Data gaps, data incomparability, and data imputation: a review of poverty measurement methods for data-scarce environments

Hai-Anh H. Dang, Dean Mitchell Jolliffe, Calogero Carletto, Hai-Anh H. Dang, Dean Mitchell Jolliffe and Calogero Carletto
Authors registered in the RePEc Author Service: Hai-Anh H. Dang (), Dean Jolliffe and Calogero Carletto

No 8282, Policy Research Working Paper Series from The World Bank

Abstract: This paper reviews methods that have been employed to estimate poverty in contexts where household consumption data are unavailable or missing. These contexts range from completely missing and partially missing consumption data in cross-sectional household surveys, to missing panel household data. The paper focuses on methods that aim to compare trends and dynamic patterns of poverty outcomes over time. It presents the various methods under a common framework, with pedagogical discussion on the intuition. Empirical illustrations are provided using several rounds of household survey data from Vietnam. Furthermore, the paper provides a practical guide with detailed instructions on computer programs that can be used to implement the reviewed techniques.

Keywords: Inequality; Poverty Diagnostics; Poverty Monitoring&Analysis; Poverty Lines; Poverty Impact Evaluation; Small Area Estimation Poverty Mapping; Poverty Assessment; Educational Sciences; Labor&Employment Law; Demographics (search for similar items in EconPapers)
Date: 2017-12-19
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Citations: View citations in EconPapers (7)

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Related works:
Journal Article: DATA GAPS, DATA INCOMPARABILITY, AND DATA IMPUTATION: A REVIEW OF POVERTY MEASUREMENT METHODS FOR DATA‐SCARCE ENVIRONMENTS (2019)
Working Paper: Data gaps, data incomparability, and data imputation: A review of poverty measurement methods for data-scarce environments (2018)
Working Paper: Data Gaps, Data Incomparability, and Data Imputation: A Review of Poverty Measurement Methods for Data-Scarce Environments (2018)
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