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

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  • Hai-Anh Dang

    (World Bank, USA)

  • Dean Jolliffe

    (World Bank, USA)

  • Calogero Carletto

    (World Bank, USA)

Abstract

We offer a review of methods that have been employed to provide poverty estimates of 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. We focus on methods that aim to compare trends and dynamic patterns of poverty outcomes over time. We present the various existing 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, we also offer a practical guide with detailed instructions on computer programs that can be used to implement the reviewed techniques.

Suggested Citation

  • Hai-Anh Dang & Dean Jolliffe & Calogero Carletto, 2018. "Data gaps, data incomparability, and data imputation: A review of poverty measurement methods for data-scarce environments," Working Papers 456, ECINEQ, Society for the Study of Economic Inequality.
    • Handle: RePEc:inq:inqwps:ecineq2018-456
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    More about this item

    Keywords

    poverty; mobility; imputation; consumption; wealth index; synthetic panels; household survey.;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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