Mapping Multidimensional Poverty in India: Spatial Patterns and Determinants

This study investigates the spatial distribution and key drivers of multidimensional poverty (MDP) across Indian districts, employing data from the National Family Health Survey (NFHS-5) 2019–2021. Significant regional inequalities are revealed, with poverty concentrated in specific areas of Uttar Pradesh, Bihar, Jharkhand, Chhattisgarh, Odisha and parts of Assam. Spatial econometric modelling identifies critical socio-ethnic factors (including Muslim and Scheduled Tribe populations, rural residence, primary-sector employment and education levels) and infrastructural determinants (such as access to all-weather roads, school infrastructure and health insurance) as major drivers of MDP. The findings, based on the Spatial Error Model, highlight the interconnectedness of these factors and the need for comprehensive, spatially targeted interventions. Addressing regional disparities through integrated infrastructural improvements and social programmes is essential for effective poverty alleviation. Specifically, the study recommends prioritizing investments in primary healthcare, insurance coverage, electricity, school infrastructure and road construction to reduce MDP and promote more inclusive development in India. JEL Codes: O12, R12, O15, I32, C21, I38

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Publication Details

Journal
South Asia Economic Journal
Published
2026-08-03
DOI
https://doi.org/10.1177/13915614261463101
Primary Topic
Income, Poverty, and Inequality
Type
article
Field-Weighted Citation Impact
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article

Mapping Multidimensional Poverty in India: Spatial Patterns and Determinants

Poulomi Roy, Dipsa Midya
South Asia Economic Journal
Income, Poverty, and Inequality
article

Mapping Multidimensional Poverty in India: Spatial Patterns and Determinants

Poulomi Roy, Dipsa Midya
article en

Abstract

This study investigates the spatial distribution and key drivers of multidimensional poverty (MDP) across Indian districts, employing data from the National Family Health Survey (NFHS-5) 2019–2021. Significant regional inequalities are revealed, with poverty concentrated in specific areas of Uttar Pradesh, Bihar, Jharkhand, Chhattisgarh, Odisha and parts of Assam. Spatial econometric modelling identifies critical socio-ethnic factors (including Muslim and Scheduled Tribe populations, rural residence, primary-sector employment and education levels) and infrastructural determinants (such as access to all-weather roads, school infrastructure and health insurance) as major drivers of MDP. The findings, based on the Spatial Error Model, highlight the interconnectedness of these factors and the need for comprehensive, spatially targeted interventions. Addressing regional disparities through integrated infrastructural improvements and social programmes is essential for effective poverty alleviation. Specifically, the study recommends prioritizing investments in primary healthcare, insurance coverage, electricity, school infrastructure and road construction to reduce MDP and promote more inclusive development in India. JEL Codes: O12, R12, O15, I32, C21, I38

South Asia Economic Journal
Jadavpur University (IN)
No poverty
Openalex Percentile: Top 4%
Income, Poverty, and Inequality
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