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Conditions for the most robust multidimensional poverty comparisons using counting measures and ordinal variables

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  • Gaston Yalonetzky

    ()
    (University of Leeds & OPHI)

Abstract

A natural concern with multivariate poverty measures, as well as with other composite indices, is the robustness of their ordinal comparisons to changes in the indices’ parameter values. Applying multivariate stochastic dominance techniques, this paper derives the distributional conditions under which a multidimensional poverty comparison based on the popular counting measures, and ordinal variables, is fully robust to any values of the indices.parameters. As the paper shows, the conditions are relevant to most of the multidimensional poverty indices in the literature, including the Alkire-Foster family, upon which the UNDP.s "Multidimensional Poverty Index" (MPI) is based. The conditions are illustrated with an example from the EU-SILC dataset.

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File URL: http://www.ecineq.org/milano/WP/ECINEQ2012-257.pdf
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Bibliographic Info

Paper provided by ECINEQ, Society for the Study of Economic Inequality in its series Working Papers with number 257.

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Length: 24 pages
Date of creation: Jun 2012
Date of revision:
Handle: RePEc:inq:inqwps:ecineq2012-257

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Web page: http://www.ecineq.org
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Keywords: Multidimensional poverty; stochastic dominance;

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Cited by:
  1. Sabina Alkire and Maria Emma Santos, 2013. "Measuring Acute Poverty in the Developing World: Robustness and Scope of the Multidimensional Poverty Index," OPHI Working Papers ophiwp059, Queen Elizabeth House, University of Oxford.

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