countries where medium ‐ intensity conflict persist and are already in the process of rebuilding, and countries which are not in conflict. According to the Armed Conflict Survey (IISS 2017), high ‐ intensity conflict is defined by frequent (daily) armed clashes between governments, government forces and insurgents, or among non ‐ state armed groups that control territory.

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Input:
returns to human capital. Then, we find that relative _pcGDP_ is 53 _._ 5 percent, accounting

48See Web Appx. Fig. 8(a) for the mortality distributions.
49See Web Appx. Fig. 8(b) for the distribution of schooling we use, based on the I2D2 data (1990-2016).
50We compare GDP per capita in levels. An alternative approach would be to compare GDP per capita
in log levels. In that case, the gap is of 51%. In any case, the main point of our inquiry in this section is to
compare the relative contribution of education and experience, so the absolute metric is not important.

According to I2D2 data, workers in developed economies work   43 hours per week on average compared to 50 in developing economies. Assuming three   weeks of time off, we get that workers in developed economies on average train for 3 _._ 4%   of their working time, compared to 2 _._ 0% in developing economies.

To see whether the differences in the experience premium might be accounted for   by differences in hours spent training, we draw on recent data from _OECD.Stat_ (OECD,   2021). The data contain information on 33 developed economies and 4 developing   economies.

[2 Global SDG Indicators Database, accessed April 26, 2022: https://unstats.un.org/sdgs/indicators/database/](https://unstats.un.org/sdgs/indicators/database/)

Using data from the Armenia Land Tenure and Area (ALTA) study and in the context of land tenure rights, this paper addresses questions on: (i) the data quality implications associated with respondent strategy; (ii) the data quality implications associated with level of data collection; (iii) the interaction of biases stemming from the use of proxy respondents and aggregated level data collection, as relevant; and ultimately, (iv) the implications of these design decisions on the computation and monitoring of SDGs

Armenia Land Tenure and Area (ALTA) study

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Input: implications associated with level of data collection; (iii) the interaction of biases stemming from the use of proxy respondents and aggregated level data collection, as relevant; and ultimately, (iv) the implications of these design decisions on the computation and monitoring of SDGs 1.4.2 and 5.a.1.

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Input: The magnitudes are similar as we saw with the overall conﬂict index. A one standard deviation decline in quarterly casualties, which is about 90, is associated with a 2 % higher return rate. The use of chemical weapons and incidents of skirmishes and ﬁghting all have a signiﬁcant negative eﬀect on returns to Syria. In results not shown, we ﬁnd less robust relationships between the number of air strikes and incidents of artillery and carpet bombing and refugees ’ decision to return. 4. 1. 1 Vignette Analysis We complement the study of returns that have already happened with data from hy- pothetical vignettes. There are advantages and disadvantages of both of these data sources. The returns observed to date are still a very small percentage of the overall refugee population, and therefore the factors aﬀecting their return decision may not be representative of the larger Syrian refugee population. The hypothetical vignettes, while clearly weaker in that they represent hypothetical scenarios, seek to provide in- sights into the external validity of the earlier results. Usage context: background mention, primary mention, supporting mention.

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Input: There is a clear increase in the entry of new foreign ﬁrms which may be driven by refugees ’ enterpreneurship. Cheaper low-skilled labor may have helped all businesses cutting costs. Balkan and Tumen (2016) had also found a decline in prices and attribute their ﬁnding to lower labor costs, which may also be one of the mechanisms driving our results. Gross proﬁts and sales also appear to have gone up, which would be consistent with an increase in demand. As noted by Maystadt and Verwimp (2014), heterogeneous eﬀects on speciﬁc subgroups of the native population should be expected from refugee crises. In case of the Syrian refugee crisis in Turkey, the business activity in hosting region appears to have beneﬁted. For a complete picture of the eﬀects of the Syrian refugee crisis on local economies in Turkey, further research will be needed on market activity, health and longer term eﬀects. More speciﬁcally for the line of research this study focused on, further analysis using micro-level ﬁrm data would be needed to understand how ﬁrms adjust their activity, 24 Usage context: supporting mention, background mention, primary mention.

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Input: We exploit the LFS, which does not collect consumption data and has a different design from the HEIS, to fill the missing poverty data problem in Jordan for the years the HEIS is absent. We validate our imputation-based estimates of poverty against those obtained from the actual consumption data (or design-based estimates) for the two years 2008 and 2010 when consumption data are available, before imputing estimates for other years when consumption 4 See, for example, King et al. (2001) and Honaker and King (2010) for examples of adaptation of multiple imputation methods in the field of political science. 6 Usage context: primary mention, supporting mention, background mention.

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Input: to severe based on the score. Moreover, depression is screened with the Patient Health Questionnaire, a 9-item tool administered directly to adolescents. These instruments collectively gauge a broad spectrum of psychological and emotional states, including post-traumatic stress, emotional disturbances, behavioral issues, inat- tention, peer relationships, prosocial behavior, anxiety, and depression, offering a com- prehensive view of the mental health and socioemotional development of the minors in our study. Figures B. 3 and B. 4 depict the distribution of the raw scores for Venezuelan and Colom- bian minors for each of the four scales. Surprinsingly, we do not observe any stinking differences on the distribution of any of these scores across groups. We are also not able to distinguish statistical differences between Colombian and Venezuelan children in any of the scales, when we estimate the specification highlighted in equation (1) as illustrated in Table 7. This is an unexpected result considering that typically, forcibly displaced pop- ulations have a high prevalence of socioemotional and mental health issues, but might be related to the fact that Venezuelan migrants have not faced war (as many forced migrants have in other contexts) directly and as such, these issues are less prevalent. Usage context: supporting mention, background mention, primary mention.

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Input: In all speciﬁcations, conﬂict incidence correlates nega- tively with country-level economic performance. The estimated coeﬃcients of conﬂict incidence are statistically signiﬁcant and negative. We also ﬁnd that the coeﬃcients 7For a discussion see Henderson et al. (2012). In order to calculate light per capita we use popu- lation data that is provided by a World Bank dataset. 8The standard reference here is Miguel et al. (2004). Ciccone (2011) shows that high rainfall levels three years earlier seem to be best predictors of conﬂict in the reduced form. Miguel and Satyanath (2011) argue that lagged negative growth shocks are a predictor of conﬂict onset. In any case, there is no evidence from this literature that contemporaneous growth declines cause conﬂict. Bazzi and Blattman (2014) corroborate the view that the relationship between income shocks and conﬂict is not straightforward. They do not ﬁnd evidence of an eﬀect of price shocks on conﬂict onset and only weak evidence on incidence. 9Results from this are presented in the Appendix. 10We take the threshold from Mueller (2016) who shows that a threshold like this leads to a similar number of coded civil wars as the threshold of 1000 battle-related deaths often used in the conﬂict literature. In the context here, this is a conservative approach as it is not the threshold which yields the biggest diﬀerence between conﬂict and non-conﬂict countries. 10 Usage context: primary mention, background mention, supporting mention.

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Input: The vulnerability of the Internally Displaced People in SSA has certainly been overlooked for too long, but the increased support provided by UNHCR is an encouraging but challenging sign in that respect. Figure 3. Refugees and Internally Displaced People in SSA, 2003 ‐ 2013 Source: 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). The annual number of IDPs is collected from the IDMC (2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2012, 2013, 2014) annual reviews. Usage context: supporting mention, primary mention, background mention.

UNHCR statistical population online dataset

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Input:
and hourly wages. For this objective, we merge upper secondary ENLACE test scores

limitations, large-scale standardized tests like ENLACE capture skills that are important

una comparación entre ENLACE, Excale y Pisa," 2014. Nexos.

_Promise_, Washington, DC: World Bank, 2018.

28

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#### **Tables**

Table 1: ENLACE Panel       - Means and Standard Deviations

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Input: -0.0232 -0.0248 (0.0246) (0.0258) (0.0269) HH access electricity -0.0637 -0.0571 -0.1051+ (0.0489) (0.0499) (0.0559) Proximity and market access Level two -0.3000*** (0.0713) Level three -0.3988*** (0.0821) Level four -0.4862*** (0.0832) Distance to Zone city (Km) -0.002* (0.0008) Market accessibility indicator 0.0897** (0.0307) Observations 787 782 787 Chi-square test 0.0000 0.0000 0.0000 R2 0.2871 0.2738 0.2538 Source: World Bank Staff based on SESRE 2023. Standard errors in parentheses. All estimates are controlled for regions. +p<0.10, * p<0.05, ** p<0.01, *** p<0.001 Annexes 121 Results on Social Cohesion Table D.18: Regression analysis of host and refugee attitudes (1) (2) (3) Hosts: Attitudes Index Hosts: Trusts Refugees Refugees: Trusts Hosts Male -0.021 -0.025 -0.029 (0.060) (0.036) (0.039) Age 0.004 0.003 -0.003 (0.009) (0.005) (0.006) Age Sq. -0.000 -0.000 0.000 (0.000) (0.000) (0.000) Educ: Primary incomplete - - - Educ: Completed primary -0.094 -0.040 -0.009 (0.066) (0.050) (0.052) Educ: Completed secondary -0.003 0.033 -0.083 (0

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Input: - - Educ: Completed primary -0.094 -0.040 -0.009 (0.066) (0.050) (0.052) Educ: Completed secondary -0.003 0.033 -0.083 (0.098) (0.055) (0.066) Educ: Completed post-sec. -0.074 -0.073 -0.055 (0.103) (0.050) (0.106) Agrees on improved local services 0.408*** 0.116** (0.103) (0.055) Years in Ethiopia 0.002 (0.005) Agrees hosts culturally similar 0.215*** (0.055) Region Fixed Effects Yes Yes Yes N 1724 1666 1613 Source: World Bank Staff based on SESRE 2023.

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Input: The vulnerability of the Internally Displaced People in SSA has certainly been overlooked for too long, but the increased support provided by UNHCR is an encouraging but challenging sign in that respect. Figure 3. Refugees and Internally Displaced People in SSA, 2003 ‐ 2013 Source: 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). The annual number of IDPs is collected from the IDMC (2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2012, 2013, 2014) annual reviews.

UNHCR statistical population online dataset

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

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Input: These findings were also echoed in the context of other developing countries such as India (Allard et al., 2022) and Zimbabwe (Mabugu, Maisonnave, Henseler, Chitiga-Mabugu, & Makochekanwa, 2023). In the MENA economies ’ context, the evidence is considerably sparcer. Early work on the impact of the COVID-19 pandemic on labor markets in the MENA region re- lied on high-frequency phone surveys and highlight important job losses among wage workers and an uneven impact across industries (Krafft, Assaad, & Marouani, 2021, 2022). Providing evidence from Labor Force Surveys in the Islamic Republic of Iran, Dang and Salehi-Isfahani (2023) find that the pandemic exacerbated the pre-existing low participation of females in the labor force. Wahby and Assaad (2023), on the other hand, focus on the impact of the pandemic on Syrian refugees in Jordan and find a divergence in job finding and separation rates of Syrian refugees relative to their Jorda- nian hosts after the onset of the pandemic. Focusing on cross-border commuters in the West Bank and Gaza, Adnan and Etkes (2022) find that undocumented commuters benefited relative to their documented peers after the pandemic, as Israeli policies inadvertently created incentives for employers to favor the former. This sharply con- trasts the results by Borjas and Cassidy (2020) on the impact of the pandemic on immigrants in the United States. The rest of this paper is organized as follows. Section 2 provides background information on labor markets in the West Bank and Gaza, as well as background in- formation on the COVID-19 pandemic and government responses. Section 3 describes the data. Section 4 discusses our methodology. Section 5 presents the main regression results and investigates heterogeneous effects. Section 6 provides robustness checks. Finally, we provide concluding remarks in Section 7. 4 Usage context: background mention, primary mention, supporting mention.

Labor Force Surveys
high-frequency phone surveys

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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: background mention, primary mention, supporting mention.

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Input: The long-term consequences of these trends are signiϐicant, as diminished educational outcomes and social isolation can hinder successful integration into host communities. Conversely, sustained social and educational integration efforts are vital for positive outcomes. For instance, studies indicate that long-term integration can be hampered by social, economic, and institutional barriers (Chiswick and Miller, 2014), while interventions focused on language support and community engagement can lower these barriers (Ozden and Wagner, 2020). Further, speciϐic interventions aimed at removing obstacles to education for children on the move can contribute signiϐicantly to better integration outcomes (Schuettler and Caron, 2020). This paper beneϐits from key information coming from administrative data on educational records of Ukrainian refugees in Italy for the academic years 2021-2022 to 2023-2024 for grades 6 to 13. This provides a unique opportunity to examine enrollment, attendance, test performance, and other indicators of integration into the Italian educational system. Supplemented by survey data collected in 2023-2024, this study offers an overview of the challenges and opportunities faced by Ukrainian students in secondary schools and highlights areas for potential policy development. This study advances the literature by adding empirical evidence on the short- to medium-term educational impacts of displacement on young refugees within a European host country, offering insights into the role of education policy in mitigating human capital losses. It also contributes to discussions on human development by identifying factors that support or hinder integration, highlighting pathways for improving educational and social outcomes for refugee students. Results highlight that despite gradual improvements, enrollment rates remain signiϐicantly lower among refugees compared to native and other foreign students. Ukrainian refugees also demonstrate higher absenteeism and lower academic performance, particularly in subjects requiring language proϐiciency such as Italian and English. However, good performance in mathematics suggests potential strengths linked to their prior educational backgrounds. Despite these challenges, teachers seem to be more inclined to recommend Ukrainian refugees for high-track education compared to other newly arrived foreigners, indicating potential optimism about their academic capabilities. The Usage context: background mention, primary mention, supporting mention.

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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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