Regression-based Imputation for Poverty Measurement in Data Scarce Settings

Hai-Anh Dang () and Peter Lanjouw

No 611, Working Papers from ECINEQ, Society for the Study of Economic Inequality

Abstract: Measuring poverty trends and dynamics are important inputs in the formulation and design of poverty reduction policies. The empirical underpinnings of such exercises are often constrained by the absence of suitable data. We provide a broad, generalist, overview of regression-based imputation methods that have seen widespread application to estimate poverty outcomes in data-scarce environments. In particular, we review two imputation methods employed in tracking poverty over time and estimating poverty dynamics. We also discuss new areas that promise of further research.

Keywords: poverty; imputation; consumption; wealth index; synthetic panels; household survey (search for similar items in EconPapers)
JEL-codes: C15 I32 O15 (search for similar items in EconPapers)
Pages: 17 pages
Date: 2022-04
New Economics Papers: this item is included in nep-ecm
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http://www.ecineq.org/milano/WP/ECINEQ2022-611.pdf First version, 2022 (application/pdf)

Related works:
Chapter: Regression-based imputation for poverty measurement in data-scarce settings (2023)
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Persistent link: https://EconPapers.repec.org/RePEc:inq:inqwps:ecineq2022-611

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