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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.

Suggested Citation

  • Gaston Yalonetzky, 2012. "Conditions for the most robust multidimensional poverty comparisons using counting measures and ordinal variables," Working Papers 257, ECINEQ, Society for the Study of Economic Inequality.
    • Handle: RePEc:inq:inqwps:ecineq2012-257
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    Cited by:

    1. Espinoza-Delgado, José & Silber, Jacques, 2018. "Multi-dimensional poverty among adults in Central America and gender differences in the three I’s of poverty: Applying inequality sensitive poverty measures with ordinal variables," MPRA Paper 88750, University Library of Munich, Germany.
    2. Lucio Esposito & Enrica Chiappero‐Martinetti, 2019. "Eliciting, Applying And Exploring Multidimensional Welfare Weights: Evidence From The Field," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 65(S1), pages 204-227, November.
    3. José V. Gallegos & Gaston Yalonetzky, 2015. "Robust ``pro-poorest'' poverty reduction with counting measures: The anonymous case," Working Papers 361, ECINEQ, Society for the Study of Economic Inequality.
    4. 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.
    5. Alkire, Sabina & Oldiges, Christian & Kanagaratnam, Usha, 2021. "Examining multidimensional poverty reduction in India 2005/6–2015/16: Insights and oversights of the headcount ratio," World Development, Elsevier, vol. 142(C).
    6. Iñaki Permanyer & M. Azhar Hussain, 2018. "First Order Dominance Techniques and Multidimensional Poverty Indices: An Empirical Comparison of Different Approaches," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 137(3), pages 867-893, June.
    7. Alkire, Sabina & Santos, Maria Emma, 2014. "Measuring Acute Poverty in the Developing World: Robustness and Scope of the Multidimensional Poverty Index," World Development, Elsevier, vol. 59(C), pages 251-274.
    8. Espinoza-Delgado, José & Klasen, Stephan, 2018. "Gender and multidimensional poverty in Nicaragua: An individual based approach," World Development, Elsevier, vol. 110(C), pages 466-491.
    9. Rodríguez Guerrero, Esmeralda & Nimeh, Zina & Franco Correa, Andrea, 2021. "Women's empowerment in Colombia: A multidimensional approach," MERIT Working Papers 2021-028, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    10. Jacques SILBER & Jose Espinoza-Delgado, 2023. "A rank-dependent multidimensional deprivation index (MDI) for binary data," Working Papers 641, ECINEQ, Society for the Study of Economic Inequality.
    11. M. Azhar Hussain & Nikolaj Siersbæk & Lars Peter Østerdal, 2020. "Multidimensional welfare comparisons of EU member states before, during, and after the financial crisis: a dominance approach," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 55(4), pages 645-686, December.
    12. Francisco Azpitarte & Jose Gallegos & Gaston Yalonetzky, 2020. "On the robustness of multidimensional counting poverty orderings," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(3), pages 339-364, September.
    13. Valérie Bérenger, 2017. "Using ordinal variables to measure multidimensional poverty in Egypt and Jordan," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 15(2), pages 143-173, June.
    14. Deutsch, Joseph & Silber, Jacques & Wan, Guanghua & Zhao, Mengxue, 2020. "Asset indexes and the measurement of poverty, inequality and welfare in Southeast Asia," Journal of Asian Economics, Elsevier, vol. 70(C).
    15. Angelo Moretti & Natalie Shlomo & Joseph W. Sakshaug, 2020. "Multivariate Small Area Estimation of Multidimensional Latent Economic Well‐being Indicators," International Statistical Review, International Statistical Institute, vol. 88(1), pages 1-28, April.
    16. Sabina Alkire & Usha Kanagaratnam & Ricardo Nogales & Nicolai Suppa, 2022. "Revising the Global Multidimensional Poverty Index: Empirical Insights and Robustness," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 68(S2), pages 347-384, December.
    17. Rolf Aaberge & Andrea Brandolini, 2014. "Social evaluation of deprivation count distributions," Working Papers 342, ECINEQ, Society for the Study of Economic Inequality.
    18. 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.
    19. Angelo Moretti & Natalie Shlomo & Joseph W. Sakshaug, 2021. "Small Area Estimation of Latent Economic Well-being," Sociological Methods & Research, , vol. 50(4), pages 1660-1693, November.
    20. Bassma Said Jellali, 2019. "Assessing Policy Effectiveness to Measure Inequality of Opportunity in Wellbeing and Education: Case of Tunisia," International Journal of Applied Economics, Finance and Accounting, Online Academic Press, vol. 5(2), pages 65-77.
    21. Valérie Bérenger, 2017. "Using ordinal variables to measure multidimensional poverty in Egypt and Jordan," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 15(2), pages 143-173, June.
    22. Albert Hizgilov & Jacques Silber, 2020. "On Multidimensional Approaches to Financial Literacy Measurement," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(3), pages 787-830, April.
    23. Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2020. "On the construction of a feasible range of multidimensional poverty under benchmark weight uncertainty," European Journal of Operational Research, Elsevier, vol. 281(2), pages 415-427.

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    More about this item

    Keywords

    Multidimensional poverty; stochastic dominance;

    JEL classification:

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

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