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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.

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File URL: http://www.ecineq.org/milano/WP/ECINEQ2009-150.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 150.

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Length: 20 pages
Date of creation: 2009
Date of revision:
Handle: RePEc:inq:inqwps:ecineq2009-150

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Related research

Keywords: Multidimensional poverty measurement; deprivation; counting approach; dimension adjusted headcount ratio; ordinal data;

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References

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  1. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-66, May.
  2. A. Atkinson, 2003. "Multidimensional Deprivation: Contrasting Social Welfare and Counting Approaches," Journal of Economic Inequality, Springer, vol. 1(1), pages 51-65, April.
  3. Sen, Amartya K, 1976. "Poverty: An Ordinal Approach to Measurement," Econometrica, Econometric Society, vol. 44(2), pages 219-31, March.
  4. Russell Davidson & Jean-Yves Duclos, 2013. "Testing for Restricted Stochastic Dominance," Econometric Reviews, Taylor & Francis Journals, vol. 32(1), pages 84-125, January.
  5. Yélé Batana, 2013. "Multidimensional Measurement of Poverty Among Women in Sub-Saharan Africa," Social Indicators Research, Springer, vol. 112(2), pages 337-362, June.
  6. Zheng, Buhong, 2000. " Poverty Orderings," Journal of Economic Surveys, Wiley Blackwell, vol. 14(4), pages 427-66, September.
  7. Shorrocks, Anthony F, 1983. "Ranking Income Distributions," Economica, London School of Economics and Political Science, vol. 50(197), pages 3-17, February.
  8. Anthony Shorrocks, 2009. "On the measurement of unemployment," Journal of Economic Inequality, Springer, vol. 7(3), pages 311-327, September.
  9. Foster, James E & Shorrocks, Anthony F, 1988. "Poverty Orderings," Econometrica, Econometric Society, vol. 56(1), pages 173-77, January.
  10. Alkire, Sabina & Foster, James, 2011. "Counting and multidimensional poverty measurement," Journal of Public Economics, Elsevier, vol. 95(7-8), pages 476-487, August.
  11. Yélé Maweki Batana & Jean-Yves Duclos, 2008. "Multidimensional Poverty Dominance: Statistical Inference and an Application to West Africa," Cahiers de recherche 0808, CIRPEE.
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Cited by:
  1. 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.
  2. Sabina Alkire & James Foster, 2011. "Understandings and misunderstandings of multidimensional poverty measurement," Journal of Economic Inequality, Springer, vol. 9(2), pages 289-314, June.
  3. 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.
  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 - Italian Review of Economics, Demography and Statistics, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 0(1), pages 103-110, January-M.
  5. 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.
  6. 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.

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