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Distribution-Sensitive Multidimensional Poverty Measures

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  • Gaurav Datt

Abstract

This paper presents axiomatic arguments to make the case for distribution-sensitive multidimensional poverty measures. The commonly used counting measures violate the strong transfer axiom, which requires regressive transfers to be unambiguously poverty increasing, and they are also invariant to changes in the distribution of a given set of deprivations among the poor. The paper appeals to strong transfer as well as an additional cross-dimensional convexity property to offer axiomatic justification for distribution-sensitive multidimensional poverty measures. Given the nonlinear structure of these measures, it is also shown how the problem of an exact dimensional decomposition can be solved using Shapley decomposition methods to assess dimensional contributions to poverty. An empirical illustration for India highlights distinctive features of the distribution-sensitive measures.

Suggested Citation

  • Gaurav Datt, 2019. "Distribution-Sensitive Multidimensional Poverty Measures," The World Bank Economic Review, World Bank, vol. 33(3), pages 551-572.
    • Handle: RePEc:oup:wbecrv:v:33:y:2019:i:3:p:551-572.
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    File URL: http://hdl.handle.net/10.1093/wber/lhx017
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    Cited by:

    1. Peter Saunders & Yuvisthi Naidoo & Melissa Wong, 2022. "Comparing the Monetary and Living Standards Approaches to Poverty Using the Australian Experience," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 162(3), pages 1365-1385, August.
    2. 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).
    3. Zaira Najam & John Gibson, 2022. "Does intra‐country poverty convergence depend on spatial spillovers and the type of poverty measure? Evidence from Pakistan," Asia and the Pacific Policy Studies, Wiley Blackwell, vol. 9(3), pages 516-535, September.
    4. Gaurav Datt, 2019. "Multidimensional poverty in the Philippines, 2004–2013: How much do choices for weighting, identification and aggregation matter?," Empirical Economics, Springer, vol. 57(4), pages 1103-1128, October.
    5. Dutta, Indranil & Nogales, Ricardo & Yalonetzky, Gaston, 2021. "Endogenous weights and multidimensional poverty: A cautionary tale," Journal of Development Economics, Elsevier, vol. 151(C).
    6. Santos Maria Emma & Lustig Nora & Miranda Zanetti Maximiliano, 2023. "Counting and Accounting: Measuring the Effectiveness of Fiscal Policy in Multidimensional Poverty Reduction," Asociación Argentina de Economía Política: Working Papers 4691, Asociación Argentina de Economía Política.
    7. Zaira Najam & Susan Olivia, 2021. "Does the impact of cash transfers differ across poverty measures? Evidence from Pakistan," Working Papers in Economics 21/09, University of Waikato.
    8. Sinha, Kompal & Davillas, Apostolos & Jones, Andrew M. & Sharma, Anurag, 2021. "Do socioeconomic health gradients persist over time and beyond income? A distributional analysis using UK biomarker data," Economics & Human Biology, Elsevier, vol. 43(C).
    9. Zaira Najam & John Gibson, 2021. "Does within-country poverty convergence depend on spatial spillovers and the type of poverty measure? Evidence from Pakistan," Working Papers in Economics 21/07, University of Waikato.
    10. John Gibson & Omoniyi Alimi, 2020. "Measuring poverty with noisy and corrected estimates of annual consumption: Evidence from Nigeria," African Development Review, African Development Bank, vol. 32(1), pages 96-107, March.
    11. World Bank, 2022. "A Welfarist Theory Unifying Monetary and Non-Monetary Poverty Measurement," Policy Research Working Paper Series 10076, The World Bank.
    12. Vito Peragine & Maria G. Pittau & Ernesto Savaglio & Stefano Vannucci, 2021. "On multidimensional poverty rankings of binary attributes," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 23(2), pages 248-274, April.
    13. Salauddin Tauseef, 2022. "The Importance of Nutrition Education in Achieving Food Security and Adequate Nutrition of the Poor: Experimental Evidence from Bangladesh," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(1), pages 241-271, February.
    14. Bedük, Selçuk, 2018. "Identifying people in poverty: a multidimensional deprivation measure for the EU," SocArXiv 7prxq, Center for Open Science.
    15. 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.
    16. Balasubramanian, P. & Burchi, F. & Malerba, D., 2023. "Does economic growth reduce multidimensional poverty? Evidence from low- and middle-income countries," World Development, Elsevier, vol. 161(C).
    17. Guo, Junping & Qu, Song & Zhu, Tiehui, 2022. "Estimating China’s relative and multidimensional Poverty: Evidence from micro-level data of 6145 rural households," World Development Perspectives, Elsevier, vol. 26(C).

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