Estimation of Poverty in Somalia Using Innovative Methodologies
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, e...
| Main Authors: | , |
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| Format: | Working Paper |
| Language: | English |
| Published: |
World Bank, Washington, DC
2019
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| Subjects: | |
| Online Access: | http://documents.worldbank.org/curated/en/509221549985694077/Estimation-of-Poverty-in-Somalia-Using-Innovative-Methodologies http://hdl.handle.net/10986/31267 |
| Summary: | 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. |
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