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Geospatial Multidimensional Poverty Gap in India: A rural and urban decomposition analysis

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  • Gupta, Pallavi

Abstract

This paper examines the geographical distribution of multidimensional poverty in rural and urban India for the year 2021, utilising secondary data sourced from the NITI Aayog report 2021 based on the NFHS-4 dataset. The 2021 MPI, based on Alkire and Foster methodology, encompasses three dimensions—health, education, and standard of living—comprising twelve indicators. An in-depth analysis of interstate deprivation across diverse indicators within the rural and urban Multidimensional Poverty Index (MPI) highlights heightened levels of deprivation in economically challenged states like Madhya Pradesh, Bihar, Uttar Pradesh, and Jharkhand. A comprehensive decomposition analysis has been undertaken to identify the principal contributors to multidimensional poverty. The outcomes emphasise the critical role of health as a pivotal dimension, with nutrition emerging as the foremost factor influencing the overall MPI in both rural and urban contexts. These findings underscore the necessity for targeted policies aimed at poverty eradication, with a specific focus on strategic interventions in health and nutrition. The insights offer valuable perspectives for development planners and policymakers, contributing to a nuanced understanding of the intricate patterns of multidimensional poverty across Indian states.

Suggested Citation

  • Gupta, Pallavi, 2023. "Geospatial Multidimensional Poverty Gap in India: A rural and urban decomposition analysis," MPRA Paper 120408, University Library of Munich, Germany, revised 02 Dec 2023.
    • Handle: RePEc:pra:mprapa:120408
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    References listed on IDEAS

    as
    1. Sanjay K. Mohanty & Guru Vasishtha, 2021. "Contextualizing multidimensional poverty in urban India," Poverty & Public Policy, John Wiley & Sons, vol. 13(3), pages 234-253, September.
    2. Alkire, Sabina & Foster, James, 2011. "Counting and multidimensional poverty measurement," Journal of Public Economics, Elsevier, vol. 95(7), pages 476-487.
    3. Sabina Alkire & Maria Emma Santos, 2010. "Acute Multidimensional Poverty: A New Index for Developing Countries," Human Development Research Papers (2009 to present) HDRP-2010-11, Human Development Report Office (HDRO), United Nations Development Programme (UNDP).
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    5. Sabyasachi Tripathi & Komali Yenneti, 2020. "Measurement of Multidimensional Poverty in India: A State-level Analysis," Indian Journal of Human Development, , vol. 14(2), pages 257-274, August.
    6. repec:qeh:ophiwp:ophiwp038 is not listed on IDEAS
    7. 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.
    8. Harald Strotmann & Jürgen Volkert, 2018. "Multidimensional Poverty Index and Happiness," Journal of Happiness Studies, Springer, vol. 19(1), pages 167-189, January.
    9. Venugopal Mothkoor & Nina Badgaiyan, 2021. "Estimates of multidimensional poverty for India using NSSO-71 and -75," WIDER Working Paper Series wp-2021-1, World Institute for Development Economic Research (UNU-WIDER).
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    1. Gupta, Pallavi, 2024. "A Systematic Review on Women's Participation in Agricultural Work and Nutritional Outcomes," MPRA Paper 124283, University Library of Munich, Germany.

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    Keywords

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    JEL classification:

    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs
    • J11 - Labor and Demographic Economics - - Demographic Economics - - - Demographic Trends, Macroeconomic Effects, and Forecasts

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