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Regional Perspectives on the Multidimensional Poverty Index

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  • Pasha, Atika

Abstract

This paper analyzes the consequences of an alternative weighting scheme for the Multidimensional Poverty Index (MPI), using a data-driven approach, as opposed to the currently employed equal weighting scheme. This weighting scheme has been under strong scrutiny since the MPI's inception, given the sensitivity of country rankings to different weights and indicator choices. Therefore, the current study employs Multiple Correspondence Analysis (MCA) for weighting of the indicators and investigates its impact on the scores and relative ranking of 28 countries. The results show that equal weighting of the three dimensions cannot be statistically justified. Moreover, the statistical weights differ systematically across countries, implying differences in deprivations across regions, although household poverty rankings are highly correlated between normative and statistical weights. Given the high correlation between all indicators employed within the MPI, a large overlap is found in the information, implying that there might not actually be so much multidimensionality within the dimensions of the MPI.

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  • Pasha, Atika, 2017. "Regional Perspectives on the Multidimensional Poverty Index," World Development, Elsevier, vol. 94(C), pages 268-285.
    • Handle: RePEc:eee:wdevel:v:94:y:2017:i:c:p:268-285
    DOI: 10.1016/j.worlddev.2017.01.013
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    10. Dutta, Indranil & Nogales, Ricardo & Yalonetzky, Gaston, 2021. "Endogenous weights and multidimensional poverty: A cautionary tale," Journal of Development Economics, Elsevier, vol. 151(C).
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    13. Migbaru Alamirew Workneh, 2020. "Nonmonetary poverty in Ethiopia: Multidimensional approach," Poverty & Public Policy, John Wiley & Sons, vol. 12(4), pages 326-356, December.
    14. Thereza Balliester Reis, 2022. "Socio‐economic determinants of financial inclusion: An evaluation with a microdata multidimensional index," Journal of International Development, John Wiley & Sons, Ltd., vol. 34(3), pages 587-611, April.
    15. Héctor E. Nájera Catalán, 2019. "Reliability, Population Classification and Weighting in Multidimensional Poverty Measurement: A Monte Carlo Study," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 142(3), pages 887-910, April.
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    17. Sam Jones, 2019. "Counting-based multidimensional poverty identification: From deprivation weights to bundles," WIDER Working Paper Series wp-2019-55, World Institute for Development Economic Research (UNU-WIDER).
    18. Sabina Alkire, 2018. "The Research Agenda on Multidimensional Poverty Measurement: Important and As-yet Unanswered Questions," OPHI Working Papers ophiwp119_3.pdf, Queen Elizabeth House, University of Oxford.
    19. Jinfang Wang & Hui Xiao & Xiaojin Liu, 2022. "The Impact of Social Capital on Multidimensional Poverty of Rural Households in China," IJERPH, MDPI, vol. 20(1), pages 1-16, December.
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    22. Ismaila Rimi Abubakar, 2022. "Multidimensional Poverty among Nigerian Households: Sustainable Development Implications," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(2), pages 993-1014, November.

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