Poverty Imputation in Contexts Without Consumption Data: A Revisit With Further Refinements

Hai-Anh Dang (), Talip Kilic, Kseniya Abanokova and Calogero Carletto

Review of Income and Wealth, 2025, vol. 71, issue 1

Abstract: Survey‐to‐survey imputation has been increasingly employed to address data gaps for poverty measurement in poorer countries. We refine existing imputation models, using 14 multi‐topic household surveys conducted over the past decade in Ethiopia, Malawi, Nigeria, Tanzania, and Vietnam. We find that adding household utility expenditures to a basic imputation model with household‐level demographic and employment variables provides accurate estimates, which even fall within one standard error of the true poverty rates in many cases. The proposed imputation method performs better than several commonly used multiple imputation and machine learning techniques. Further adding geospatial variables improves accuracy, as does including additional community‐level predictors (available from data in Vietnam) related to educational achievement, poverty, and asset wealth. Yet, within‐country spatial heterogeneity exists, with certain models performing well for either urban areas or rural areas only. These results offer cost‐saving inputs into future survey design.

Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1111/roiw.12714

Related works:
Working Paper: Poverty imputation in contexts without consumption data: a revisit with further refinements (2025)
Working Paper: Poverty Imputation in Contexts without Consumption Data: A Revisit with Further Refinements (2023)
Working Paper: Poverty Imputation in Contexts without Consumption Data: A Revisit with Further Refinements (2023)
Working Paper: Poverty Imputation in Contexts without Consumption Data: A Revisit with Further Refinements (2021)
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:bla:revinw:v:71:y:2025:i:1:n:e12714

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0034-6586

Access Statistics for this article

Review of Income and Wealth is currently edited by Conchita D'Ambrosio and Robert J. Hill

More articles in Review of Income and Wealth from International Association for Research in Income and Wealth Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().