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: background mention, supporting mention, primary mention.

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Input:
When the stable lights data set is examined, most countries display positive growth in _AoL_ and negative
growth in _R_ . There is a weak negative relationship in levels (Figure 7) and a somewhat stronger negative
relationship in growth rates (Figure 8). This outcome is not surprising. For all but a handful of rapidly
growing countries, the periphery of an expanding _AoL_ is not as bright as the center. Thus, _R_ must fall
because _R_ = _SoL_ ÷ _AoL_ .

We use four independent variables. Data for GDP, non-agricultural GDP, and manufacturing value-added
are all measured in constant 2005 US dollars. These data come from the World Development Indicators
supplied by the World Bank. Data for electricity consumption in kilowatt-hours come from the
International Energy Agency via the World Development Indicators. Data for population come from the
UN Population Division, again via the World Development Indicators. Data for the value of the stock of
physical capital, denominated in constant 2005 US dollars, come from the Penn World Tables Version 8.0.

World Development Indicators
Penn World Tables Version 8.0

International Energy Agency via the World Development Indicators

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Input: cents. The universe of blocks (“ manzanas ”) was stratified by socioeconomic strata and a representative sample of blocks was selected at random without replacement. To en- sure a sample representative of Colombian children by age group, stratum, and sex, we followed a multi-stage random sampling process. 8 As mentioned earlier, one of the biggest constraints in characterizing the role of forced migration in children ’ s human development within developing countries is the difficulty of finding a representative sample of those migrants. This is specially true in contexts where migrants are not hosted in refugee camps, but are integrated in local communi- ties, which account for 80 % of refugees worldwide (Climate Center 2022). We address these difficulties, leveraging all available information on Venezuelan settlements across the country to construct the largest possible comprehensive listing. The listing included data on Venezuelan settlements from all available sources, such as the 2018 population census, migrant organizations, and settlements identified by iMMAP, a non-profit orga- nization. iMMAP uses multiple sources, including OIM, United Nations, local migrant organizations, and satellite images, to identify Venezuelan settlements geographically. 9 Hence, to create our sampling frame, our field team verified the geographic location of all the Venezuelan settlements in-person and implemented a snowball sampling procedure in all the settlements found. Usage context: supporting mention, primary mention, background mention.

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Input: Figure 2. Sample and Distribution of Venezuelans in Colombia Notes: The left-hand panel of the ﬁgure illustrates in shades the number of Venezuelans registered in the RAMV census; the red circles depict the surveys carried out per municipality. The right-hand panel illustrates the number of Venezuelans per municipality reported in the 2018 Colombian census, a proxy of the overall distribution of migrants in the country. The correlation between the sample and the 2018 Colombian census registry is 0. 93. 39 Usage context: supporting mention, primary mention, background mention.

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Input:
**Appendix C: Robustness to DHS Cluster Geocoding Uncertainty**

The standard DHS jitter algorithm displaces cluster centroids by up to 5 km (urban) or 10 km (rural). To assess sensitivity of our results to this measurement error, we implement a simulation in which each DHS cluster centroid is displaced 1,000 times by a random draw from the DHS jitter distribution, and the treatment indicator is recomputed after each displacement. We report the median coefficient and the 5th and 95th percentile bounds across simulations. The simulated bounds are narrow relative to the estimated confidence intervals, indicating that DHS cluster geocoding uncertainty does not substantially bias our estimates.

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Input: Sudan domain (.48 standard deviations below the mean). It is higher for female than male hosts in both domains, by .14 standard deviations from average in the Somali domain and .19 standard deviations in the South Sudan domain. The difference in attitudes between male and female hosts is not statistically significant, and inter-group attitudes vary little by age or education. We can study the characteristics associated with attitudes by putting this index into a regression 0 10 20 30 40 50 60 70 80 90 100 Hosts Refugees Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Addis Ababa All Hosts All Refugees Neither are trustworthy Only my group Only the other group Both are trustworthy Percent Figure 7.9: Are most Ethiopians/refugees in Ethiopia trustworthy? Source: World Bank Staff based on SESRE 2023. Note: Combines two questions regarding trust in Ethiopians and refugees, with identical wording to both Ethiopians and refugees. 2.3 2.4 2.5 2.6 2.7 2.8 2.9 3 3.1 Eritrean Somali South Sudanese Addis Ababa All Hosts Figure 7.10: Host attitudes Index Source: World Bank Staff based on SESRE 2023. Note: This index is an average of ten questions regarding beliefs about refugees’ character, the rights they should

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Input:
REGIONAL BUREAU FOR SOUTHERN AFRICA

**DEMOCRATIC REPUBLIC OF THE CONGO REFUGEES SITUATION**

As of 3 0 September 2022

**Author: UNHCR DIMA - RSA** Contact : rsarbdima@unhcr.org **Source:** UNHCR Primes, Government, UNHCR

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Input: 5.4 Dependency ratio 1.1 1.5 0.5 0.4 0.7 1.3 Female-headed 44% 73% 45% 58% 44% 69% Head’s age 42.3 39.6 42.0 30.9 42.1 37.6 Source: World Bank Staff based on SESRE 2023. Sociodemographic Profile 12 2.2 Education Integrating refugee children into educational programs soon after arrival14 avoids the loss of valuable years of education and human capital accumulation that can hinder future prospects. Integrating refugees into national education systems can improve future outcomes for refugee children and their hosts (UNHCR, 2020; Piper et al., 2020; Abu-Ghaida and Silva, 2020; Crawford et al., 2015; Bilgili et al., 2019). Investment in human capital development can enable refugees to contribute to local economies to benefit refugees and hosts alike, and it can contribute to the recovery of countries of origin and the hosting communities. Despite the positive externalities of integrating refugees into public-school systems, a large influx of refugee children can exacerbate existing inefficiencies. Where there are large inflows, the national education system might require additional human and financial resources to integrate newly arrived children. Increasing the supply and improving the quality of schools in affected areas, supported by external assistance and financing, can avoid tension between refugees and host community populations over

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

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Input: 14 4. 1 Variation across Districts Pakistan is divided administratively into four provinces with 102 districts — Punjab, Balochistan, North-West Frontier Provinces (NWFP), and Sindh — plus the federal capital Islamabad, the Federally Administered Tribal Areas (FATA), the federally administered Northern Areas and Azad Jammu and Kashmir (AJK). The four provinces or Punjab, Balochistan, Sindh and NWFP, together with Islamabad, account for more than 97 percent of the population. Geographically, parts of Balochistan, the NWFP and FATA border Afghanistan. Sindh and Balochistan are sparsely populated provinces, with the exception of Karachi in Sindh, which is the single biggest metropolis in the country with a population approaching 10 million. We use data from the population census, 1998, as well as the census of private schooling, 2000, to provide estimates of madrassa, private, and government school enrollment in each district except for those in the province of FATA. The geographical dispersion of madrassa enrollment depends on how we define madrassa prevalence. There are three alternatives. We could present a geographical breakdown of the total number of children enrolled in madrassas. This number is related to the total population of the district, and may thus reflect only the size of the district relative to others. Usage context: supporting mention, background mention, primary mention.

population census
census of private schooling, 2000

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Input:
However, it also highlights the APC’s limited capacity to collect protection data and build up a more
robust and comprehensive protection analysis. The main challenges have been identified as limited
humanitarian access, sensitivity related to some protection thematic, a lack of information sharing
among different agencies, limited capacity and knowledge to operationalize the protection risks
equation, a lack of conflict sensitivity analysis and limited protection assessments. The available
protection analysis is usually limited to the overall chronic issues in the country, while conflict and
displacement related risks and threats remain less explored and assessed.

Those limitations can be overcome should the APC members prioritize the resources to fill those gaps
and increase their commitment to the coordination system for the protection sector.

A workshop with APC members will be organized in the course of August 2017 which will provide an
opportunity to produce a joint protection analysis that would support a prioritization exercise.

Integrated protection response plans are also under development at regional level and will provide a
regional perspective of the protection context and priorities.

Page **10** of **12**

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

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Input: is largest in the Somali domain (where it increases to 89 compared 76 percent for males). A similar pattern is observed regarding being comfortable with having a refugee neighbor. 0 10 20 30 40 50 60 70 80 90 100 Eritrean Somali South Sudanese Addis Ababa All Hosts Strongly agree Agree Disagree Strongly disagree Percent Figure 7.1: Host response to “Refugees are good people” Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 90 100 Eritrean Somali South Sudanese Addis Ababa All Hosts Comfortable Neutral Not comfortable Percent Figure 7.2: Host response to “Would you feel comfortable having a refugee as a neighbor?” Source: World Bank Staff based on SESRE 2023. Markets and Opportunities 65 0 10 20 30 40 50 60 70 80 90 100 Male Female Male Female Male Female Male Female Eritrean Somali South Sudanese Addis Ababa Comfortable Neutral Not comfortable Percent Most Ethiopian hosts want refugees to have access to free primary education and healthcare and the right to work, and to live where they choose. Eighty-seven percent of hosts believe that refugees should have the right to free primary education and healthcare, increasing to 95 percent in

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Input: 20 of intense conflict. We examine also the overall impact of the 25 years of conflict on educational outcomes. This analysis allows us to consider the full long-term impact of the conflict on educational outcomes of different generations of children in Timor Leste. 4. 2. 1. The educational impact of the 1999 wave of violence We exploit variation in the number of killings over time and across districts to identify conflict affected individuals. Our intention here is to analyze whether individuals exposed to the violence during their primary school age show different primary school completion rates eight years after the end of the war, relative to those not affected by the conflict. The outcome variable in which we are interested is whether individuals completed primary school in 2007. Figure 7 shows average primary school attainment for all individuals in our sample. The graph shows an increasing trend in primary school completion across cohorts and a progressive reduction of the gender gap. The gap among the younger cohort (those born after 1987) is almost zero. The drop in the curve for the younger cohort confirms the presence of significant delays in school attendance. For the purpose of this analysis, we use the TLSS 2007 dataset and the HRVD dataset contained in the CAVR data publication. Usage context: background mention, primary mention, supporting mention.

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Input: In other contexts, deregistration signifies not the achievement of a durable solution but rather the end of state or international support (IDMC 2015). 33 The absence of a clear and operational approach to defining the ‘ end ’ of internal displacement may be one of the factors behind the continued overall increase in the global numbers of IDPs. Lack of clarity around when displacement ends also leaves room for political manipulation. Governments may find it politically expedient to artificially prolong IDP status by deterring returns or local integration, for example in Azerbaijan and Georgia to promote claims over territory (Beau 2003). In other contexts, national 28 UNHCR ’ s IDP data focus only on internally displaced populations to which it extends protection or assistance. IDMC coverage of IDP data is more expansive and in 2015 included additional data on: (a) 26 countries accounting for 4. 5 million IDPs including some significant IDP hosting countries (Turkey, India, Ethiopia, Bangladesh and Kenya); and (b) IDPs in countries where UNHCR is active who are not protected or assisted by the agency. In 2015, IDMC ’ s aggregate figure for conflict-induced internal displacement was 3. 3 million higher than UNHCR ’ s aggregate figure for IDPs protected or assisted by the agency. 29 IDMC ’ s 2016 report presents both data sets alongside each other. Usage context: primary mention, background mention, supporting mention.

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Input: to inform decisions such as the size of schools to ensure progress toward inclusive systems that support refugees and their hosts can be made. Strengthening the use of statistics includes facilitating access to data and disseminating results. The SESRE is an excellent start to this initiative. Yet, the need to systematically integrate refugees in every round of the national household surveys and other data collection activities is key to allowing for evidence-based policy making. 77 Abdelhady D., and Al Ariss, A. (2023). How Capital Shapes Refugees’ Access to the Labour Market: The Case of Syrians in Sweden. The International Journal of Human Resource Management, 34(16), 3144-3168, DOI: 10.1080/09585192.2022.2110845 Abu-Ghaida, D., and Silva, K. (2020). Forced Displacement and Educational Outcomes: Evidence, Innovations, and Policy Indications. Second issue. Quarterly Digest on Forced Displacement. Washington, D.C.: World Bank Group, UNHCR and JDC. Adda, J., Dustmann, C., and Görlach, J. S. (2022). The Dynamics of Return Migration, Human Capital Accumulation, and Wage Assimilation. The Review of Economic Studies, 89(6), 2841-2871. Alix-Garcia, J., Walker, S., Bartlett, A., Onder, H., and Sanghi, A. (2018). Do Refugee Camps Help or Hurt Hosts? The Case of Kakuma, Kenya. Journal of Development Economics, 130, 66-83. Alkire, S., Kanagaratman, U.,

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Input: 17 significant for both selected and non-selected youth (see the 𝛽 ൅ 𝛿 estimate and the 𝛽 estimate for columns 2 & 3). Lack of results also holds for specification 3, where imputing missing data with upper and lower bound estimates to account for the potential bias introduced by attrition did not alter the lack of impact of the program, as well as for specification 4 (see the 𝛿 estimate). Figures 1, 2, and 3 plot the distribution of soft skills scores at baseline for both selected and non- selected youth. The figures indicate that scores across the three skills are concentrated towards the end of the scale, suggesting that soft skills training offered by NVSP might have been ineffective or too basic for this pool of volunteers. 19 Indeed, as table 1 shows, a high percentage of selected youth (71 percent) and non-selected youth (63 percent) had taken previous training in soft skills prior to NVSP. Results from a process evaluation conducted separately support this explanation. The majority of NVSP volunteers in focus group discussions and interviews mentioned that they would have welcomed more advanced trainings on soft skills, as well as on technical topics and job-relevant skills that can support their employability. Usage context: background mention, primary mention, supporting mention.

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Input: among refugees and their best-preferred pulse. CSB is a corn soya blend with added essential micronutrients and vitamins called super cereal. Based on this information, we compare how the distribution list shared what refugees should have received to what they reported regarding food consumption. The results show that refugees reported quantities lower than WFP food aid admin data for every item except for CSB+ and salt (Table E.6). Even when correcting for shares indicated as sold, refugee households still reported lower quantities. Using the WFP food aid information, we found a picture similar to UNHCR’s. Annexes 127 Table E.5: Food quantity and expenditure comparisons Items Quantity (per capita/year) Expenditure (per capita/year) SESRE WFP SESRE WFP Nonzero All Net of sold ration* Cereals 82.0 77.9 2,179 Wheat 60.5 1,427 Pulse 17.1 15.6 1,366 Peas 5.7 137 Vegetable oil 3.7 5.4 5.0 627 967 CSB+ 19.3 11.1 10.1 36 394 Salt 1.6 1.8 1.7 57 63 All cereals 76.9 - - 2,994 All pulses 8.3 - - 385 Aggregate ration/month 46.7 - Source: WFP and World Bank Staff based on SESRE 2023. Note: *Net of sold ration = quantity*share of ration sold (we asked the share of ration sold in SESRE) Table

WFP food aid information
WFP food aid admin data

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Input: Following the approach used for the Global Costing of Refugee Inclusion, successful inclusion is defined as earning sufficient income to be no longer poor and to consume more than the (international) poverty line. This definition opens two tracks for investigation: first, how much aid would be needed if the policy objective were to bring refugee consumption up to the poverty line. The answer to this question is found by identifying the poverty gap for refugees. This opens the second track which explores the factors that determine, or at least that are associated with, the size of the poverty gap. The note is organized as follows. The next section discusses data and presents some key descriptive statistics on refugees and host communities in Uganda. This is followed by a methodological section discussing how own income and aid are complements and how an analysis of poverty gaps informs about the need for assistance. This is followed by two analytical sections. The first identifies refugee poverty gaps, and assistance needs for refugees with distinct characteristics. The following section estimates how much has been saved by including refugees in the economy and explores how more could be saved. Conclusions follow. 2 The poverty numbers in World Bank (2019) are based on the official poverty line adopted in Uganda in 1997. There was a need to update this line as it was too old and producing a very low poverty rate. For example, using this line produced a national poverty rate of about 21 percent in 2019 / 20 compared to more the than 40 percent international poverty rate using the USD 2. 15 2017 PPP daily poverty line. In order to address this criticism, the poverty line was revised by the Uganda Bureau of Statistics in 2021, but it is not available for the 2018 Refugee and Host Communities Household Survey used in this note. Instead, we are using the international poverty line throughout.

2018 Refugee and Host Communities Household Survey

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Input:
1 2 3 4 5 6 7 8 9 10
Decile

JFPR applicants: Enrollment at any school, by
scholarship status and decile

<!-- PAGE 20 -->
**Figure 2: Proportion of girls who complete grade 7 among those who completed grade 5,**
**by economic status decile, DHS data**

Outcomes** Enrolled in JFPR school 0.87 0.65 0.22 0.00 Attending on the day of school visit 0.80 0.58 0.22 0.00 Enrolled in any school 0.90 0.77 0.13 0.00

**form)** **variables)**

**Enrolled at JFPR school** 0.222*** 0.292*** 0.303*** 0.413*** 0.065* 0.302*
(0.018) (0.021) (0.022) (0.056) (0.036) (0.166)

**Enrolled at JFPR school** 0.222*** 0.292*** 0.303*** 0.413*** 0.065* 0.302*
(0.018) (0.021) (0.022) (0.056) (0.036) (0.166)
**Attending JFPR school on day of visit** 0.223*** 0.299*** 0.313*** 0.426*** 0.094** 0.436**
(0.018) (0.022) (0.023) (0.056) (0.040) (0.188)

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Input: Overall, 27 % of the transitions that occurred had an imputed month. Two things to keep in mind when considering this table. This does not show all the respondents-time periods in our sample (8, 240 observations). Since imputation will only occur when there is a transition in or out of a job, we are only including in the table those transitions and not all the periods where the individual is staying in a certain job. The total number of transitions is 726 which is less than the total number of individuals in the sample. That is because for some individuals all transitions occur prior to 2016 so they are not captured in our synthetic panel. Table 2 Transitions in and out of jobs by half, nationality, camp residency and imputation status of the month where the transition occurred Half Jordanian Syrian camp = 0 camp = 1 Usage context: primary mention, supporting mention, background mention.

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

PIHS
Living Standard Measurement Surveys

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

Labor Force Surveys
Living Standards Measurement Study
Multiple Indicator Cluster Surveys

individual registration of refugees and asylum seekers

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Input: Moreover, some refugees may not register because they are unaware that they should, and others may be reluctant to do so because they are skeptical of the integrity of the registration process (e. g. fair access to entitlements or opportunities for durable solutions) or lack confidence in protection measures. Individuals in irregular migration flows may also choose not to apply for asylum due to fear of declaring themselves to the authorities. A significant challenge with refugee registers is keeping them up to date. Individual registration can provide a robust snapshot of the stock of refugees and asylum-seekers, but registers need to be updated regularly to reflect flows, i. e. increases in refugee and asylum-seeker numbers (births, new arrivals) and decreases (deaths, departures, durable solutions). In situations of sudden mass influxes, existing registration capacity may not be adequate and the scope of registration data is then rationalized. 65 Additionally, it may not be possible to capture all demographic changes in the case of highly mobile populations. Usage context: primary mention, supporting mention, background mention.

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Input: 21 Lebanon. It was the obvious step forward in overcoming these problems and the answer to the increasing demand for evidence around the Syrian crisis. The study benefitted from a unique and unprecedented set of data. The UNHCR registry data in Jordan and Lebanon were among the better quality registry data available worldwide and the UNHCR also conducted home visits in Jordan that, at the time of the study, covered over a third of all refugees. There were also sample surveys in both Jordan and Lebanon that were small in size but representative of the population present in the registry. The home visits and the surveys included questions on income and expenditure that could be used for the welfare assessment. Using these data, the study addressed ten questions defined as follows: 1) Who are the refugees?; 2) How different are refugees from “ regular ” populations?; 3) How poor are refugees?; 4) What are the main predictors of refugees ’ welfare and poverty?; 5) How vulnerable are refugees from a monetary and non ‐ monetary perspective?; 6) Do poverty and vulnerability statuses overlap?; 7) How effective are refugee assistance programs?; 8) What is the potential for alternative policies?; 9) How does welfare compare across countries and data sets?; 10) How transferable are Usage context: background mention, supporting mention, primary mention.

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Input: 10,000 15,000 20,000 25,000 30,000 35,000 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Figure D.28: Value of productive assets in households with business Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 Percent 70 80 90 100 Hosts Refugees Hosts Refugees Hosts Refugees Eritrean Somali South Sudanese Employed Unemployed, searching Unemployed, not searching Inactive not in school Inactive in school Figure D.30: Youth work status by survey domains Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 90 100 Hosts Refugees-Current Refugees-COB Hosts Refugees-Current Refugees-COB Hosts Refugees-Current Refugees-COB Eritrean Somali South Sudanese Salary (employment/casual labor) Crops/livestock Donations(NGO/gov) Remittances (local/international) Other (rental income, PSNP, pension) Percent Figure D.29: Primary source of income pre-post migration by survey domains Source: World Bank Staff based on SESRE 2023. Annexes 111 Results on Refugees’ Aspirations Table D.10: Refugee intention to migrate abroad (1) (2) Camp-Based Refugees OCP Refugees Male 0.022 -0.001 (0.019) (0.008) Age Under 30 - - Age 30-44 -0.000 -0.007 (0.020) (0.008) Age 45-64 -0.082*** -0.088** (0.027) (0.036) Education: Primary incomplete - - Education: Completed primary -0.008 0.004 (0.036) (0.009) Education: Completed secondary 0.016 0.006 (0.064)

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Input: Source: UNHCR Statistical Online Population Database Note: Only includes refugee situations greater than 25, 000 people. Excludes high-income (OECD and non-OECD) countries. Excludes Palestinian refugees under UNRWA ’ s mandate.

UNHCR Statistical Online Population Database

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Input: 17 Figure 10: Children aged 7-12 attending school (%) Source: Listening to Displaced People Survey, 2014 and 2015. 5. Challenges Faced by Returnees The results suggest that returnees were less affected by the crisis than IDPs and refugees. This is reflected in data on asset and livestock ownership, but also in the information pertaining to exposure to violence. Returnees reported fewer victims; fewer returnees reported to have lost income as a consequence of the crisis; more of their children were able to continue schooling; and relative to IDPs and refugees, fewer perceived being poorer in June 2014 than before the crisis. Returnees are also the group that feels most secure, that has high levels of trust in the Malian army and police and that has a positive attitude towards most government policies. 88 88 97 79 76 78 99 88 92 55 74 72 91 98 92 96 100 85 90 91 96 90 86 87 87 95 89 76 75 90 94 92 97 86 73 98 Bamako Gao Timbuktu Kidal Niger Mauritania IDPs Returnees Refugees 14-Aug 14-Oct 14-Nov 14-Dec 15-Jan 15-Feb Usage context: supporting mention, primary mention, background mention.

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Input: 2 INTRODUCTION In 2015, an estimated 2. 2 million Syrians Under Temporary Protection (SUTPs) were residing in Turkey, the majority arriving in the country over the last 4 years. 2 Turkey ’ s national population is roughly 75 million; recent refugees account for approximately 3 percent of the population. For a country that has never experienced such a large-scale, sudden inflow of foreigners, demographic changes in the composition of the population and labor force will yield unprecedented implications. This paper examines, as data allows, the relationship between the size of the foreign-born population and host community poverty rates in Turkey. First, this paper finds the poverty rates of ‘ recent migrants ’ near the Syrian border (NSB) significantly increased from 2009 to 2013. Second, the number of foreign-born households being captured by the Labor Force Survey (LFS) is expanding, which suggests a growing number of foreign households that are likely to be Syrians. Third, with respect to poverty, the results show no negative impacts on the host community as a result of the increasing size of the foreign-born population. The impact of SUTPs has been both positive and negative. Overall, a significant negative impact on host communities ’ welfare is not observed in the data. Usage context: primary mention, supporting mention, background mention.

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Input: In most other cases, sexual and gender-based violence is a crime of opportunity that is often committed by relatives rather than strangers (Wood 2009, 2006). A study of sexual violence in a pediatric ward in Goma, Democratic Republic of the Congo, showed the predominance of domestic sexual violence over militarized rape. Of 500 pediatric cases treated for sexual violence at the hospital (2006 – 2008), nearly all were females between the ages of 10 and 18 (Kalisya and others 2011). Also in the Democratic Republic of the Congo, the results of a population-based household survey with a randomly assigned module on sexual violence (a subsample of 3, 436 women) yielded a very high prevalence of rape — an estimate of more than 400, 000 women were raped in the 12 months prior to the 2007 survey — and showed that the most pervasive form of sexual violence was from intimate partners and that the most conflict-affected provinces were at higher risk of sexual violence (Peterman, Palermo, and Bredenkamp 2011). A population-based random cluster survey of adults in Liberia (conducted in 2008) is one of the few quantitative studies on the legacy of sexual violence in conflict situations. The study showed Usage context: background mention, supporting mention, primary mention.

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Input:
this approach to calculating hunger the HCES-direct method. Of note is that neither the FBS-CV nor the

HCES-direct method actually measures what individuals ate (as in a food intake survey) or ask about

The FBS-CV and HCES-direct methods both rely on household surveys. In the case of the FBS-CV method,

the second moment of the calorie distribution comes from the surveys, while the HCES-direct method

relies on the surveys for all moments. Yet, the design of HCES varies over several key dimensions, such

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Input: 10 scored on a Likert scale running from 0 (significantly worse) – 10 (significantly better). The survey questions on optimism were collected at outreach, baseline and endline. Employment status: Due to slight differences in access to labor markets for refugees in Jordan and Lebanon and differences in how we were able to ask about employment status, we tabulate employment status as whether or not an individual is employed. Participants were asked at outreach about their employment status, and, in subsequent rounds, whether or not this had changed. This variable is coded 0 for not currently employed and 1 for employed. Economic scarcity: We collect survey questions on individual perceptions on: ability to meet current needs; ability to meet future needs; expectation that access to jobs is fair; expectation that salaries are fair; and belief that unfair access to labor markets fuels tensions. Ability to meet current and future needs are coded on a Likert scale running from 1 (completely unable) to 5 (fully able). The “ fairness ” indicators are coded: 0 (unfair) or 1 (fair). Whether or not competition around employment contributes to tensions is captured on a 1 (not at all) to 5 (absolutely) Likert scale. Usage context: background mention, primary mention, supporting mention.

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Input: The SEIS questionnaire includes a dedicated section on labor market status that mirrors the ILO reference week definition used in the national LFS. This alignment allows direct comparison of employment rates between the refugee population captured in SEIS and the national working-age population captured in the LFS, controlling for differences in age structure and educational attainment. Preliminary comparisons show that SEIS-measured employment rates for working-age refugees are 14 percentage points below LFS-measured national rates, net of compositional differences.

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Input: Treatment Randomization: The housing subsidy program was randomized geographically at the community level. 8 In the ﬁrst step, 158 communities in Irbid and Mafraq were randomized into treatment or control for HSP assistance, stratifying on governorate and district population quartile. One third of communities were randomly assigned to treatment, while the remaining two thirds were randomly assigned to control. All eligible applicants living in the treatment communities were assigned to treatment. In all analysis below, error terms are clustered at the community level. There were several reasons for the cluster randomized design, including the ability to streamline implementation (and thus lower program costs), to reduce conﬂict among refugee households as- signed to treatment versus control, and to improve the analysis of treatment spillovers onto host community members by boosting the local saturation of program assistance, thereby making it more salient to neighbors. Refugee Sample: The survey sample consists of all refugees assigned to treatment and an 7See AER RCT Registration Number AEARCTR-0006141. 8Communities correspond to the Jordanian government ’ s administrative unit of “ localities ”. Communities in Mafraq have 3, 866 people on average, while those in Irbid are somewhat larger at 14, 626 individuals on average. 10 Usage context: supporting mention, primary mention, background mention.

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Input:
**Table 8: Flood Risk Classification of Proposed Subproject Sites**

| Site ID | District | Elevation (m) | 50-yr Flood Zone | Design Adjustment |
|---|---|---|---|---|
| S-04 | Rambora North | 312 | Outside | None |
| S-11 | Kalendo East | 287 | Inside | Elevated plinth |
| S-17 | Mwenda Central | 301 | Boundary | Drainage upgrade |
| S-22 | Ngozi West | 318 | Outside | None |

Flood hazard maps used for this classification were prepared by the National Flood Risk Management Authority and validated against historical flood records from the Ministry of Home Affairs' disaster registry.

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Input: 3 MPI, constructed in Admasu et al. (2021), to capture the deprivations of forcibly displaced individuals and their gendered lives. The paper proceeds as follows. Section 2 reviews the existing literature to provide the background and motivation for the analysis, including a summary of the different country contexts covered by the case studies in this paper. Section 3 outlines the measurement strategy for deconstructing the MPI used for analysis and its limitations, followed by Section 4, which introduces the data. Section 5 presents the findings, first for deprivation results at the individual level and then results evaluating intrahousehold inequalities. Concluding remarks are discussed in Section 6. 2 Background and Literature Review 2. 1 Individual-level measures of gender and multidimensional poverty Individual-level analyses of multidimensional poverty have mostly centered around children, with various studies analyzing the relevance of indicators for children (aged 0- 17 years), 2 as well as other age ranges. The MPI has also been used to better understand gender issues, for example, Batana (2008) implemented a women ’ s MPI in Sub-Saharan Africa. Bhutan ’ s Gross National Happiness measures (2010, 2015), Vijaya et al. (2014), and Klasen and Lahoti (2016) are implemented at the individual level. Usage context: supporting mention, background mention, primary mention.

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Input:
the World Bank's Poverty and Inequality Platform (PIP). PIP is managed jointly by the Data and

Research Groups in the World Bank's Development Economics Division. It reports both poverty

measures and inequality measures, including the Gini Index for 168 countries from 1968 to 2022. The

Gini index is based on primary household survey data obtained from government statistical agencies

alternative dataset that provides inequality measures. Specifically, we use the Standardized World

Income Inequality Database (SWIID). [5] The SWIID maximizes the comparability of available income

<!-- PAGE 10 -->
Income Study database.

Data on natural disasters is from the EM-DAT database maintained by the Centre for Research

Poverty and Inequality Platform
Gini Index
Income Study database
EM-DAT database

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Input: Both treatment and control group respondents report equally high confidence in their ability to return to school “ should [she] decide to do so. ” These findings from the quantitative impact evaluation complement the results from a set of qualitative focus group discussions that were held with participants at the end of the 6 months of classroom training. Twenty-five percent of the trainees from Round 1 participated in a total of 34 focus group discussions that covered a variety of topics including their satisfaction with the program and their empowerment in both social and economic realms. The trainees overwhelmingly voiced a high degree of satisfaction with the training, and trainers commented on how the motivation or “ seriousness ” of the participants grew over the 6 month period. The trainees credited the transport allowance and free childcare in particular as features that facilitated their full participation; as one trainee commented, 22 Questions adapted from the Adolescent Self-Regulation Inventory, developed and validated for youth in the United States by Moilanen, 2006. The questions were revised and translated into an 11-item for the Liberian context. In the future, we plan to conduct basic testing on this scale on internal consistency and reliability. 17

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Input: environment. Any issues discovered during these monitoring visits were brought to the attention of service providers and resolved swiftly in conjunction with the project coordination team at MoGD. Eligibility: The EPAG program was targeted to young women who: i) were age 16 to 27, ii) possessed basic literacy and numeracy skills, iii) were not enrolled in school within several months prior of the program initiation, and iv) resided in one of nine target communities in and around Monrovia. 6 These eligibility criteria stemmed from the project's objectives to reach young women at an early enough age to significantly improve the trajectory of their working years, to focus on girls who already had the basic literacy and numeracy skills needed to succeed in the labor market, and to avoid incentivizing applicants to drop out of school.

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

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

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Input: However, we can- not exclude the possibility that refugees would sort non-randomly into areas with particular ethnic characteristics. 19 In order to address this potential endogeneity, we implement an instrumental variable (IV) ap- proach. We are particularly concerned about certain ethnic groups from certain countries of origin moving to destination countries with similar ethnic characteristics. Such endogenous selection would be reflected in the EPR-ER data. To deal with the plausibly endogenous nature of the resulting refugee EF and EP indices, we implement a gravity model to predict the number of refugees of a certain ethnic group e moving from country o to d at time t, based on EPR-ER data. The predicted (and plausibly exogenous) number of refugees by ethnic group e is then used to create other (plausibly exogenous) diversity indices to be used as instrumental variables. More specifically, we estimate the following gravity model: 17We also use this method to link data from EPR-ER on the ethnicities of refugees with data from the Murdock Atlas on their historical homeland (Section 4. 3). 18As a robustness check (Section 5. 3), we use an alternative linkage based on the relations between sets of language nodes associated with two groups. 19Another source of selection may come from the fact ethnic groups are more likely to be displaced when they share territory with regime supporters in their countries of origin (Lacina et al., 2017). Since similar ethnic groups are likely to share common borders (Michaelopoulos and Papaioannou, 2016), it is not impossible to think conflict might spill over through this channel. 19 Usage context: primary mention, background mention, supporting mention.

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Input: The GIS-based beneficiary targeting map was reviewed during the midterm assessment to verify that the communities selected for Component 2 infrastructure investments remained those with the highest unmet need. Updated displacement figures from UNHCR and poverty scores from the Ministry of Social Welfare were overlaid in the GIS to check whether the original targeting ranks had shifted. The GIS reanalysis confirmed that 41 of the original 47 target communities remained in the highest-need tertile; the six communities that fell below the threshold were replaced through a targeted consultation process.

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

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Input: The Women ’ s Empowerment in Agriculture Index (WEAI) (Alkire et al. 2012) uses individual-level data, and the linked Gender Parity Index reflects inequalities across women and men ’ s deprivation scores within the same household. Alkire, Apablaza and Jung (2014) design and implement an exploratory individual-level MPI for 31 European countries over six waves of data using EU-SILC data sets, finding no cases in which are women significantly less poor than men, and in many cases, they are significantly poorer. Espinoza-Delgado and Klasen (2018) create an individual-level MPI to understand differences in poverty between women and men in Nicaragua, finding similar overall incidence, but much higher intensity of poverty among women. Bessell (2015) and Pogge and Wisor (2016) explore deeply contextual gendered poverty measures and elucidate the ways that participatory consultations can inform the design and uses of gendered measures. Rogan (2016) uses the global MPI to analyze the gender poverty gap in South Africa. Alkire, Ul Haq, and Alim (2019) use individual-level data alongside MPI data to expose gendered and intrahousehold differences among MPI poor and non-poor children. Usage context: primary mention, background mention, supporting mention.

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Input:
Chinese Exports in Agriculture and Food Products**   Value of Exports in Billion USD        _Source_ : COMTRADE Database, Authors calculation    19     <!-- PAGE 23 -->  **Table 1.

6 [http://faostat.fao.org/](http://faostat.fao.org/)   6     <!-- PAGE 10 -->  standards and heavy regulation (Chen and Findlay 2008).Chinese exports in agricultural and  food products are increasing.

Although there is no data on the implementation of  voluntary standards, the China Statistical Yearbook of Certification and Accreditation (cited in  Jin et al.

China Statistical Yearbook of Certification and Accreditation

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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, supporting mention, background mention.

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Input: mean CEI over our sample period. Since return decisions are likely impacted by the persistence of conﬂict, we classify districts into high and low conﬂict districts, using the top 10th percentile of the mean CEI as a cut-oﬀpoint. 11 We will use this classiﬁcation to explore the extent to which return decisions of key social and demographic groups are impacted by the persistence of conﬂict. Survey of refugees in Lebanon and Jordan: In a survey of 900 Syrian refugees in Jordan and Lebanon, we randomly varied the details of the scenario or vignette presented to a given individual respondent. Some refugee families are certainly more predisposed to wanting to return than others. By describing hypothetical scenarios, but ones which hit fairly close to home, and varying key factors within those scenarios should help us identify what factors are important to many refugee families when deciding whether to return. For all respondents in all vignettes, we asked “ How likely is this family to return to Syria in the next 2 months? ” where the respondent could answer using a Likert scale, ranging from “ Very likely ” to “ Very unlikely ”. For the analysis below, we use an indicator which is equal to one if a respondent says the family is either very likely or likely to return, and 0 if the respondent says neutral, unlikely or very unlikely. Usage context: supporting mention, primary mention, background mention.

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

Administrative Venezuelan Migrant Registry

Administrative Venezuelan Migrant Registry (RAMV)

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Input:
future year by the counterpart observation in the CRU benchmark dataset (from the most

representative temperature/rainfall combination, derived from CRU data for 1980-2000).

departure: the benchmark series from the CRU data. This translation step is necessary

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

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

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


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

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

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

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


Input: 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.

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

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

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


Input: 14 people may also gain from conflict in terms of income and wealth and this may explain why some people do not move. The defining attributes of the alternative choices are very different from any other model and the task of economics is to understand what these defining attributes should be. In terms of independent variables, “ push ” factors become more important than “ pull ” factors in forced displacement models. The intensity of a conflict may be more important than the income opportunities in potential destination areas. In addition to the classic socioeconomic variables, risk aversion, stress, anxiety, other traits of personality and behavioral factors in general have to be well understood and measured. Hence, one could think of four essential blocks of independent variables including individual or household socioeconomic characteristics, “ push ” factors, “ pull ” factors and behavioral factors. Also, access to and dissemination of information related to the conflict in the place of origin but also in the potential places of destination may be crucial for people to make choices. This is where social psychology, behavioral economics and neuroeconomics may offer insights into such choices. Forced displacement data are also unusual in their form. 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

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:
random variation, seasonal variation, and measurement error. Furthermore the FAO forces any CV to lie

motivation for this second approach, which is purely illustrative, is that the FAO derives this mean from

The third and final component needed to replicate the FAO calculations is to use the sample average of

daily energy requirement (2068 kcal per person per day). Using these estimates, the FAO approach

11 This is the last FAO report on which we have a detailed description of the exact mechanisms used. The
methodology used has been modified slightly since then, as explained Annex 2 of FAO (2012) and footnote 4.

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:
Survey data, for example from large household survey programs such as the Demographic and Health Surveys (DHS), Multiple Indicators Cluster Survey (MICS), or Living Standards Measurement Study (LSMS) is independent of public record keeping and can also capture vaccination obtained through private or non-governmental providers

The data that support the findings of this study are available from the from the Central Statistical Office of Poland and the Orbis database of Bureau Van Dijk.

Multiple Indicators Cluster Survey (MICS)

Living Standards Measurement Study (LSMS)

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Input: ICRC ’ s work is based on the Geneva Conventions of 1949, their Additional Protocols, its Statutes — and those of the International Red Cross and Red Crescent Movement — and the resolutions of the International Conferences of the Red Cross and Red Crescent. 84 WFP is the food assistance branch of the United Nations and the world's largest humanitarian organization addressing hunger and promoting food security. 85 See: popstats. unhcr. org. 86 IDP data are only included from 1998 onwards. 87 See: http: / / data. unhcr. org. Currently the Burundi situation, Yemen (regional refugee and migrant response plan), DRC regional refugee response, Mediterranean (refugees / migrants emergency response), CAR, Côte d ’ Ivoire, Syria Emergency, Sahel Emergency, South Sudan Situation, Horn of Africa Emergency, and the Liberia Portal. 88 IOM ’ s new Global Migration Data Analysis Centre provides limited data on global migration trends such as data on asylum application in Europe and selected countries (including demographics, country of origin, and country of asylum). Usage context: primary mention, background mention, supporting mention.

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Input: 10 as the Demographic and Health Surveys (DHS), though researchers have reduced under-reporting by providing special training to interviewers, placing greater emphasis on respondents ’ privacy and safety, and allowing women multiple opportunities to disclose their experiences (Ellsberg et al., 2001a; Garcia Moreno et al., 2003; Ellsberg et al., forthcoming). Estimates of the magnitude of the problem Population-based surveys have found that between 10-70 % of women report being physically assaulted by an intimate male partner at some point in their lives (Heise, Ellsberg and Gottemoeller, 1999). See Annex A for estimates from many recent population based studies (Ellsberg et al., forthcoming). Findings from a multi-country study on domestic violence and women ’ s health carried out by the World Health Organization in fifteen sites and ten countries found that between 13-62 % of women had experienced physical violence by a partner over the course of their lifetime, and between 3-29 % of women reported violence within the past year (Figure 1. 1). Figure 1. 1. Usage context: background mention, supporting mention, primary 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. Usage context: primary mention, background mention, supporting mention.

Displaced People Survey
Afrobarometer perception survey

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Input: Journal on Education in Emergencies, Inter-agency Network for Education in References 80 References Emergencies, 5(2). https://doi.org/10.33682/f1wr-yk6y. Ravallion, M. (1998). Poverty Lines in Theory and Practice: Living Standards Measurement Study. LSMS Working Paper, Issue 133. https://documents1.worldbank.org/curated/en/916871468766156239/pdf ReDSS. (2018). Local Integration Focus: Refugees in Ethiopia - Gaps and Opportunities for Refugees Who have Lived in Ethiopia for 20 Years or More. ReDSS. Rotter, J. B. (1966). Generalized expectancies for internal versus external control of reinforcement. Psychological monographs: General and applied, 80(1), 1. RRS. (2017). Road Map for Implementing the Federal Democratic Republic of Ethiopia Government Pledges and the Practical Application of the CRRF in Ethiopia. RRS RRS. (2019). Directive to Determine Conditions for Movement and Residence of Refugees Outside Camps, Directive No. 01/2019. RRS RRS. (2019a). Directive to Determine the Procedure for Refugees Right to Work. Directive No. 02/2019. RRS. (2019b). Refugees and Returnees Grievances and Appeals Handling Directive. Directive No. 03/2019. RRS, and UNHCR. (2021). Ethiopia GRF Pledge Progress Report. RRS and UNHCR Shamsuddin, M., Acosta, P.A., Schwengber, R.D., Fix, J., and Pirani, N. (2021). Integration of Venezuelan Refugees and Migrants in Brazil. Policy Research Working Papers 9605. http://hdl.handle.net/10986/35358. Schuettler, K., and Caron, L. (2020). Jobs Interventions for Refugees and Internally

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Input: protracted nature of refugee hosting in Ethiopia, it is essential to better understand how vocational training programs and cooperatives can become self-sustainable, especially in the more remote border regions with poor market linkages. Box 3.3: Refugee Vocational Training and Cooperatives Jobs and Livelihoods 35 In line with high reliance on remittances, labor force participation and employment rates among OCP refugees are low, with rates similar for male and female refugees. Table 3.2 presents labor force participation (LFP) data; among those aged 15-64, LFP is 46 percent for refugees and 66 percent for hosts. This increases to 67 and 72 percent when you use the relaxed definition of unemployment, reflecting the large number of OCP refugees who say they are ready to work but are not actively searching. The unemployment rate is an astonishing 63 percent for refugees relative to 12 percent for hosts, and it increases to 75 percent under the relaxed definition. Only 17 percent of OCP refugees work, and 23 percent are inactive and not in school. Female refugees have similarly large rates of inactivity and unemployment, and the total share working is similar to male refugees. Female refugees also have high rates of self-employment relative to female

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

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

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