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Measuring poverty in multidimensional contexts

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  • Iñaki Permanyer

    (Centre d’Estudis Demogràfics)

Abstract

When measuring multidimensional poverty it is reasonable to expect that the trade-offs between variable pairs can differ depending on whether the concerned pairs are complements or substitutes. Yet, currently existing approaches based on deprivation count distributions unrealistically assume that all pairs of variables are related in the same way—an unfortunate circumstance that undermines the possibilities of identifying the poor, aggregating their poverty levels and modeling non-trivial interactions between variables in highly flexible ways. This paper, which aims at modeling non-trivial relational structures across variables both in the identification and aggregation steps, is a first contribution towards addressing these inadequacies. The approach has been axiomatically characterized to flesh out the normative foundations upon which it is based and has a vast potential for application.

Suggested Citation

  • Iñaki Permanyer, 2019. "Measuring poverty in multidimensional contexts," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 53(4), pages 677-708, December.
    • Handle: RePEc:spr:sochwe:v:53:y:2019:i:4:d:10.1007_s00355-019-01207-4
    DOI: 10.1007/s00355-019-01207-4
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    Cited by:

    1. Adriana Stankiewicz Serra & Gaston Isaias Yalonetzky & Alexandre Gori Maia, 2021. "Multidimensional Poverty in Brazil in the Early 21st Century: Evidence from the Demographic Census," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 154(1), pages 79-114, February.
    2. Sam Jones, 2022. "Extending multidimensional poverty identification: from additive weights to minimal bundles," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 20(2), pages 421-438, June.
    3. Vito Peragine & Maria G. Pittau & Ernesto Savaglio & Stefano Vannucci, 2021. "On multidimensional poverty rankings of binary attributes," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 23(2), pages 248-274, April.

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