ai4data/datause-dataset-rechunked huggingface dataset:
Furthermore, in some contexts, registration as an IDP can expire after a prescribed timeframe without regard to whether the person achieved a durable solution (e. g. after five years in Russia). The accuracy of IDP registers is greatly impacted by political considerations, particularly a government ’ s willingness to acknowledge internal displacement and to enable the humanitarian community to respond. Some countries may be reluctant to acknowledge the presence of IDPs, or may be inclined to understate numbers to demonstrate progress in military operations or limit assistance provided to IDPs. For example, in Kenya, registration of individuals displaced by the 2007 and 2008 post-election violence excluded ‘ integrated ’ IDPs, i. e. those who had sought refuge with host communities or rented accommodation in urban areas, as assistance was limited to registered IDPs. Alternatively, aggregate numbers of IDPs in particular countries may be inflated to suggest a deterioration of the situation or to maximize humanitarian assistance. Therefore, access to IDP areas and the willingness of IDPs to be counted may be largely dependent on government policies. These political considerations can lead to disagreements on the data, undermine cooperation and in some cases even lead to reduced humanitarian funding. Profiling of IDP situations Profiling of IDP situations is a collaborative process aimed at generating reliable data that can be broadly agreed upon. As a collaborative process, it can be a crucial tool for generating agreement on persistent questions such as who is recognized as internally displaced within a given context, what are the most prevalent vulnerabilities caused by displacement, and how do IDPs fare compared to host populations. In sought refuge with host communities or rented accommodation in urban areas, as assistance was limited to registered IDPs. 68 However, in many conflict-affected countries, governments lack the basic capacity to maintain Civil Registration and Vital Statistics (CRVS) systems including the registration of births and deaths in non-displacement situations, let alone the registration of IDPs displaced due to natural disasters or conflict. 69 IOM has introduced biometric registration systems in South Sudan, Sudan, DRC and Nigeria to circumvent
and Vital Statistics (CRVS) systems including the registration of births and deaths in non-displacement situations, let alone the registration of IDPs displaced due to natural disasters or conflict. 69 IOM has introduced biometric registration systems in South Sudan, Sudan, DRC and Nigeria to circumvent these problems.
While there is a large literature on the role of immigrants on the native-born population in terms of labor market competition, there is a limited amount of studies that examine the effect from displaced populations. Many conclusions from the traditional literature on the study of immigrants ’ impact on natives cannot be applied to the case of Syrians in Turkey. There are many differences between the inflow of Syrians and other flows of extended family and economic immigrants. First, the sheer volume of Syrian refugees and the short time- frame in which they entered Turkey is unprecedented. For the case of Syrians in Turkey, or displaced populations in general, large movements of refugees are not restricted due to humanitarian reasons. Second, formal immigration processes are controlled, limited, and regulated by destination countries. Therefore, results from literature on “ immigrants ” are very different than a focus on displaced or refugee populations. Recent literature on the labor market effects of SUTPs estimates negative impacts on host community employment rates. The negative displacement results are largest for the young, women, informal workers, 2 United Nations High Commissioner for Refugees (UNHCR) – Syrian Regional Refugee Response, Inter-agency Information Sharing Portal 3 (UNHCR) – Syrian Regional Refugee Response, Inter-agency Information Sharing Portal
**Annex 2**

**FGDs Questionnaire**

FGDs Questions :

1. Torture, Arbitrary detention, and Forced Disappearance, are some of the protection risks faced by youth
in NWS, from your point of view What solutions or actions would help mitigate/overcome these
protection risks?
2. The survey results conducted earlier in NWS indicated that 66% of youth are facing discrimination, if you
agree with that statement, can you please clarify and elaborate the factors contributing to
discrimination, exclusion, and stigmatization among youth in the region?
3. What challenges do young people encounter when trying to acquire official documents?
4. Which are the top 5 risks you believe young males face? and which are the tops 5 protection risks young
females face?
5. How can organizations engage young people in NWS in the rebuilding of their communities?
6. 54% of the surveyed youth in NWS who themselves or their family have properties and 83% of them
have property documents, could you explain more by whom it is occupied?
7. What are the main protection risks related to your/your family's properties?

Demographics:

Female Participants: Total of 50 across all FGDs, 25 in Aleppo/ A'zaz and 25 in Idleb/Idleb.
tegrated in Tajik labor markets relative to their previous situation in Afghanistan. This is a typical characteristic of forcibly displaced populations as it naturally take time for them to recover their livelihood. Moreover, females have lower labor market participa- tion rates, hours worked, and wages relative to men. We also see that student enrollment for individuals of schooling age is dramatically lower in Tajikistan relative to Afghanistan. Finally, not surprisingly, household size for refugees is smaller in Tajikistan, which likely originates from family separation due to forced displacement from Afghanistan. Outcome variables. Using the census data, we construct five index variables for each of the outcomes of interest: refugee integration, educational attainment, mental health, income and consumption, and labor market outcomes. Indexes for dichotomous vari- ables were constructed as the average of all outcomes. Indexes that include continuous variables were constructed standardizing each variable, averaging all variables, and stan- dardizing the average once again. The methodology to construct indexes was adopted from Kling, Liebman and Katz (2007). Appendix B. A describes in detail all the variables included in each of the indexes. In sum, each of the indexes comprises the following: Integration index: Includes four variables that measure the feelings of belonging of refugees in Tajikistan. These are measured using a Likert scale.
Papaioannou, 2016; Berman et al., 2017; Harari and Ferrara, 2018; Eberle et al., 2020; McGuirk and Burke, 2020b). As a further robustness check, we also use data on conflict incidence and intensity from the UCDP, which uses a more conservative definition of conflict. The UCDP dataset is manually curated and compiled with automated computer assistance (Sundberg and Melander, 2013). The UCDP defines an armed conflict event as “ an incident where armed force was used by an organized actor against another organized actor, or against civilians, resulting in at least one direct death at a specific location and a specific date ” (Pettersson et al., 2020). We extract daily event observations from the UCDP dataset if the location of the actual event is exactly known, the event location is within a radius of less than 25 km around a known point, or at least the administrative district where the event happened is known. As pointed out by Eberle et al. (2020), the UCDP events are more likely to capture violence between large-scale and more structured groups. Table B. 2 shows that on average, conflict events seem to occur more in refugee-hosting areas. This is of course not a causal interpretation but a simple correlation.
The cooperative medical scheme's benefit package was reviewed during project preparation to assess its adequacy for the health care needs of the target population. The review found that the scheme covered primary care visits and generic medicines at contracted facilities but excluded dental care, mental health outpatient services, and optical care. The project will support a targeted benefit expansion for enrolled refugees and host community members in the lowest two wealth quintiles, covering MHPSS outpatient consultations at no additional premium cost.
groupement level data cannot measure the character of the displacement in any meaningful way, but analysis at the individual level can. 5. 2 Individual Level Relationships Two survey waves posed additional questions on local displacement dynamics. While these ad- ditional questions restrict comparison with other survey waves, they provide the opportunity to unpack the mixed results found in the aggregate analysis. Poll 14 is a special survey that only sam- ples cities (Ville de Goma, Ville de Beni, Ville de Butembo, Ville de Bukavu, Ville d ’ Uvira, Ville de Bunia and Irumu in particular) while Poll 15 is a representative sample of all territoires in the three provinces. 11 These survey waves are labeled as “ Cities ” and “ General ” samples in the indi- vidual analysis. Analyzing these two surveys together enables the comparison of relationships by the local context, which may distort the impact that hosting has on perceptions of social cohesion. Figure 5 plots the coefﬁcients from series of logistic regressions to account for the binary na- ture of the dependent variables. The regressions include Province ﬁxed effects and groupement clustered standard errors to account for unmeasured context-speciﬁc dynamics. Responses are weighted by the inverse proportion of selection at the territoire in each regression.
The resulting migration matrices should be viewed as work in progress, but they are an important step in an ongoing global effort to improve migration data. The matrices can be readily updated as additional or superior information surfaces, and they can easily be extended to include future census rounds. Bilateral datasets of international migration are rare. Attempts to create them have focused almost exclusively on industrialized countries as destinations because these countries have more accurate and more frequently produced data. Harrison and others (2003) calculate bilateral remittances for the countries of the Organisation for Economic Co-operation and Development (OECD) together with the 27 largest nonmembers. These estimates are based on international bilateral migrant stock data that the authors also provide, although many of the data are derived from the Trends in International Migration (OECD 2002). This report, published annually since 1973, was arguably the most comprehensive guide to international migration for many years and has been the basis for many studies (see, for example, Mayda 2007). More recently, the OECD has developed a database that provides a comprehensive overview of migration to OECD countries in 2000 (OECD 2008). These data are disaggregated by a number of covariates including age, gender, educational attainment, and place of birth.
We, therefore, first examine whether or not there is structure, both, to selection into the treatment group and attrition, which could undermine our econometric approach, where we rely on difference-in-difference estimators. Imbalance between treatment and control groups could undermine the key assumption of parallel trends. For example, given that men and women face different barriers in the labor market, we should not expect employment to evolve in the same way for men and women after the treatment. We would expect to observe a difference-in-differences for a treatment group where women are more common than in the reference group, even without the program. To test for imbalances, we run a simple regression of treatment and attrition indicators at baseline on the socio-economic and demographic controls, GRIT indicators, self-reported optimism, employment status and risk. Table 4 (Column 1 for the treatment analysis, Column 2 for the attrition analysis) shows some signs of structure. In particular, host status and risk preferences are significantly different between treatment and control, with 9 For example, “ hummus ” is used to refer to chickpeas in general but can also be used for the dish involving mashed chickpeas, tahini, lemon and garlic in Lebanon. In other dialects, some qualifiers are required to specify this dish (e. g. hummus ne ’ em, or smooth hummus). This is akin to identifying a British or American individual using similar variations in foodstuffs such as courgette / zucchini; coriander / cilantro; etc. 10 Specifically, we regress variables with missing observations on the list of all variables with a complete record. We then use the predicted values from this regression to populate the missing variables. Where appropriate, predicted values are rounded to the nearest integer and within answer codes of that variable. In a second round, this process is repeated on the full set of actual and predicted values from the first stage.
The descriptive characteristics of foreign-born and host community households are still comparable, and therefore allow for comparisons between 2013 and 2014. It is possible to make some inferences on welfare changes by looking at changes in host community employment rates and labor market characteristics. Overall, this paper finds no negative effects on host community welfare from an increasing population of SUTPs. As other authors have stated, the influx of SUTPs has had both positive and negative impacts. It seems on average, the host community has been strong and adaptive, and not negatively impacted. This is not to disregard that real strains do exist in some regions where the SUTP population is very large. Nor do these results undermine findings of displacement effects in the labor market that certain types of workers are experiencing. However, on average nationally, we do not see a systematic decline in the welfare of the host community between 2011 and 2013. The remainder of the paper is organized as follows. Section 2 outlines the data availability and technical issues. Section 3 discusses descriptive statistics of the foreign-born and host community. Section 4 explores the impact of the foreign-born population on host community welfare. 1. DATA AND TECHNICAL ISSUES Data Sets Data availability limits which data set can be used to identify the foreign-born population and geographic location while measuring poverty. The Turkish Statistical Institute (TUIK) has been conducting three nationally representative surveys annually since 2005; the Household Income and Consumption Expenditure Survey (HICES), the Survey on Income and Living Conditions (SILC) and the Labor Force Survey (LFS). However the HICES, which is the national survey that is used to measure official poverty, 5 UNCHR, 2013pg 13 6 UNHCR (22 November 2013), UNHCR (15 September 2014) 7 UNHCR (22 March 2013), Erdogan (2014), pg 14 8 This technical issue will be discussed further later in the paper.
Ethiopia in 2017. The SPS 2017 was conducted in refugee camps and host communities in four regions in Ethiopia. The survey was used to draw a profile for skills and potential opportunities for refugees and host 9 See Annex C for detailed information on survey design and methodology. 10 Financial support was provided by the World Bank and UNHCR Joint Data Center on Forced Displacement. Introduction 7 communities to design a better mix of approaches that could help the government in designing livelihood opportunities for these communities. Due to differences in scope, sampling design, and methodology, results based on the SPS cannot be directly compared with those of SESRE. Box 1.1 summarizes the similarities and differences between SPS 2017 and SESRE 2023. The Skills Profile Survey (SPS), conducted in 2017, is a household survey focused on collecting data on refugees from South Sudan, Somali, Eritrea, and Sudan living in camps in Ethiopia, as well as from host communities. The sample frame for the survey was derived from the list of all refugee camps, sites, and locations provided by UNHCR-Ethiopia as of January 2017, covering the four main regions that host refugees: Tigray, Afar, Gambella, Benishangul-Gumuz, and Somali. The SPS specifically
Wages: the earnings measure we use is the response to the question “ how much did you earn from your main job activity during the last month? ” In the LFS 2011 there is further information on how much of that income was irregular, for example a bonus payment, but the LFS 2014 no longer provides that breakdown. There is also a measure of the “ number of hours per week worked in the main job ” (both usual and total hours), which can be used to construct hourly wages. Since the hours worked measure does not correspond exactly to the earnings measure and introduces additional measurement error, our preferred wage measure is the monthly wage. We exclude wage observations were respondents report having usual working hours of less than 14 or more than 84 hours per week.
I expect citizens who perceive tax collection to be the responsibility of non-state actors to be less likely to be willing to pay taxes to the state ’ s tax department than citizens who perceive tax collection to be the responsibility of the state. Perceptions of the eﬀectiveness of donor and non-state actor provision of services are assessed using the following items. Respondents were probed on how much they believe the following non-state actors and donors do to help their country: the United Nations; international donors and NGOs; international businesses and investors; China; and the United States. 9 I also include Freedom House ’ s political liberties and civil rights ratings for the 19 countries in the sample. These two variables should capture the relative equality of inﬂuence in making policy. They indicate whether citizens are able to express their voice without fear of repression and whether elections are free and fair. Neither of these variables are signiﬁcant at the p < 0. 05 level. 14
**Component 4: Project Management, Monitoring, and Evaluation (US$3.8 million)**

This component will finance the operating costs of the Coordination Unit and support the rollout of the Management Information System (MIS) across all twelve participating district offices. The MIS will track beneficiary registration, service delivery milestones, and grievance redress outcomes, providing real-time dashboards for national coordinators. Quarterly progress reports generated from the MIS will form the basis of implementation support missions. The component also covers the cost of the endline evaluation, contracted to an independent firm, and capacity-building workshops for district-level M&E officers.
include the rice price — which appears with the wrong sign but is only marginally signiﬁcant — and elevation and population density — which are no longer signiﬁcant. Comparing Tables 7 and 5, we ﬁnd that in the smaller NLSS 2002 / 3 dataset none of the anticipated consumption variables is statistically signiﬁcant. Other results are as before. 4. 4 Magnitude To assess the relative magnitude of our results, we multiply coeﬃcients estimated in Tables 4 and 5 by the standard deviation of their respective regressors. We then average over the various regressions reported in Tables 4 and 5. Calculations are summarized in Table 8. The larger the value, the more inﬂuence the regressor has on the choice of a destination district. We see that the most important regressors in terms of magnitude are travel time to the near- est road, elevation, language similarity, and the price of rice. Consumption variables have an eﬀect on migration destination that is smaller in magnitude: a one standard deviation increase in anticipated relative consumption, for instance, has an eﬀect on destination that corresponds to a third of the eﬀect of a one standard deviation in elevation — and one-sixth of a one stan- dard deviation in distance from the nearest road. Income variables have a negligible eﬀect on migration decisions.
the Refugee Proclamation of 2019, while encampment undermines achieving the goals set out in the Proclamation. The GoE pledged to transform camps into settlements and facilitate mobility for refugees to take advantage of opportunities in the labor market and increase work authorization to allow for the formalization of working conditions. Humanitarian and development partners should strongly support this pledge by swiftly investing in and accelerating inclusive approaches through the engagement of line ministries. Yet, large gaps in financing remain to fill the needs of refugees and host communities. Better coordination and engaging line ministries can achieve better outcomes for refugees and their hosts. Implementing an overarching coordination mechanism across line ministries to track investments and progress on refugee inclusion could leverage the existing humanitarian resources to deliver the first mile investment into inclusive development approaches, led by development actors. Improved communication, collaboration, and connections between RRS and line ministries could support initiatives seeking to mainstream refugees into existing governance structures. Encouraging these collaborative efforts of departments and agencies of the GoE can achieve a successful implementation of development solutions. Efforts to improve the coverage, accuracy, reliability, quality, and comparability of data can provide the analytical underpinning for policy decisions. Better
5 implemented in six areas: Bamako, the regional capitals of Gao, Timbuktu, and Kidal as well as one refugee camp in Mauritania and one in Niger. Bamako was selected because it is home to a large number of IDPs. The refugee camps were selected to obtain a sample of refugees. Returnees were identified in the regional capitals of Timbuktu, Gao and Kidal where the phone network was (still) functional. The approach to selecting respondents differed by location and depended on the availability of pre-existing population information.  Bamako: Listing information of all households with IDPs was obtained from the International Organization for Migration (IOM). Based on this data 10 districts were selected and in each district 10 households were randomly identified.  Gao, Timbuktu and Kidal: No listing data was available and the cities were divided into different sectors. The enumerator was assigned a starting point in a sector, a direction (North, South, East, West) and based on the code of the day 9 the enumerator selected the first household. If the code of the day was 4, the enumerator would choose the 5th house to conduct the first interview. No more than 6 houses were to be interviewed from one starting point.
Protection monitoring interviews conducted in the three northern border districts revealed persistent gaps in access to civil documentation, with 42 percent of respondents reporting that at least one household member lacked a valid national identity document. Barriers cited most frequently included costs of administrative fees, distance to documentation offices, and limited awareness of entitlements. Protection monitoring interviews were conducted with 1,840 households across 18 communities between January and April, with samples drawn using systematic random sampling from updated household registration lists.
cereal production (in kilograms) per residential [household member reported by the] household head in the immediate post harvest [period as the measure of agricultural] production.

index. [8] Here, we construct a food variety score (FVS) to combine the diversity of a


person's diet into a single index (Hatloy, _et al.,_ 1998). The FVS is based on the number


of different food items eaten over a registration period. We evaluate two versions: 1) a

associated with food shortages into a numerical index. Our third alternative indicator is


an index of these 'coping strategies'. We asked the most knowledgeable woman within

1996 and the World Bank's forthcoming World Development Report on Poverty 2000/1, the demand for such comprehensive measures is more urgent than ever.