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Poverty Measurement with Ordinal Data

Author

Listed:
  • Chrysanthi Hatzimasoura

    (Department of Economics, George Washington University)

  • Christopher J. Bennett

    (Department of Economics, Vanderbilt University.)

Abstract

The Foster, Greer, Thorbecke (1984) class nests several of the most widely used mea- sures in theoretical and empirical work on economic poverty. Use of this general class of measures, however, presupposes a dimension of well-being that, like income, is cardinally measurable. Responding to recent interest in dimensions of well-being where achievements are recorded on an ordinal scale, this paper develops counterparts to the popular FGT measures that are still meaningful when applied to ordinal data. The resulting ordinal FGT measures retain the simplicity of the classical FGT measures and also many of their desirable features, including additive decomposability. This paper also develops ordinal analogues of the core axioms from the literature on economic poverty, and demonstrates that the ordinal FGT measures indeed satisfy these core axioms. Moreover, new domi- nance conditions, which allow for poverty rankings that are robust with respect to the choice of poverty line, are established. Lastly, the ordinal FGT measures are illustrated using self-reported data on health status in Canada and the United States.

Suggested Citation

  • Chrysanthi Hatzimasoura & Christopher J. Bennett, 2011. "Poverty Measurement with Ordinal Data," Working Papers 2011-14, The George Washington University, Institute for International Economic Policy.
  • Handle: RePEc:gwi:wpaper:2011-14
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    References listed on IDEAS

    as
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    Cited by:

    1. Clarke, Philip & Erreygers, Guido, 2020. "Defining and measuring health poverty," Social Science & Medicine, Elsevier, vol. 244(C).
    2. Marta Pascual & David Cantarero & Paloma Lanza, 2018. "Health polarization and inequalities across Europe: an empirical approach," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(8), pages 1039-1051, November.
    3. Bénédicte Apouey & David Madden, 2023. "Health poverty," Chapters, in: Jacques Silber (ed.), Research Handbook on Measuring Poverty and Deprivation, chapter 19, pages 202-211, Edward Elgar Publishing.
    4. Michal Brzezinski, 2015. "Accounting for trends in health poverty: a decomposition analysis for Britain, 1991–2008," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 16(2), pages 153-159, March.
    5. Best, Rohan & Hammerle, Mara & Mukhopadhaya, Pundarik & Silber, Jacques, 2021. "Targeting household energy assistance," Energy Economics, Elsevier, vol. 99(C).
    6. Silber, Jacques & Yalonetzky, Gaston, 2021. "Measuring welfare, inequality and poverty with ordinal variables," GLO Discussion Paper Series 962, Global Labor Organization (GLO).
    7. 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.
    8. Suman Seth and Gaston Yalonetzky, 2018. "Assessing Deprivation with Ordinal Variables: Depth Sensitivity and Poverty Aversion," OPHI Working Papers ophiwp123.pdf, Queen Elizabeth House, University of Oxford.
    9. Pascual-Sáez, Marta & Cantarero-Prieto, David & Lanza-León, Paloma, 2019. "The dynamics of health poverty in Spain during the economic crisis (2008–2016)," Health Policy, Elsevier, vol. 123(10), pages 1011-1018.
    10. Suman Seth & Gaston Yalonetzky, 2021. "Assessing Deprivation with an Ordinal Variable: Theory and Application to Sanitation Deprivation in Bangladesh," The World Bank Economic Review, World Bank, vol. 35(3), pages 793-811.
    11. Martyna Kobus & Olga Półchłopek & Gaston Yalonetzky, 2019. "Inequality and Welfare in Quality of Life Among OECD Countries: Non-parametric Treatment of Ordinal Data," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 143(1), pages 201-232, May.
    12. Christopher Bennett & Ričardas Zitikis, 2015. "Ignorance, lotteries, and measures of economic inequality," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 13(2), pages 309-316, June.

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    More about this item

    Keywords

    poverty measurement; ordinal data; FGT poverty measures; social welfare; dominance conditions;
    All these keywords.

    JEL classification:

    • I3 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • D63 - Microeconomics - - Welfare Economics - - - Equity, Justice, Inequality, and Other Normative Criteria and Measurement
    • O1 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development

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