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Poverty measurement with ordinal variables: A generalization of a recent contribution

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  • Gaston Yalonetzky

    () (University of Leeds and OPHI)

Abstract

Bennett and Hatzimasoura (2011) derive a new class of poverty measures suitable for ordinal variables. These indices are weighted sums of the population probabilities of attaining each state of the ordinal variable which is below the poverty line. The weights are uniquely determined by the choice of the classi?single parameter and by the number of ordinal states below the poverty line. However, as I show in this note, such restrictive propery is not necessary for the derivation of poverty measures for ordinal variables that satisfy a broad array of desirable properties, including those advocated by Bennett and Hatzimasoura. The class of measures proposed in this note include those of the authors, as a specific subclass. Since the class of admissible poverty measures for ordinal variables is unbounded, the note provides two dominance conditions whose fulfillment ensure the agreement of ordinal poverty comparisons among measures belonging to subfamilies within the class.

Suggested Citation

  • Gaston Yalonetzky, 2012. "Poverty measurement with ordinal variables: A generalization of a recent contribution," Working Papers 246, ECINEQ, Society for the Study of Economic Inequality.
  • Handle: RePEc:inq:inqwps:ecineq2012-246
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    File URL: http://www.ecineq.org/milano/WP/ECINEQ2012-246.pdf
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    References listed on IDEAS

    as
    1. Gaston Yalonetzky, 2013. "Stochastic Dominance with Ordinal Variables: Conditions and a Test," Econometric Reviews, Taylor & Francis Journals, vol. 32(1), pages 126-163, January.
    2. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
    3. Chrysanthi Hatzimasoura & Christopher J. Bennett, 2011. "Poverty Measurement with Ordinal Data," Working Papers 2011-14, The George Washington University, Institute for International Economic Policy.
    4. Allison, R. Andrew & Foster, James E., 2004. "Measuring health inequality using qualitative data," Journal of Health Economics, Elsevier, vol. 23(3), pages 505-524, May.
    5. Buhong Zheng, 2011. "A new approach to measure socioeconomic inequality in health," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(4), pages 555-577, December.
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    More about this item

    Keywords

    Poverty measurement; ordinal variables; stochastic dominance.;

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty

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