ai4data/datause-dataset-rechunked huggingface dataset:
Poverty remains widespread and social indicators are well below the average for Sub-Saharan Africa. Chad is ranked 173 among the 177 countries surveyed in the 2006 UNDP Human Development Report. The incidence of poverty (defined as the proportion of households with annual spending below what is necessary to meet minimal needs) is estimated at 55 percent according to a 2003 household survey; an estimated four-fifths of the population of about 8. 8 million is living on less than a dollar a day3. Of the population over 15 years old, more than 73 percent (and 76 percent of women) are illiterate. Access to potable water has improved over past years, but is still limited to one out of three people in 2005. Less than two percent of the population has access to electricity and only 1021 kilometers of roads has been paved on a surface area of over 1. 2 million square kilometers. As already mentioned, Chad has recently become oil producing country; however, the economy remains largely agricultural and pastoral. About 80 percent of the country ’ s population lives in rural areas and continue to make their living4 from agriculture and livestock. Cotton is the principal cash crop, employing about 300, 000 families.
The second source is Giri et al. (2011), who use 1997 to 2000 Landsat data, together with supervised and unsupervised digital image classification, to construct a 30 square meter resolution map of the global distribution of mangrove.

4Nordhaus (2006) considers areas with elevation less than 8 meters as vulnerable to storm surge. We
use a less stringent definition because Shuttle Radar Topography Mission (SRTM) elevation estimates
below 10 meters are not considered reliable (McGranahan et al., 2007). We thank Eric Strobl for
providing us with GIS boundaries for global coastal lowlands constructed from STRM data.


7



<!-- PAGE 10 -->
shortest path to the coast. We find that there are 3,853 cells (49% of cells in storm surge

We measure local economic activity using remote sensing data on nightlights; potential hurricane de struction using a damage index derived from a wind field model calibrated for Central America; and mangrove protection by calculating the cumulative width of mangroves along the closest path to the coast.
**SOUTH SUDAN** | October 2023

- Adapt modalities of GBV services to address and response to needs of persons with disabilities and GBV actors know how
to access support services, for example for interpretation. Local OPDs, in particular women led OPDs, are trained in how
to safely identify and refer GBV survivors.

- Ensure that Child Safeguarding Policy training is systematically provided to as many humanitarian workers as possible especially those in close contact with children - and communities to ensuring that all humanitarian actions are properly
implemented to protect all children including children with disabilities from the increasing deliberate or unintentional acts
of abuse and exploitation registered in the last quarter.

- Ensure the meaningful participation of older women and persons with disabilities in awareness raising campaigns and
other community-based activities.

- Adopt strategies to prevent and address discrimination against older women and support the full inclusion of women from
all age groups in empowerment activities and interventions.

- Continue collection of GBV data that is age and disability disaggregated to ensure that data is inclusive of older women
with and without disabilities and use the data to inform responses.
Figure 4: Refugees and Asylum-Seekers by Migratory Path 1951 – 2015 Source: UNHCR Statistical Online Population Database, UNHCR Global Trends 2015
This paper analyzes data from the initial wave of VenRePS-Kids, conducted from Oc- tober to December 2022, to outline key demographics and stylized facts about forcibly displaced children and adolescents. Initially, we examine the human development dis- parities of forcibly displaced Venezuelan children and adolescents in comparison to their Colombian counterparts. Our approach to human development is broad, covering physi- cal, cognitive, socio-emotional, and mental health aspects. Additionally, we complement our analysis by exploring differences in food security, social cohesion, and the economic status of parents. Although our analysis is descriptive, it represents a crucial initial step 2Venezuelan households are defined as those where both parents and their children have a Venezuelan nationality. Colombian households are composed of Colombian citizens only. 3
**awareness sessions (90%), community networks (53%) protection analysis (44%). The** main gap remains
on specific strategies to mitigate impacts on **the safety, evacuation routes and well-being** .
 According to the survey findings, a significant majority of respondents (77%) indicated **that there are**

**currently no organizations**, institutions, agencies, or entities offering tailored and specialized activities or
services specifically designed for youth in northwest Syria.

 79% of the respondents believe some groups within youth are facing **disproportionate impacts** :

Young parents, the only segment of this
population groups with some level of access to
services and programs, was not identified by
respondents as one of the groups at heightened
risk. The attribution of 15% to **young people**

**belonging to minorities** is relevant finding,
considering that, it is a high percentage for a
small group. **IDPs** as the second group exposed
to higher impact represents a need to better
understand the specificities of the risks faced by
them; also, relevant to see that adolescent men
seem to face increased risks than adolescent
women. Absence of data on the particularities
of these risks faced by both genders limits the
accuracy of the programmatic response.

Those that belong to minorities
- Significant number of new IDPs (141,775 as of June 2017) due to the recurrent military clashes,
decrease of 25% compared to 2016;

- Increase number of refugee returnees as of June 2017 compared to the previous year due to
shrinking protection space in Pakistan and Iran;

- Increased trends in short term displacement due to the lack of humanitarian access, with
people often returning to their place of origin after the engagement has finished (ex. Situation
in Kunduz in 2016: 118,166 people were displaced from Kunduz in September-October, and
69,916 Kunduz IDPs that were displaced within the Northern and North-Eastern provinces
returned to their places of origin within several weeks – a month period);

- Pattern of secondary and multiple displacement in rural and urban centers (according to the
REACH study on prolonged displacement, some 23% IDPs were displaced twice or more [1] );

- Pattern of return in unsafe areas due to limited livelihood opportunities in urban centers and
the need to tend to crops [2] ;

- Pattern of local integration in urban center of protracted IDPs due to lack of security in area
of origin;
In a 2004 note to its Executive Com- mittee, UNHCR established the average at 17 years at the end of 2003 (Executive Committee of the High Commissioner ’ s Programme 2004). This number has been widely quoted by media, ac- tivists, humanitarian agencies, and development institutions (Milner 2014; United Nations 2016; UNHCR 2015). The rest of the paper is organized as follows. Section 1 gives some deﬁnitions and background information on the refugee population. In section 2, we provide some summary statistics from our main source of data, the UNHCR Population Statistics Database. Section 3 describes the method followed to construct duration statistics and presents a few stylized facts. The results of our anal- ysis are presented in section 4. Section 5 concludes. 1 Background: Deﬁnitions and Data Under the terms of the 1951 Convention Relating to the Status of Refugees – henceforth the Convention – later amended by the 1967 Protocol, a refugee is a person, who “ owing to a well-founded fear of being persecuted for reasons of race, religion, nationality, membership of a particular social group or political opinion, is outside the country of his nationality, and is unable to, or owing to such fear, is unwilling to avail himself of the protection of that country. ” Data on refugees and asylum seekers are collected by individual countries, international orga- 3
Border crossings The registration of people crossing internationals borders is conducted in many countries, and in some cases these data are used to estimate migration flows. Identifying refugees among people crossing borders is a significant challenge, particularly if individuals decide not to apply for asylum or refugee status (UNSD 2014). Additional problems associated with the collection of data on border crossings include: (a) difficulties distinguishing migrants from other people crossing a border, such as tourists, commuters, traders and truck drivers; (b) lack of capacity of many border posts and officials to handle large migration flows; (c) less scrutiny and diligence of emigration flows compared with immigration flow; and (d) lack of tight controls at most borders and the high incidence of undocumented or irregular crossings (UNSD 2014). Administrative records and registers Many countries have administrative records or registers of immigrants that could generate statistics on asylum-seekers and refugees. In particular, data on residence permits issued to refugees or asylum- seekers could be used to generate statistics on both flows and stocks of refugees. 79 For example, Eurostat collects and disseminates data on residence permits granted to those with refugee status and subsidiary protection (UNSD 2014).
It is diﬃcult to draw causal inference from observational data. This study is no exception. The results presented here are nevertheless suﬃciently suggestive to cast doubt on the theory that the choice of migration destination is driven primarily by income diﬀerentials. Other factors seem to play a strong — and probably more important — role. References 1. Adams, Richard, Remittances, Investment, and Rural Asset Accumulation in Pakistan, 30
The LFS employment module follows ILO definitions: a person is classified as employed if they performed at least one hour of paid or unpaid work during the reference week, or if they were temporarily absent from their regular job. The LFS therefore captures both formal wage employment and informal self-employment in subsistence agriculture, a distinction that is important for understanding the full scope of labor market adjustment to the economic shocks we study. The LFS does not collect wage information for self-employed individuals, which limits our ability to estimate wage effects for that subgroup.
challenge in some cases, notably among South Sudanese, refugees generally believe they are culturally similar to their hosts. This rate averages 78 percent for all refugees. It is lowest in South Sudanese camps at 68 percent and highest in Somali camps at 87 percent. Many of these refugees who say they are culturally similar to their hosts respond that they have no Ethiopian friends and that social interactions with Ethiopians are complex. 0 10 20 30 40 50 60 70 80 90 100 Eritrean Somali South Sudanese Addis Ababa All Refugees Figure 7.16: Share of refugees who agree they are “culturally similar to hosts” Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 Age Under 30 Age 30-44 Age 45-64 Age Over 64 Female Male Figure 7.18: Share or refugees engaged in a community representative body by demographic group Source: World Bank Staff based on SESRE 2023. 0 10 20 30 40 50 60 70 80 Eritrean Somali South Sudanese Addis Ababa All Refugees Figure 7.17: Share or refugees involved in a community representative body Source: World Bank Staff based on SESRE 2023. Markets and Opportunities 71 Low refugee social integration is not
Africa. The Afro Barometer Working Papers No. 200. Woldehanna, T., Hoddinott, J., and Dercon, S. (2008). Poverty and Inequality in Ethiopia:1995/96 – 2004/05. May. World Bank (2017). Forcibly Displaced: Toward a Development Approach Supporting Refugees, the Internally Displaced, and Their Hosts. Washington, D.C: World Bank. https://doi.org/10.1596/978-1-4648-0938-5. World Bank. (2019). Informing the Refugee Policy Response in Uganda. Results from the Uganda Refugee and Host Communities 2018 Household Survey. World Bank. (2019b). Better Opportunities for All: Vietnam Poverty and Shared Prosperity Update Report. Washington DC: World Bank Group. World Bank (2020). Ethiopia Regional Poverty Report: Promoting Equitable Growth for All Regions. Washington, D.C.: World Bank Group. World Bank (2020b). Ethiopia Poverty Assessment: Harnessing Continued Growth for Accelerated Poverty Reduction. Washington, D.C.: World Bank Group. World Bank (2023). World Development Report 2023: Migrants, Refugees, and Societies. Washington, D.C: World Bank Group. https://doi:10.1596/978-1-4648-1941-4 World Bank. (2023a). Social Cohesion and Forced Displacement: A Synthesis of New Research. World Bank. (2023b). Welfare in Forcibly Displaced Populations: From Measuring Outcomes to Building Capabilities. Leveraging Harmonized Data to Improve Welfare among Forcibly Displaced Populations and their Hosts: A Technical Brief Series. World Bank. (2023c). Do Legal Restrictions Affect Refugees’ Labor Market and Education Outcomes? Evidence from Harmonized Data
0.10, ** p < 0.05, *** p < 0.01 Annexes 114 The regression specification used is: where is the vector of control variables that include demographic characteristics (sex of household head, age of household head, family size, years of schooling completed by the head), assets and wealth (mobile phone ownership, livestock ownership in tropical livestock units, land ownership, bank account, non-farm business ownership, electricity access), employment (share of employed members), resource and market access (market accessibility and proximity to resource hubs), and shocks (health, market, employment, drought, political). The regression also controls for survey domain and survey time (month) fixed effects to account for the effects of location and time on welfare. Table D.13: Determinants of welfare for in-camp refugees (1) In-camp refugees Head years since refugee status (from 2022) 0.00 (0.00) Head wants to go back to own/parents 0.02 (0.03) Ration change -0.43*** (0.10) Head: has any relative in own/parents’ COB 0.05 (0.04) HH received humanitarian food aid in past 12 months -0.00 (0.04) Distance to woreda capital (log) -0.10*** (0.01) Distance to border (log) -0.03 (0.02) Medium market accessibility -0.02 (0.06) High market accessibility 0.29*** (0.05) Constant 11.10*** (0.34) Survey domain Yes Survey time Yes Observations 1,266 Source:
to the Venezuelan migratory crisis, whereas the VenRepPS survey was conducted during the pandemic in 2020. These temporal inconsistencies result in varying sample composi- tions across surveys, diverging from the landscape we observe in 2022. Notably, forced migrants in the VenReps Kids survey migrated during the crisis but have since remained in the country for several years, potentially leading to disparities in household integration outcomes. IV GENERAL DESCRIPTIVE STATISTICS IV. A Key characteristics of adults Table 2 provides descriptive statistics for the adults in our study, encompassing the pri- mary caregiver, mother and father (if residing with the child), and the individual finan- cially responsible for the child (should they be different from the aforementioned per- sons). Typically, the roles of primary caregiver and financial provider are fulfilled by either the mother or the father. The table is organized into three panels for clarity: Panel A details key individual characteristics, Panel B outlines adults ’ access to services, and Panel C focuses on labor market characteristics. Within the table, columns (1) and (2) present average values for adults from Colombia and Venezuela, respectively, while the final column displays the results of mean difference tests between these two groups, with standard errors noted in brackets.
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
recently introduced the first version of their Global Internal Displacement Database (GIDD) that allows users to explore, filter and sort IDMC ’ s data to produce graphs and tables, and export underlying data. 102 Such platforms need to incorporate safeguards to protect the privacy and confidentiality of individuals ’ data. UNHCR and Statistics Norway are currently leading an initiative to improve forced displacement statistics with the participation of national statistical agencies. This process began with the presentation of the “ Report on Statistics on Refugees and IDPs ” at the 46th session of the UN Statistical Commission in March 2015, 103 followed by an international conference in Turkey in October 2015. 104 The conference set in motion a process for national statistical agencies to collaborate to develop a set of recommendations that both countries and international organizations can use to improve data collection, reporting, data disaggregation, and overall quality, including the preparation of International Recommendations for Refugee Statistics (IRRS). Progress on this agenda was discussed at the 47th session of UNSD held in New York in March 2016, where it was recommended that the expert group should also include IDPs in its scope of work (UNSD 2016). 105 The current initiative is focused on refugees, asylum-seekers and IDPs but would ideally be extended to host communities and returnees.
Consequently, they may fear detection by authorities when asked to respond to surveys or participate in public initiatives. 1 Furthermore, collective repre- sentative and longitudinal data on forcibly displaced migrants, a population with high mobility rates, is difficult and costly (Ib ´ a ˜ nez et al. 2024). This complexity is compounded when focusing on children and adolescents, given the need for enumerators to receive specific training to interact with such a vulnerable demographic and for migrant parents to authorize their children ’ s involvement despite prevailing distrust issues. To address this knowledge gap, we launched the Venezuelan Refugee Panel Study for Kids (VenRePs-Kids) in Medell ´ ın, Colombia. VenRePs-Kids is a longitudinal study repre- sentative of forcibly displaced Venezuelan and Colombian children and adolescents aged 5 to 17. To our knowledge, it is the first study to gather panel data specifically on forcibly 1This concern is also prevalent among undocumented migrants in the United States, as highlighted by Amuedo-Dorantes and Lopez (2015). 2
**Statistical Note: Clustering in DHS-Based Analyses**

In all regression tables, _t_-statistics are computed using standard errors clustered at the DHS cluster level. This clustering is essential because: (a) the DHS sampling design introduces within-cluster homogeneity that violates the assumption of independent errors; and (b) our treatment variable — mine proximity — is constant within a DHS cluster, so ignoring within-cluster correlation would produce artificially small standard errors. The effective sample size after clustering is substantially smaller than the nominal number of DHS interviews.
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.
Staff based on SESRE 2023. Most of the analysis presented in this chapter is based on detailed consumption data from the Socioeconomic Survey of Refugees in Ethiopia (SESRE) conducted between October 2022 and February 2023. All consumption of food and non-food items is included, regardless of whether these items are purchased on the market, come from own production, or received as gifts. For own-consumption and gifts, the quantities consumed are valued at prevailing prices in the enumeration area. Although consumption is expressed annually, the reference period used during data collection varies based on the nature of the items. For example, questions related to information on food and food-related items was asked by visiting households twice a week using the “last three days” and “last four days” as reference periods. For house rent, durable goods, clothing, health and education expenditures, and some other categories, the survey questions used the “last three months” and “last 12 months” as references. Imputed rent for owner-occupied houses is calculated by the Ethiopian Statistical Service (ESS) team and is included in the consumption expenditure data shared with the Bank team. Spatial and temporal price deflators adjust for price variations across time and space. First, nominal consumption
12 employment status and education level also significant at 10 %. Marital status and education are important predictors of attrition. As we might expect, these imbalances suggest some threats that, if left uncorrected, could undermine the parallel trends assumption of difference-in-difference estimators. That said, we see no sign of differences between treatment and control, or attritors and non-attritors, over the key GRIT personality features. This suggests that members of the treatment group are not, for example, more motivated to succeed than members of the control group. To account for these biases, we generate a series of inverse probability weights to balance the data. These weights define the probability of an individual with particular characteristics (e. g. host or refugee status) being in each of the treatment and control groups at baseline and endline and are used to rebalance the data in order to closer support the parallel trends assumption. Results are shown in Column 3 of Table 4. Following weighting, data balances on all key factors, including nationality. This suggests that the parallel trends assumption is more reasonable under the weighted dataset than in the raw treatment / control data. 11 Based on these analyses, we conclude that it is safe to use weighted OLS-based approaches.