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Stochastic dominance and decomposable measures of inequality and poverty

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  • Buhong Zheng

Abstract

In this paper, we characterize some new links between stochastic dominance and the measurement of inequality and poverty. We show that: for second‐degree normalized stochastic dominance (NSD), the weighted area between the NSD curve of a distribution and that of the equalized distribution is a decomposable inequality measure; for first‐degree and second‐degree censored stochastic dominance (CSD), the weighted area between the CSD curve of a distribution and that of the zero‐poverty distribution is a decomposable poverty measure. These characterizations provide graphical representations for decomposable inequality and poverty measures in the same manner as Lorenz curve does for the Gini index. The extensions of the links to higher degrees of stochastic dominance are also investigated.

Suggested Citation

  • Buhong Zheng, 2021. "Stochastic dominance and decomposable measures of inequality and poverty," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 23(2), pages 228-247, April.
    • Handle: RePEc:bla:jpbect:v:23:y:2021:i:2:p:228-247
    DOI: 10.1111/jpet.12496
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    2. Chan, Terence, 2022. "On a new class of continuous indices of inequality," Mathematical Social Sciences, Elsevier, vol. 120(C), pages 8-23.

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