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Multidimensional poverty analysis: Looking for a middle ground

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  • Ferreira, Francisco H. G.
  • Lugo, Maria Ana

Abstract

Widespread agreement that poverty is a multifaceted phenomenon, encompassing deprivations along multiple dimensions, clashes with often vociferous disagreement about how best to measure these deprivations. Drawing on the recent literature, this short note proposes three methodological alternatives to the false dichotomy between scalar indices of multidimensional poverty, on the one hand, and a"dashboard"approach that looks only at marginal distributions, on the other. These alternatives include simple Venn diagrams of the overlap of deprivations across dimensions, multivariate stochastic dominance analysis, and the analysis of copula functions, which capture the extent of interdependency across dimensions. Examples from the literature on both developing and developed countries are provided.

Suggested Citation

  • Ferreira, Francisco H. G. & Lugo, Maria Ana, 2012. "Multidimensional poverty analysis: Looking for a middle ground," Policy Research Working Paper Series 5964, The World Bank.
  • Handle: RePEc:wbk:wbrwps:5964
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    References listed on IDEAS

    as
    1. Esfandiar Maasoumi & Maria Ana Lugo, 2008. "The Information Basis of Multivariate Poverty Assessments," Palgrave Macmillan Books, in: Nanak Kakwani & Jacques Silber (ed.), Quantitative Approaches to Multidimensional Poverty Measurement, chapter 1, pages 1-29, Palgrave Macmillan.
    2. Koen Decancq, 2014. "Copula-based measurement of dependence between dimensions of well-being," Oxford Economic Papers, Oxford University Press, vol. 66(3), pages 681-701.
    3. Chakravarty, Satya R. & Deutsch, Joseph & Silber, Jacques, 2008. "On the Watts Multidimensional Poverty Index and its Decomposition," World Development, Elsevier, vol. 36(6), pages 1067-1077, June.
    4. Nora Lustig, 2011. "Multidimensional indices of achievements and poverty: what do we gain and what do we lose? An introduction to JOEI Forum on multidimensional poverty," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 9(2), pages 227-234, June.
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    6. Nora Lustig, 2011. "Multidimensional Indices of Achievements and Poverty: What Do We Gain and What Do We," Working Papers 1121, Tulane University, Department of Economics.
    7. Koen Decancq & María Ana Lugo, 2013. "Weights in Multidimensional Indices of Wellbeing: An Overview," Econometric Reviews, Taylor & Francis Journals, vol. 32(1), pages 7-34, January.
    8. François Bourguignon & Satya R. Chakravarty, 2019. "The Measurement of Multidimensional Poverty," Themes in Economics, in: Satya R. Chakravarty (ed.), Poverty, Social Exclusion and Stochastic Dominance, pages 83-107, Springer.
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    13. Casey Quinn, 2007. "Using copulas to measure association between ordinal measures of health and income," Health, Econometrics and Data Group (HEDG) Working Papers 07/24, HEDG, c/o Department of Economics, University of York.
    14. Nora Lustig, 2011. "Multidimensional Indices of Achievements and Poverty: What Do We Gain and What Do We Lose? - Working Paper 262," Working Papers 262, Center for Global Development.
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    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Rural Poverty Reduction; Regional Economic Development; Achieving Shared Growth; Economic Theory&Research;
    All these keywords.

    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • O15 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Economic Development: Human Resources; Human Development; Income Distribution; Migration

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