Journal Press India^®

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This research investigates the spatial distribution and intensity of multidimensional poverty in India for the year 2021, using secondary data from the NITI Aayog report 2021, which is based on the NFHS-4 dataset. The 2021 Multidimensional Poverty Index (MPI), calculated using the Alkire and Foster methodology, includes three dimensions—health, education, and standard of living—comprising twelve indicators. The study identifies heightened levels of deprivation in economically challenged states such as Bihar, Madhya Pradesh, Uttar Pradesh, and Jharkhand. A detailed analysis was conducted to determine the primary causes of multidimensional poverty, revealing that health, particularly nutrition, is a significant factor affecting the MPI. The findings underscore the need for targeted policies aimed at eradicating poverty, with a particular focus on timely health and nutrition interventions. These insights offer a deeper understanding of the complex patterns of multidimensional poverty across Indian states, providing valuable perspectives for development planners and policymakers.

Keywords

Poverty in India, Multidimensional poverty, Multidimensional Poverty Index (MPI), Spatial pattern of poverty, Deprivation

1. Alkire, S. & Foster, J. (2011). Counting and multidimensional poverty measurement. Journal of Public Economics, 95,  476–487.
2. Alkire, S. & Seth, S. (2008). Measuring multidimensional poverty in India: A new proposal. OPHI Working Paper 15, Oxford Poverty and Human Development Initiative (OPHI), University of Oxford.
3. Alkire, S. & Seth, S. (2015). Multidimensional poverty reduction in India between 1999 and 2006: Where and how? World Development, 72, 93–108.
4. Ataguba, J. E., Ichoku, H. E. & Fonta, W. M. (2013). Comparing poverty and deprivation between money-metric and multidimensional measures in Nigeria. Journal of Poverty, 17(4), 543-559.
5. Bisiaux, A. (2013). Poverty measurement: Differences and complementarities between monetary poverty, primary good deprivation, and capability approaches. Cahiers du GREThA, 2013-23.
6. Dehury, B. & Mohanty, S. (2015). Regional estimates of multidimensional poverty in India. Economics, 9, 1-35.
7. Kumar, V. S., Kumar, & Sonu, (2015). Multi-dimensional poverty index (MPI): A state wise study of India in SAARC countries. International Journal of Enhanced Research in Educational Development, 3, 14-21.
8. Sen, A. (1976). Poverty: An ordinal approach to measurement. Econometrica: Journal of the Econometric Society, 44(2), 219–231. Retrieved from https://doi.org/1912718
9. Suppa, N. (2016). Comparing monetary and multidimensional poverty in Germany. Review of Income and Wealth, 62(3), 478-498.
10. Tran, T. Q., Nguyen, C. V. & Nguyen, M. H. (2014). Does economic growth reduce poverty in Vietnam? Evidence from a panel data analysis. Asian Social Work and Policy Review, 8(2), 112-125.
11. Tripathi, S.  & Yenneti, K. (2020). Measurement of multidimensional poverty in India: A State-level analysis. Indian Journal of Human Development, 14, 257–274.
12. UNDP (2015). Human development report 2015: Work for human development. United Nations Development Programme. Retrieved from http://hdr.undp.org/sites/default/files/ 2015_human_development_report.pdf
13. UNDP (2019). The 2019 Global Multidimensional Poverty Index (MPI). Retrieved from http://hdr.undp.org/en/2019-MPI
14. United Nations Development Programme (UNDP). (2015). Human development report 2015: Work for human development. New York: United Nations Development Programme.
15. Wang, X., Feng, H., Xia, Q., & Alkire, S. (2016). On the relationship between income poverty and multidimensional poverty in China. Oxford Development Studies, 44(2),      218-240.