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The Bayesian approach to poverty measurement

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  • Michel Lubrano

    (School of Economics, Jiangxi University of Finance and Economics, AMSE - Aix-Marseille Sciences Economiques - EHESS - École des hautes études en sciences sociales - AMU - Aix Marseille Université - ECM - École Centrale de Marseille - CNRS - Centre National de la Recherche Scientifique)

  • Zhou Xun

    (School of Economics and Management [Nanjing] - NJUST - Nanjing University of Science and Technology)

Abstract

This survey paper reviews the recent Bayesian literature on poverty measurement. After introducing Bayesian statistics, we show how Bayesian model criticism could help to revise the international poverty line. Using mixtures of lognormals to model income, we derive the posterior distribution for the FGT, Watts and Sen poverty indices, then for TIP curves (with an illustration on child poverty in Germany) and finally for Growth Incidence Curves. The relation of restricted stochastic dominance with TIP and GIC dominance is detailed with an example on UK data. Using panel data, we show how to decompose poverty into total, chronic and transient poverty, comparing child and adult poverty in East Germany when redistribution is introduced. When a panel is not available, a Gibbs sampler is used to build a pseudo panel. We illustrate poverty dynamics by examining the consequences of the Wall on poverty entry and poverty persistence in occupied West Bank.

Suggested Citation

  • Michel Lubrano & Zhou Xun, 2021. "The Bayesian approach to poverty measurement," Working Papers halshs-03234072, HAL.
    • Handle: RePEc:hal:wpaper:halshs-03234072
    Note: View the original document on HAL open archive server: https://shs.hal.science/halshs-03234072
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    References listed on IDEAS

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    More about this item

    Keywords

    bayesian inference; mixture model; poverty indices; stochastic dominance; poverty dynamics;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs

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