ai4data/datause-dataset-rechunked huggingface dataset:
While most existing theories of madrassa enrollment are based on household attributes (for instance, a preference for religious schooling or the household ’ s access to other schooling options) the data show that among households with at least one child enrolled in a madrassa, 75 percent send their second (and / or third) child to a public or private school or both. Widely promoted theories simply do not explain this substantial variation within households. 1 Corresponding Author: Tahir Andrabi (tandrabi @ pomona. edu). This study would not have been possible without the enthusiasm and continuous support we received from Tara Vishwanath. Charles Griffin first encouraged us to look at the data. We thank Veena Das, Shehla Andrabi, Sehr Jalal, Ritva Reinikka and Carolina Sánchez for their encouragement and to Hedy Sladovich for her excellent editorial suggestions. The paper has also benefited from comments by Ismail Radwan, Naveeda Khan, Shahzad Sharjeel and Shanta Devarajan. The research department of the World Bank provided funding for this study through the Knowledge for Change trust fund. The findings, interpretations and conclusions expressed in this paper are those of the authors and do not necessarily represent the views of the World Bank, its Executive Directors, or the governments they represent. Working papers describe research in progress by the authors and are published to elicit comments and to further debate. Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized Public Disclosure Authorized WPS3521
14 % of respondents think that a **go and see visit** prior to the return would be useful. From
those who responded positively, 63 % would like to send community leaders for the go and
see visit, while remaining 37 % male family members.

9 % were aware about some kind of information campaign on the return. It is to be noted
that at the time of the interviewed conducted, the information campaign on return has not
yet been officially launched.

In 64 % of interviewed families, the response on **who decides on the return** was political
administration **.** This percentage is relatively high compared to other return intention
surveys conducted by protection cluster. In 23 % it is the community elders who reportedly
make the decision on return, followed by family members in 13 % of cases (which is usually
the highest category reported). Only 49 % of respondents felt that they **participate in the**

**decision making process** on the return.

**Despite the fact that IDPs wish to return to their area of origin, 26 % indicated that not**
integrate into the surrounding community and labor market. Among Eritreans in Afar and Amhara, the share working is 43 percent and 9 percent, respectively. Among workers, Eritreans in Amhara are three times as likely to work for NGOs or RRS, and very few work outside the camp. Box 3.1: Eritrean refugee sample in the SESRE Jobs and Livelihoods 27 Ethiopia relies on a camp-based model, with 88 percent of refugees hosted in camps. As outlined, in-camp refugees generally do not have work permits or business licenses and largely depend on work inside the camp or informal work outside the camp. On the other hand, the GoE introduced an out-of- camp policy (OCP)39 in 2010 that provides refugees the opportunities to live in Addis Ababa and different non-camp locations of their choice. Roughly 71,000 Eritreans were under the OCP regime as of 2022, with over 90 percent living in Addis Ababa. In practice, most of those approved for the OCP have family and friends in Ethiopia who support them with remittances—fewer than 1,500 OCP work permits were issued by 2022. The permit allows refugees to freely move and establish residence in all areas of the country except restricted areas. OCP refugees
41 Note: Refugee data are from the UNHCR statistical population online dataset, accessed in September 2014. Refugee data from 2007 to 2013 include people in refugee ‐ like situations (see note, Figure 1). IDP data from 1990 to 2008 are aggregated based on Center for Systematic Peace (http: / / www. systemicpeace. org /). UNHCR assisted ‐ IDP are compiled based on several UNHCR (1995, 1996, 2007, 2008, 2009, 2010, 2011, 2012, 2013, and 2014) reports. UNHCR ‐ assisted IDPs are only IDPs who are protected / assisted by UNHCR. These are also not necessarily representative of the entire IDP population in a given country. Many of the world's IDP situations are not covered by UNHCR and are thus not reflected. Since some adjustments could take place over time, we always use the figures from the last available report.
positive long-term integration as it limits long-term scarring effects, such as long- term unemployment or inactivity (Fasani et al., 2022; Slotwinski et al., 2019). Refugee employment after arrival depends on policies in the host country concerning work permits and mobility (Fuller, 2015; World Bank, 2017). On the other hand, arrival of refugees may have a complex range of positive and negative effects on local labor markets in host communities, including on sectoral employment, wages, and prices. Studies in Ethiopia show that 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Addis Refugees Camp Refugees Lack of work/business opportunities High cost of living Poor services or institutional support Lack of freedom or mobility Lack of community/family networks Insecurity or discrimination Figure 3.1: Top 3 difficulties with being a refugee Source: World Bank Staff based on SESRE 2023. Jobs and Livelihoods 26 refugees may decrease employment among hosts in rural areas (Ayenew, 2021), while other studies find no effect on employment and increases in consumption (von der Goltz, 2023) and product diversification and livestock sales (Walelign et al., 2022) as refugees increase consumer demand for agricultural products, with variations in effects across the different regions of Ethiopia. Most refugees in Ethiopia do
The sample households are located within varying distance from the nearest refugee camp (approx. 67 to 76, 665 meters) (see Figure 3). 12DRDIP aims to improve access to basic social services, expand economic opportunities, and enhance environmental management for communities hosting refugees through providing funding for community driven projects.
13 Second, each individual in the JLMPS restricted sample is matched to the 2010 Jordanian school census. The matching process determines for each individual the number of sex- appropriate public basic and secondary schools per 1, 000 individuals available in the individual ’ s subdistrict of birth when the individual was of age to accede to this educational level (six years of age for the basic level and 15 years of age for the secondary level). 7 A school is considered sex-appropriate for a female if it is a girls ’ or a mixed school and for a male if it is a boys ’ or mixed school. The empirical analysis is also performed by entering boys ’, girls ’, and mixed schools separately. 8 Measuring the local supply of public schools at the subdistrict of birth of the individual (i. e., the child) mitigates potential endogeneity originating from parents who had a higher taste for schooling moving to subdistricts where public schooling was more abundant when their child was of school age, although it is not possible to rule out that parents might have moved across subdistricts prior to the birth of their child.
Throughout the war, HLP rights violations has been one
of the main impacts, particularly related to

**secondary/unauthorized occupation, destruction,**

**and confiscation** . Absence of ownership documents
(either due to loss or verbal agreements) increased the
exposure to house, land, and property related
violations. In the case of youth, these risks are
enhanced, due to **lack of procedures to secure tenure**

**for youth when parents have died** .

Occupied I don't
know

**What is the status if your familys property?**

**54%**

Abandoned Destroyed Rented Confiscated

Family separation, lack of access to legal services,
informality on tenure, ethnic background,
discrimination, are some of the existing drivers for **additional HLP violations for youth** . The percentage of destroyed
properties documented by the survey raised additional concerns related to future restitution of HLP rights for young
people and the need to safeguarding these documents for transitional justice purposes.

Youth participating in the FDGs also mentioned:
tanker water. 36 Improved bathing refers private or shared bathtub, shower, separate room for bathing. 0 20 40 60 80 100 120 Hosts Refugees Hosts Refugees Hosts Refugees In camp Addis Ababa Total Overcrowded Improved wall Improved roof Percent Figure 2.21: Housing quality Source: World Bank Staff based on SESRE 2023. 0 20 40 60 80 100 Hosts Refugees Hosts Refugees Hosts Refugees In camp Addis Ababa Total Owned Rented UN/NGO temporary UN/NGO permanent Other Percent Figure 2.20: Dwelling type Source: World Bank Staff based on SESRE 2023. Sociodemographic Profile 23 Refugees’ access to improved sanitation facilities is similar to hosts. Refugees’ access to improved toilet facilities37 is the same as hosts, or even better in some cases. Eritrean, Somali, and OCP refugees and their hosts have similar toilet facilities. Even though the percentage of households with access to improved toilet facilities is lower among South Sudanese refugees than other refugees, it is higher compared to their hosts. Moreover, refugees have higher access to improved waste disposal methods38 than hosts. Both refugee and host households have low access to electricity, except for hosts of Eritrean refugees. Hosts around Eritrean refugees have better access to electricity (meter private or shared) for
Indeed, despite the recent literature rejecting the conflictive impact of refugees in hosting areas (Zhou and Shaver, 2021), the magnitude of our coefficients might be explained by the confounding presence of refugees. Columns (5) and (6) further introduce climatic controls. Column (6) corresponds to Equation 1 and refers to our benchmark specification. Columns (1) and (2) show that without incorporating the changes in ethnic diversity induced by refugees we would not be able to identify a relationship between diversity and violent conflicts. In column (3), the revised refugee fractionalization index has a negative and significant coefficient, while the revised refugee polarization index has a positive and significant effect on the incidence of violent conflicts. In columns (2), (4), and (6), our coefficients of interest are of the same order of magnitude when the number of refugees is controlled for. Our results are not altered by incorporating rainfall and temperature anomalies (columns (5) and (6)), but the estimates become slightly more precise. 21
natural log of a country ’ s population size and government consumption as a share of GDP; the latter is the most widespread measure of government size (Adsera and Boix, 2002; Alesina and Wacziarg, 1998; Rodrik, 1998). Tax compliance is also related to the government ’ s ability to eﬀectively detect and punish tax avoiders, tax evaders, and tax arrears. Although an imperfect measure of states ’ deterrent capacity, Afrobarometer includes two survey questions on perceptions of government enforcement and monitoring capacities. One question probes respondents on how often ordinary people who break the law go unpunished. The other probes respondents on how often oﬃcials who commit crimes go unpunished. This latter question is also a measure of perceived government fairness- the extent to which a government implements the law evenly across all social groups. 6. 2. 5 Procedural Justice I include two indicators of procedural justice. The ﬁrst probes respondents on how often people are treated unequally under the law. The next taps citizens ’ perceptions of the government ’ s treatment of their ethnic group. Speciﬁcally, respondents were asked how often their ethnic group is treated unfairly by their government. 9 6. 2. 6 Donor and Non-State Actor Provision of Services I include a measure of who citizens believe is responsible for collecting income taxes.
13 Commission for Reception, Truth and Reconciliation (CAVR). 7 This information has been collected from deponents to the Commission ‘ s statement-taking process. 8 We make use of data on the number of killings that occurred during the war in order to derive patterns and variation of violence in Timor Leste over time and across space. We use this data to identify districts and years that experienced high and low violence-intensity, both at the start of the occupation and following the withdrawal of Indonesian troops in 1999. This allows us to estimate both the impact of the first years of the conflict and the impact of the last wave of violence in 1999. 4. 1. Identification strategy: The impact of violence on school attendance in 2001 We first investigate the short-term impact of the 1999 violence. The empirical questions being addressed are: (i) whether the violence in 1999 imperiled school attendance9 and school grade deficit, and (ii) whether different channels of exposure to conflict – displacement and house destruction – affected boys and girls and different age groups differently. 4. 1. 1. Primary school attendance and grade deficit rates in 2001 We make use of information in TLSS 2001 collected at the individual and household levels on displacement and house destruction to identify conflict-affected individuals.
years) ......... 103 Figure D.12: Average annual per capita health expenditure ....................... 103 Figure D.13: Types of disability..................................................................... 104 Figure D.14: Rent expenditure (Refugees and hosts in Addis Ababa) ........ 104 Figure D.15: Hand washing facility................................................................. 104 Figure D.16: Top 3 difficulties with being a refugee by survey domains ..... 108 Figure D.17: Work status by survey domains ������������������������������������������������ 108 Figure D.18: Type of work by survey domains ���������������������������������������������� 108 Figure D.19: Occupation by survey domains ��������������
�������������������������� 108 Figure D.19: Occupation by survey domains ������������������������������������������������� 108 Figure D.20: Work location by survey domains ��������������������������������������������� 108 Figure D.21: Hours per week by survey domains ����������������������������������������� 108 Figure D.22: Hourly earnings by survey domains ����������������������������������������� 109 Figure D.23: Household owns crops ............................................................. 109 Figure D.24: Household owns livestock......................................................... 109 Figure
................................................ 109 Figure D.25: Total value of livestock ............................................................ 109 Figure D.26: Value per tropical livestock unit ������������������������������������������������ 109 Figure D.27: Household has non-farm business ����������������������������������������� 109 Figure D.28: Value of productive assets in households with business ........ 110 Figure D.29: Primary source of income pre-post migration by survey domains......................................................................... 110 Figure D.30: Youth work status by survey domains ����������������������������������
.... 110 Figure D.30: Youth work status by survey domains �������������������������������������� 110 Figure D.31: In-camp refugee locations by ecological Zone ........................ 115 Figure D.32: Refugee’s labor market performance ��������������������������������������� 115 Figure D.33: Economic sector........................................................................
Therefore, the final sample size consisted of 759 youth, of which 473 treatment and 286 comparison. Detailed baseline data were collected through face-to-face interviews from July to September 2015 prior to implementation. The actual implementation varied between projects and ranged between the second half of August and end of December 2015. Sampled youth from both selected and non- selected NGOs were invited to fill out a questionnaire with detailed information on volunteers ’ socio-economic backgrounds, education levels, interests and attitudes towards volunteering, employment, soft skills, as well as social cohesion values. Follow-up data were collected between November 2016 and March 2017, approximately one year following the start of implementation, through phone and face-to-face interviews. The questionnaire contained the same modules asked and collected at baseline. Despite the high 8 Proposals were ranked based on four main selection criteria: institutional appraisal (25 points), technical appraisal (40 points), project impact (25 points), and financial appraisal (10 points). There was also a fifth criterion related to sustainability of volunteering activities, which was assigned a bonus score (5 points).
The only question included in the WVS related to attitudes towards immigrants - and available   for a sufficient number of survey years - is: _On this list are various groups of people.

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

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Deaton, Angus. The analysis of household surveys: a microeconometric approach to

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

group as the majority (ESS). _Proimmigdiff_ is the average pop. share (%) who would like many or some immigrants of a _different_
throughout the day prior to the survey day. We develop our own questions around self- worth rather than employing the more standard Rosenberg Self-Esteem Scale, which we found inappropriate given the Rohingya ’ s recent experiences. Speciﬁcally, we construct an index of self-worth from two questions designed to elicit respondents ’ beliefs about how they contribute to their family and community. Finally, we adapt the Cantril Self-Anchoring Striving Scale (Cantril, 1965) to measure how stable respondents feel in their present lives and in the future. We additionally examine the impacts of each treatment on physical health, cognitive function, economic decision making, time-use, and consumption. We capture respondents ’ sense of physical health by asking how many days they have fallen sick in the past thirty days and cognitive function by employing a digit-span memory test and a series of basic arithmetic problems. We explore economic decision making along two dimensions: incentivized time preferences (Andreoni and Sprenger, 2012; Gin ´ e et al., 2018) and incentivized risk preferences (Holt and Laury, 2002).
**SOUTH SUDAN** | October 2023

#### **CONTEXT**

**YOUNG POPULATION AND PREVALENCE OF DISABILITIES**

South Sudan is a young nation with an average age of 18.8 years. In the absence of an updated census, it is estimated that 1.2
million people, or 16% of the population have disabilities. The most commonly identified disabilities include visual
impairments, hearing impairments, and physical disabilities. [iv] Additionally, the proportion of older people in South Sudan is on
the rise, accounting for 5.1% of the population in 2016, an increase from 3.9% in 2008, and an indication that the number is
growing each year. [v] Notably, most older people in South Sudan reside in impoverished rural areas, where they play a crucial
role as caregivers for children whose parents have often perished in the conflict.

The country has a troubled history marked by decades of armed conflict, leading to displacement, economic instability, and
increased climate hazards such as flooding and droughts. These factors have further weakened an already fragile state and
limited governance capacity, disproportionately impacting older individuals and those with disabilities.
Despite notable disparities in the characteristics of our sample compared to the VenRePS and RAMV samples, understanding the interaction of these attributes within a frame- work of self-selection among migrants into Medellin is challenging. Moreover, it is cru- cial to note two primary distinctions between our survey and the VenRePS and RAMV surveys. Firstly, the inherent differences in the sampling frames of each survey stem from their distinct measurement objectives. Second, both surveys were conducted at different times compared to our survey. The RAMV survey was undertaken in 2018 in response 10See Ib ´ a ˜ nez et al. (2022) for specific survey and sampling details. 11Refer to Ib ´ a ˜ nez et al. (2022) for further details. 12Since the VenRePS and RAMV surveys lack information regarding children and adolescents within households, our analysis concentrates only on the household and household head characteristics that are available in all three surveys. 20
14 3. Refugees as Agents of Their Own Destiny 3. 1 The Composition of Africa ’ s Refugee Population and Its Consequences One of the first elements that catch the eye in Figure 6 is the difference in the composition of the refugee population in Africa compared to the rest of the world. The share of children and women among refugees is higher in Africa than elsewhere, in particular East and West Africa stand out here. This is, at least partly, a consequence of Africa ’ s younger, general population, but other forces could be at work as well, e. g. higher mortality of adult males in Africa or adult males staying behind or being separated from the rest of the household. It does mean however that, relative to other areas, more attention should be going to the needs and capacities of women and children in Africa. This means, for example, adaption of and increased supply of schooling and health services. Figure 6. The composition of refugees by age and gender, 2013 Source: Note: UNHCR statistics (UNHCR 2014). Asia excludes Australia, Japan and New Zealand. Americas exclude Canada and the United States. These percentages have been calculated by country when demographic data are available for at least 30 % of the total.
(Dercon et al 2005; Woldehanna et al 2008)—market shocks related to rising food prices, food shortage, and health shocks appear to be most prevalent (Figure 5.11). High food prices drive the market shocks. Food shortage seems to represent a crucial economic shock among refugees—roughly 31 percent of in-camp refugees are affected by food shortage—but not for their host communities. 4.0 2.1 2.9 8.1 3.4 7.0 In Camp Addis Ababa Total Hosts Refugees Figure 5.9: Food insecurity scale for refugees and hosts Source: World Bank Staff based on SESRE 2023. 44 Food insecurity experience is measured based on a scale that ranges between 0 and 10 and calculated by adding household’s experience related to the following events in the past year: (i) worried about having enough food, (ii) unable to eat healthy/nutrition food, (iii) only ate a few kinds of food, (iv) had to skip a meal, (v) adults ate less, (vi) ran out of food, (vii) adults were hungry but did not eat, (viii) went without eating for a whole day, (ix) restricted consumption so kids could eat, and (x) borrowed food or relied on friend/relative for help. 7.0 8.4 7.8 6.0 8.2 6.5 In Camp Addis Ababa Total Hosts