Estimating Poverty for Refugee Populations: Can Cross-Survey Imputation Methods Substitute for Data Scarcity?

Hai-Anh Dang () and Paolo Verme

No 429, GLO Discussion Paper Series from Global Labor Organization (GLO)

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.

Keywords: poverty imputation; Syrian refugees; household survey; missing data; Jordan (search for similar items in EconPapers)
JEL-codes: C15 I32 O15 (search for similar items in EconPapers)
Date: 2019
New Economics Papers: this item is included in nep-ara and nep-dev
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/208006/1/GLO-DP-0429.pdf (application/pdf)

Related works:
Working Paper: Estimating Poverty for Refugee Populations: Can Cross-Survey Imputation Methods Substitute for Data Scarcity? (2019)
Working Paper: Estimating Poverty for Refugee Populations: Can Cross-Survey Imputation Methods Substitute for Data Scarcity ? (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:zbw:glodps:429

Access Statistics for this paper

More papers in GLO Discussion Paper Series from Global Labor Organization (GLO) Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics ().