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Counting poverty orderings and deprivation curves

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  • Ma. Casilda Lasso de la Vega

    (University of the Basque Country)

Abstract

Most of the data available for measuring capabilities or dimensions of poverty is either ordinal or categorical. However, the majority of the indices introduced for the assessment of multidimensional poverty behave well only with cardinal variables. The counting approach introduced by Atkinson (2003) concentrates on the number of dimensions in which each person is deprived, and is an appropriate procedure that deals well with ordinal and categorical variables. A method to identify the poor and a number of poverty indices has been proposed taking this framework into account. However, the implementation of this methodology involves the choice of a minimum number of deprivations required in order to be identified as poor. This cut-off adds arbitrariness to poverty comparisons. The aim of this paper is two-fold. Firstly, we explore properties which allow us to characterize the identification method as the most appropriate procedure to identify the poor in a multidimensional setting. Then the paper examines dominance conditions in order to guarantee unanimous poverty rankings in a counting framework. Our conditions are based on simple graphical devices that provide a tool for checking the robustness of poverty rankings to changes in the identification cut-off, and also for checking unanimous orderings in a wide set of multidimensional poverty indices that suit ordinal and categorical data.

Suggested Citation

  • Ma. Casilda Lasso de la Vega, 2009. "Counting poverty orderings and deprivation curves," Working Papers 150, ECINEQ, Society for the Study of Economic Inequality.
  • Handle: RePEc:inq:inqwps:ecineq2009-150
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    References listed on IDEAS

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    Cited by:

    1. Vincent A. Hildebrand & María Noel Pi Alperin & Philippe Van Kerm, 2017. "Measuring and Accounting for the Deprivation Gap of Portuguese Immigrants in Luxembourg," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 63(2), pages 288-309, June.
    2. 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.
    3. Mariateresa Ciommi & Gennaro Punzo & Gaetano Musella, 2019. "Evaluating the tourist satisfaction in five famous Italian cities," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 73(1), pages 29-40, January-M.
    4. Mariateresa Ciommi & Casilda Lasso de la Vega & Francesco Maria Chelli, 2014. "Evaluating deprivation in Italy using a multidimensional counting approach," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 68(1), pages 103-110, January-M.
    5. 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.
    6. Béassoum, Christian N., 2011. "Pauvreté régionale au Tchad en 2003: une situation de référence revisitée [Chad regional poverty profile in 2003: revisiting a baseline]," MPRA Paper 34505, University Library of Munich, Germany.
    7. Mariateresa Ciommi & Ernesto Savaglio, 2015. "On multidimensional diversity orderings with categorical variables," Department of Economics University of Siena 711, Department of Economics, University of Siena.
    8. Sabina Alkire & James Foster, 2011. "Understandings and misunderstandings of multidimensional poverty measurement," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(2), pages 289-314, June.
    9. Shatakshee Dhongde & Yi Li & Prasanta K. Pattanaik & Yongsheng Xu, 2016. "Binary data, hierarchy of attributes, and multidimensional deprivation," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 14(4), pages 363-378, December.
    10. Gaston Yalonetzky, 2011. "Conditions for the Most Robust Poverty Comparisons Using the Alkire-Foster Family of Measures," OPHI Working Papers ophiwp044b, Queen Elizabeth House, University of Oxford.
    11. Aristondo, Oihana & Onaindia, Eneritz, 2018. "Counting energy poverty in Spain between 2004 and 2015," Energy Policy, Elsevier, vol. 113(C), pages 420-429.
    12. Gaston Yalonetzky, 2014. "Conditions for the most robust multidimensional poverty comparisons using counting measures and ordinal variables," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 43(4), pages 773-807, December.
    13. Rolf Aaberge & Andrea Brandolini, 2014. "Social evaluation of deprivation count distributions," Working Papers 342, ECINEQ, Society for the Study of Economic Inequality.
    14. Franco-Correa, A, 2014. "An individual-centered approach to multidimensional poverty: The cases of Chile, Colombia, Ecuador and Peru," MERIT Working Papers 2014-068, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    15. José V. Gallegos & Gaston Yalonetzky, 2014. "Robust ``pro-poorest'' poverty reduction with counting measures: the non-anonymous case," Working Papers 351, ECINEQ, Society for the Study of Economic Inequality.
    16. Carmelo García-Pérez & Mercedes Prieto-Alaiz & Hipólito Simón, 2017. "A New Multidimensional Approach to Measuring Precarious Employment," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 134(2), pages 437-454, November.

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    More about this item

    Keywords

    Multidimensional poverty measurement; deprivation; counting approach; dimension adjusted headcount ratio; ordinal data;
    All these keywords.

    JEL classification:

    • I30 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General
    • 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

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