Publication: Estimating Poverty for Refugee Populations: Can Cross-Survey Imputation Methods Substitute for Data Scarcity?
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Date
2019-12
ISSN
Published
2019-12
Author(s)
Abstract
The increasing growth of forced
displacement worldwide has led to the stronger interest of
various stakeholders in measuring poverty among refugee
populations. However, refugee data remain scarce,
particularly in relation to the measurement of income,
consumption, or expenditure. This paper offers a first
attempt to measure poverty among refugees using cross-survey
imputations and administrative and survey data collected by
the United Nations High Commissioner for Refugees in Jordan.
Employing a small number of predictors currently available
in the United Nations High Commissioner for Refugees
registration system, the proposed methodology offers
out-of-sample predicted poverty rates. These estimates are
not statistically different from the actual poverty rates.
The estimates are robust to different poverty lines, they
are more accurate than those based on asset indexes or proxy
means tests, and they perform well according to targeting
indicators. They can also be obtained with relatively small
samples. Despite these preliminary encouraging results, it
is essential to replicate this experiment across countries
using different data sets and welfare aggregates before
validating the proposed method.
Link to Data Set
Citation
“Dang, Hai-Anh H.; Verme, Paolo. 2019. Estimating Poverty for Refugee Populations: Can Cross-Survey Imputation Methods Substitute for Data Scarcity?. Policy Research Working Paper;No. 9076. © World Bank, Washington, DC. http://hdl.handle.net/10986/33020 License: CC BY 3.0 IGO.”
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