This is a 2019 paper that used GIS and probability modelling to estimate poverty and population distribution across Somalia & Somaliland. This is unlike previous reports that used human estimates for poverty and population that were often unreliable. Very interesting findings.
Abstract
Results
Ka fikir walaalayaal Let's keep it qabyaalad free during this blessed month
Abstract
Somalia is highly data-deprived, leaving policy makers to operate in a statistical vacuum. To overcome this challenge, the World Bank implemented wave 2 of the Somali High Frequency Survey to better understand livelihoods and vulnerabilities and, especially, to estimate national poverty indicators. The specific context of insecurity and lack of statistical infrastructure in Somalia posed several challenges for implementing a household survey and measuring poverty. This paper outlines how these challenges were overcome in wave 2 of the Somali High Frequency Survey through methodological and technological adaptations in four areas. First, in the absence of a recent census, no exhaustive lists of census enumeration areas along with population estimates existed, creating challenges to derive a probability-based representative sample. Therefore, geospatial techniques and high-resolution imagery were used to model the spatial population distribution, build a probability-based population sampling frame, and generate enumeration areas to overcome the lack of a recent population census. Second, although some areas remained completely inaccessible due to insecurity, even most accessible areas held potential risks to the safety of field staff and survey respondents, so that time spent in these areas had to be minimized. To address security concerns, the survey adapted logistical arrangements, sampling strategy using micro-listing, and questionnaire design to limit time on the ground based on the Rapid Consumption Methodology. Third, poverty in completely inaccessible areas had to be estimated by other means. Therefore, the Somali High Frequency Survey relies on correlates derived from satellite imagery and other geo-spatial data to estimate poverty in such areas. Finally, the nonstationary nature of the nomadic population required special sampling strategies.
Results
Poverty is somewhat heterogeneous between different population types and regions. Urban areas have a lower poverty headcount rate (60 percent), than the rest of the Somali population (Figure 6; p<0.01 vs. Mogadishu, p<0.05 vs. IDPs in settlements and nomads, and p<0.10 vs. rural areas).34 This comparison excludes the capital, Mogadishu, whose residents are poorer than in other urban areas (between 72 and 76 percent). This higher poverty rate in Mogadishu compared to other urban areas is likely the result of a larger concentration of the displaced population and the challenges associated with the displacement crisis, which the 2016/17 drought recently exacerbated.35
Poverty is also heterogeneous across space. Based on estimates from satellite imputation, the highest levels of poverty are clustered in south‐western Somalia, and several districts in northern Somalia (Figure 7).
Ka fikir walaalayaal Let's keep it qabyaalad free during this blessed month
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