ai4data/datause-dataset-rechunked huggingface dataset:
Figure 5 Panel A illustrates the percent of FDP datasets that cover various topics in their questionnaire modules and Panel B shows differences in the percent of datasets covering each topic between FDP datasets and all other non-FDP datasets stored in the WB MDL. 32 The topic of health is by far the most common with roughly 78 percent of datasets mentioning keywords related to health in their descriptions of the questionnaire modules. Other common topics include food insecurity (49 percent) and water sanitation (39 percent). Less frequently included are topic areas related to labor and employment (19 percent); security and conflict (18 percent); finance, credit and debt (14 percent); agriculture and livestock (10 percent), and shocks (9 percent). The fact that topics such as security, conflict and shocks are often not included in the survey modules is not unique to FDP datasets. In fact, those topics are also relatively uncommon in other micro-level household surveys available in the WB MDL. When compared to the topic coverage of all non-FDP micro-level datasets in the WB MDL, FDP datasets are scarcer in such topics as labor, finance, agriculture / livestock / fishery, and education. As shown in Figure 5 Panel B, these topics are much more likely to be picked up in the non-FDP micro-level datasets. When it comes to labor and employment in particular, the gap is over 50 percentage points illuminating 32 See Annex C for further details on the methodology used to analyze topic coverage. For this topic coverage analysis, we exclude those datasets that are project specific or collected before 2010.
Ababa live in rented houses; the team faced challenges in tracing some refugees due to changes in their residential locations. Challenges related to identifying the eligible sample households were also observed due to outdated names of the household heads in UNHCR lists, and UNHCR’s registration of names which is not consistent with the Ethiopian context58. Thus, these challenges required additional effort by the team to ensure that sampled households and replacements were traced, identified, and interviewed. Another challenge was that some refugees were not willing to provide their current location due to personal security reasons, but these situations were resolved by reaffirming the confidentiality of the survey. 58 UNHCR register names starting with last name, whereas, in Ethiopia names starts with first name. Annexes 97 Annex D: Descriptive Statistics and Regression Results Results on Sociodemographic Profile Table D.1: Demographic characteristics by survey domains Eritrean Somali South Sudanese Hosts Refugees Hosts Refugees Hosts Refugees Age group <15 39% 46% 54% 50% 47% 56% 15 to 24 19% 19% 17% 22% 21% 21% 25 to 44 26% 25% 21% 17% 21% 16% 45 to 64 13% 8% 7% 9% 8% 5% >=65 4% 2% 2% 2% 3% 1% Gender Male 48% 51%
Still, despite these critiques, the evidence in this paper cautions against a naive switch to the HCES
direct method. In our survey experiment, we calculate hunger to range between 19 and 68 percent -this

is a difference of more than 23 million people in Tanzania (a country with a population of 45 million

presenting a strong challenge to both the HCES-direct and the FBS-CV methods. The FBS-CV is

Note: estimates of Equation (1). Each column represents the results of a (separate) regression (OLS or LPM) of a selected HCES-derived measure (mentioned in the titles of the panels) on 7 module assignment dummies, a single selected household characteristic (mentioned in the column headings) and 7 interaction terms of that household characteristic with the module assignment dummies.

Smith L. 1998. Can FAO's Measure of Chronic Undernourishment be Strengthened? _Food Policy_ 23(5):
about 333,000 Venezuelan children were enrolled in government schools in 2020 (about 3.4 percent of the total student population in Colombia) (UNHCR, 2021a). In Turkey, the government is supporting the transition of Syrian refugee children into the national school system, redirecting resources to locations with high concentrations of refugees (Abu-Ghaida and Silva, 2020), resulting in nearly 80 percent of Syrian primary school-aged refugee children being enrolled in education programs by 2020/2021 (UNHCR, 2021). In addition to benefiting refugee children, high school enrolment and learning outcomes increased for local Turkish students (Tumen, 2019; 2021). Educational attainment is low among both hosts and refugees, especially in camps. About 73 percent of in-camp adult refugees and 59 percent of adult hosts (aged 18 and above) either did not attend school or did not complete primary education. South Sudanese refugees have the worst educational attainment. Refugees in Addis Ababa have relatively better educational attainment compared to their hosts, with a higher percentage of refugees in Addis Ababa completing primary (45 percent) and secondary (27 percent) education (Figure 2.7). Although more educated, even youth’s (age 15 to 24) educational attainment is low, with large differences by survey domains. Many youth refugees and hosts have not