ai4data/datause-dataset-rechunked huggingface dataset:
While both sons and daughters of the head may be expected to be more likely to stay in the community than other initial household members, patri-locality would make this probability higher for boys than for girls. In sum, this means we are using a set of six instruments. Although we can show that statistically convincing and close to identical results can be obtained by only using a subset of these instruments, we use the full set of instruments in the reported results. While our main measure of migration (Mi) is an indicator for having moved, we also substitute this for the log of the distance moved (kilometers from the original community of the location in which the individual was found in 2004, ‘ as the crow flies ’, set to 0 for non-movers). We will also extend the multivariate analysis to explore the role of moving to more urbanized areas and the role of sector movement in raising consumption growth. 6. Regression Results Table 9 presents the basic results for the initial household fixed effects (IHHFE) and 2SLS estimates (means for covariates are in Appendix Table 1). For each we estimate using an indicator for having moved and a measure of distance of the move. The 2SLS estimates in column (3) and (4) use the six instruments defined above. In Table 10, we present the first stage results of regressions explaining migration or the distance traveled in migration.
refugees lived in poverty, compared to 17 percent of hosts, in 2018 (World Bank, 2019). In Kalobeyei Settlement in Turkana County in Kenya, more than half of refugees are poor (58 percent), higher than the national poverty rate of 37 percent, lower than the poverty rate in Turkana County but comparable to the average poverty rate of the 15 poorest counties in Kenya (UNHCR and World Bank Group, 2020). About 72 percent of registered Venezuelans in Brazil live in extreme poverty, compared to 48 percent of Brazilians (Shamsuddin et al., 2021). Similarly, this report finds that poverty rates in Ethiopia’s refugees in camps are much higher than for host communities. Yet, refugee inflows can significantly affect host communities. Governments have been preoccupied with whether the arrival of large numbers of people in specific locations creates risks or opportunities for decades. Experience has shown that opportunities typically result if the influx of refugees is managed well and brings benefits to host communities similar to those of voluntary migrants. A recent review of the literature on refugee effects on host communities showed that most studies find a positive or non- significant effect of forced displacement on hosts’ employment, wages, and household well-being.
For example, IDPs who subsequently cross international borders may be counted as both IDPs and refugees (e. g. in the case of the Syrian displacement crisis). Table 4: Stocks and Flows Stock Increases Decreases Asylum- seekers  New applications for asylum, separately identifying individuals who were previously IDPs  Positive decisions (convention status, complementary protection status)  Rejected  Otherwise closed Refugees  Spontaneous arrivals (group recognition, temporary protection, individual recognition), separately identifying individuals who were previously IDPs  Resettlement arrivals  Births  Administrative corrections  Repatriation  Resettlement  Cessation  Naturalization  Deaths  Administrative corrections IDPs  New internal displacement  Births  Administrative corrections  Cross border flight, becoming an asylum-seeker or refugee  Return  Settlement elsewhere in the country  Local integration  Administrative corrections Source: UNHCR Global Trends, IDMC Forced Displacement Data Model
Of all countries in the World Bank's WDI, only 60%
(40% of the analyzed countries) had an inflation figure for the most recent 2019-2020 period. The IFS
data reported similarly on only half of the countries. This was last checked on August 31, 2021; WDI
data identifier FP.CPI.TOTL.ZG, and IFS data identifier PCPI ~~P~~ C ~~P~~ P ~~P~~ T.

The paper highlights the new price monitoring capabilities using surveys from the World Food Programme (WFP) gathered in 25 fragile and conflict-affected countries.

Subnational food prices have been surveyed in many countries for years by
humanitarians to inform their country operations. Well-known data bases are
those from the WFP, FEWS NET and the Food and Agricultural Organization
(FAO). [6] The paper focuses on raw monthly data from the WFP, but parts of the
discussion, and particularly the methods developed here, could apply to similar
data sets. [7]

The paper gathered all end-of-August data available from the WFP Vulnerability Analysis and Mapping (VAM) unit as of September 21, 2021.
The LFS reference week design captures the contemporaneous employment status of respondents at the time of interview, making it sensitive to the specific week in which households are interviewed within a quarter. To address seasonality, the LFS staggers interviews evenly across the 13 weeks of each quarter, ensuring that agricultural and other seasonal employment cycles are represented proportionally in the quarterly sample. We account for residual seasonality in our models by including a full set of quarter-of-year fixed effects and their interactions with the rural indicator.
7 All data collection is done by GISSE a research institute in Bamako. The anonymized unit record data of the baseline and the monthly surveys can be downloaded from www. gisse. org. The response rate for the phone interviews has been very high (Table 1): after 6 rounds of monthly interviews the original sample is almost entirely intact. The low level of attrition demonstrates that mobile phone samples can be maintained over prolonged periods without being unduly affected by (non-random) respondent drop-out. 3. Characteristics of the Displaced and Returnee Population According to the 2009 population census, the two most sizeable ethnic groups in northern Mali are the Songhai (45 %) and Kel Tamasheq (32 %)-- see Table 2. The crisis brought about an ethnic divide, which is reflected in the composition of the three sub-samples. The majority of IDPs and returnees are Songhai (75 % and 71 % respectively), while the majority of refugees are Kel Tamasheq. Results suggest that the decision of where to flee was determined by ethnicity: Kel Tamasheq and Arabs left the country; Songhai fled towards Bamako.
The curriculum included entrepreneurship principles, market analysis, business management, customer service, money management, and record-keeping. The EPAG program was implemented by four NGOs who were selected by the Liberian Ministry of Gender and Development through a competitive bidding process: the Community Empowerment Program (CEP), Liberia Entrepreneurial and Economic Development (LEED), the International Rescue Committee (IRC), and the American Refugee Committee (ARC). Two of these organizations (ARC and IRC) further subcontracted to four Liberian NGOs. 4 The service providers were responsible for developing training curricula, identifying training venues, 5 making arrangements for childcare services, assisting with the mobilization of the nine target communities, and participating in the recruitment of training participants. The EPAG program differed from many training programs in a number of ways. First, performance bonuses were awarded to training providers that successfully place their graduates in jobs or micro- enterprises. The bonus was the last payment that the service providers received under their contracts. These were paid about 12 months after the start of training, or around the same time as the midline survey. Second, a variety of contests and competitions were also held among EPAG trainees (such as attendance prizes, quizzing contests, business plan competitions, etc.).
The upcoming section provides an overview of the situation facing Venezuelan migrants in Colombia, setting the stage for understanding the context within which our study is situated. Section three offers a comprehensive description of the VenRePS-Kids study, covering aspects such as the sampling frame, the instrument used for data collection, the representativeness of the study, its implementation process, and an overview of descriptive statistics. Section four delves into the human development disparities observed among forcibly displaced chil- dren and adolescents, providing detailed insights into the nature of these gaps. In section 9
A recent global hazard analysis generated a comprehensive database of hazard events during 1975- 2007 from observed data and of event probabilities from geo-physical models (ISDR 2009). We combined this hazard information with city-specific population projections 2 It should be noted that well-documented evidence for such externalities is quite scarce. Their importance is usually taken as given: “ A building collapse may create externalities in the form of economic dislocations and other social costs in addition to the economic loss suffered by the owner. The owners may not have taken these consequences into account when evaluating specific mitigation measures. Consider the following example. A building toppling off its foundation after an earthquake could break a pipeline and cause a major fire, which would damage other homes that had not been affected by the earthquake in the first place. “ Kuenreuther and Roth (1998). See also www. quakesmart. org / index. php? option = com_content & view = article & id = 92 & Itemid = 209. But some experiences have been documented: “ As shown by research on the Great Hanshin-Awaji Earthquake, including that conducted by the Architectural Institute of Japan, Architectural Institute of Japan (1997), houses with inferior earthquake-resistant quality triggered large negative externalities in the neighborhood. For example, broken fragile houses blocked transportation networks, thereby preventing effective fire fighting and, by severing lifelines, they made recovery more difficult. ” (Nakagawaa et al. 2007).
Humanitarian organizations such as UNHCR and OCHA as well as international organizations such as IOM are also involved in the collection of data on IDPs, often involving international and local 59 OCHA is the part of the United Nations Secretariat responsible for bringing together humanitarian actors to ensure a coherent response to emergencies. See http: / / www. unocha. org /. 60 This section draws heavily on the “ Report of Statistics Norway and the Office of the United Nations High Commissioner for Refugees on statistics on refugees and IDPs ” presented at the UNSD in March 2015. 61 The number of countries where UNHCR exclusively collects data on refugees declined from 76 in 2010 to 72 in 2014, while the proportion of countries where refugee data were exclusively provided by governments gradually increased over the same period from 33 to 38 percent. In 2014, the proportion of countries where data were provided through collection conducted jointly by governments and UNHCR was 15 percent, while in the remaining proportion (13 percent), refugee data were provided exclusively by NGOs and other organizations. In 2014, more than 173 countries and territories provided data on refugees.
[2 Available at http://faostat3.fao.org/home/index.html (accessed 11 June 2013)](http://faostat3.fao.org/home/index.html) 3 Smith (1998) reports that, at the time, for 18 out of the 99 countries, the CVs are estimated based on analysis of nationally representative HCES. The rest of the countries' CVs are predicted either from measures of income distribution or as the mean CV estimated for other countries in the same region.

4 In 2012 the FAO revised its distribution to be the skew-normal distribution (Azzalini, 1985), which generalises the normal distribution to allow for skewing.
1. Introduction Sub-Saharan Africa is the youngest region in the world, and the world ’ s fastest-growing. Between 2010 and 2025, the number of people between 15 and 24 will grow to 250 million – a net increase of nearly 50 percent. Over the next decade, roughly one million young people will enter the labor market each month in Sub-Saharan Africa. However, these young people often enter the labor market too early and unprepared. Although access to education is growing, illiteracy remains high and schooling low: among the 32 Sub-Saharan African countries in the Barro-Lee (2010) data set, nearly 40 percent of women aged 15 and above have received no education at all; and the most recent (2007-2011) statistics in the World Bank ’ s Edstats data reveal that female literacy is less than 60 percent, on average. 1 This lack of preparedness contributes to a growing problem of youth unemployment. Quantifying the level of unemployment is bedeviled by lack of data and measurement issues. Household and labor force surveys throughout Africa usually record unemployment rates of less than 10 percent, 2 but those figures belie the extent of underemployment and vulnerability. Those same surveys indicate that the vast majority of working adults have insecure work in the informal sector, on the family farm, or in less- productive or unremunerated labor.
These calculations conﬁrm our earlier assessment. 5 Conclusion Combining data from a household survey and an 11 % census of the population, we have estimated destination choice regressions for Nepalese internal migrants. Results show that population density, social proximity, and access to amenities exert a strong inﬂuence on migrants ’ choice of destination. These results conﬁrm earlier work on the factors aﬀecting the subjective welfare cost of isolation (Fafchamps and Shilpi, 2008). 29
Addis Ababa All Hosts Increased economic opportunity Increased insecurity Are taking our land Figure 7.6: Host beliefs about refugee impact in Ethiopia Source: World Bank Staff based on SESRE 2023. 50 The numbers are combined here, but mainly measures employment competition since very few are concerned about wage competition. 0 5 10 15 20 25 30 35 40 Eritrean Somali South Sudanese Addis Ababa All Hosts Improved Infrastructure Improved Services Figure 7.8: Positive experience due to refugees Source: World Bank Staff based on SESRE 2023. Markets and Opportunities 67 Overall, hosts and refugees show similar trust rates in each other; still, refugees are generally more trusting. Questions about the trustworthiness of hosts and refugees reveal that most people either trust both (hosts and refugees) or neither group. Only 17 percent of hosts trust other Ethiopians but not refugees, and only 10 percent of refugees trust other refugees but not Ethiopians. In comparison, 39 percent of hosts and 55 percent of refugees trust both groups. Once again, hosts’ trust towards refugees is highest in the Somali domain (67 percent) and lowest in the South Sudanese domain (29 percent). On the other hand, refugee trust towards hosts is lowest in the Eritrean
The vulnerability of the Internally Displaced People in SSA has certainly been overlooked for too long, but the increased support provided by UNHCR is an encouraging but challenging sign in that respect. Figure 3. Refugees and Internally Displaced People in SSA, 2003 ‐ 2013 Source: Note: Refugee data are from the UNHCR statistical population online dataset, accessed in September 2014. Refugee data from 2007 to 2013 include people in refugee ‐ like situations (see note, Figure 1). The annual number of IDPs is collected from the IDMC (2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2012, 2013, 2014) annual reviews.
obtained from the multilevel logistic model. Thus, I am conﬁdent that I did not lose substantial statistical information by dichotomizing this variable. 6. 2 Independent Variables 6. 2. 1 Socio-Demographic Variables I control for standard socio-demographic variables that can aﬀect citizens ’ acceptance of government ’ s right to make people pay taxes. A question prob- ing respondents on their household income was not included in the fourth round of Afrobarometer surveys. Asking respondents to quantify their in- come can be problematic in the context of developing economies, where in- dividuals are often embedded in barter or commodity exchange, rather than, market economies. There are, however, reasonably good proxies including whether respondents own a television, radio, car, and mobile phone, and use the internet. Age, education, employment, and urban or rural residence are demographic factors that also aﬀect household resources. 6. 2. 2 Experience with Paying Taxes or Fees It is diﬃcult to assess just how ubiquitous taxes are in ordinary Africans ’ lives. There has not been any systematic eﬀort to take stock of the types and amount of taxes citizens pay across Africa. Similar to pre-modern European states, African states ’ revenue raising capacity is generally low.
3 population study2 (Brown et al, 2019) revealed that 78 percent of the population of registered refugees lived below the Jordanian poverty line, and between 2017 and 2019, there was only a 2- percentage point reduction of highly vulnerable cases. 3 UNHCR (2018a) also reports that close to 37 % of the registered Syrian refugees in Jordan are separated from a family member. Household structures have often been fluid. Many Syrian families sent members ahead to Jordan to settle and sometimes, after the reunification of the rest of the family in Jordan, male family members traveled on to Türkiye or to Europe (UNHCR, 2018a). These separations likely affected families emotionally and economically. However, little is known about the changes in economic well-being over time or how gender inequality has shaped poverty and expenditure outcomes. We use two waves of data from a unique household survey, the United Nations High Commissioner for Refugees (UNHCR) Home-Visits survey for 2013-14 and 2017-18. First, we create comparable measures of expenditure per capita over time. Then, we assess whether certain types of households are more likely to be below the median of the per capita expenditure distribution in each time period.
and 6 percent for hosts, and in the camps is 13 percent for refugees and 12 percent for hosts. 0.05 0 0.1 0.15 0.2 0.25 0.3 0.35 Elementary Occupations Craf/Related Trades Service/Sales Machine Operators Associate Prof. Clerical Support Professionals Share of Refugees Observed Predicted according to observables Figure 3.26: Refugee occupation concentration Source: World Bank Staff based on SESRE 2023. Jobs and Livelihoods 38 In Addis Ababa, refugee girls—like boys—are much less likely than host counterparts to work or attend school, and they are more likely to be unemployed or NEET. They are even less likely than refugee boys to be in school and more likely to be NEET (23 percent for girls relative to 15 percent for boys—Figure 3.28). In camps, refugee girls look more like their host counterparts regarding schooling and labor force participation. However, among those in the workforce, their relaxed unemployment rate is much higher (55 percent for female refugees and 36 percent for female hosts). Boys in camps have higher schooling rates (75 percent relative to 65 percent for hosts), reflecting their higher propensity to stay enrolled in primary or secondary schooling after the typical completion age, especially in South Sudanese camps where 84 percent
There were in total 1, 6 million refugees by November 2014. Data on the number of new ﬁrms and their ownership characteristics and value are provided by the Turkish Chamber of Commerce. 7 Data on total sales and gross proﬁts are obtained from the Turkish Ministry of Science, Industry and Technology. Other economic indi- cator variables, such as population and unemployment rates, are obtained from Turkish Statistics. Since Syrians usually have guest status rather than resident status during the period of analysis, they are not counted in oﬃcial statistics such as province population and unemployment rates. Turkey is oﬃcially divided into 81 provinces and that is the level of our analysis and variables throughout. The Chamber of Commerce provides data on the number of new ﬁrms and the num- ber of new foreign-owned ﬁrms at the provincial level. Enterprises deﬁned as ﬁrms do 11
Survey of Refugees in Ethiopia (SESRE) contribute to the debate on policies? The Socio-Economic Survey of Refugees in Ethiopia (SESRE) is a representative survey of the refugee population in Ethiopia and their host communities, the first of its kind.9 Ethiopia made significant progress over the past few years in articulating more progressive and comprehensive refugee responses. In 2023, the GoE included new pledges and commitments made in the 2023 Global Refugee Forum, including a significant shift in its refugee management policies. This includes improving the socio and economic opportunities for refugees through an agenda to transform camps into human settlements and including refugees in national services for education, including secondary education and health (UNHCR, 2024). Systematically collecting high-quality data on refugees and their hosts in one survey is pertinent to inform the GoE’s roadmap and programs to address the development needs of refugees and hosts. The national household survey of Ethiopia–Household Welfare Statistics Survey (HoWStat)—excludes the majority of displaced populations (Internally Displaced People [IDPs] or refugees) from its sample of households. Thus, we have limited in-depth information on the socio-economic outcomes—including on poverty— for refugees across all camps in Ethiopia to compare with Ethiopian hosts. SESRE collected data from November
Most importantly for the purpose of the analysis is the fact that the survey provides individual-level data on own schooling and parents ’ schooling for all adults in the sample, which is quite rare in household surveys from developing countries. Also, the survey provides the actual years of schooling completed and not only the highest educational degree attained, which allow observing the schooling variable with precision.
Without army protection most parts of the North, especially Kidal remain inaccessible to those working for the central and local government. 3 Armed bandits are active and IED explosions as well as violent attacks on the MINUSMA peacekeeping forces are regular occurrences. Under these circumstances, data collection is very difficult. INSTAT, the National Bureau of Statistics, has not been in a position to collect information from northern Mali since the beginning of the crisis. To our knowledge, our surveys implemented by a private survey entity, GISSE, are the only systematic and representative effort to collect data in north Mali since the crisis. They offer a unique database providing a crucial perspective that would otherwise not be reflected in academic analyses and policy level decision-making, and a perspective that is indispensable in any attempt at understanding the situation in Northern Mali. 4 Preceding the Accord on Peace and Reconciliation in Mali (Accord pour la paix et la réconciliation au Mali) (hereafter, the Peace Accord) of May and June 2015, four peace accords had been signed between the government and Toureg and Arab armed groups in 1 Kel Tamasheq (those who speak Tamasheq) is synonymous for Tuareq. 2 Francis David (2013): The regional impact of the armed conflict and French intervention in Mali. NOREF, Norwegian Peacebuilding Resource Centre. 3 Assessing Recovery and Development Priorities in Mali ’ s Conflict-Affected Regions. Draft Report of the Joint Assessment Mission for Northern Mali (January 2016), p. 15-16. 4 All data can be downloaded from www. gisse. org.