Regional Estimates of Multidimensional Poverty in India

Dehury, Bidyadhar; Mohanty, Sanjay K.

doi:10.5018/economics-ejournal.ja.2015-36

Cited by 31 publications

(33 citation statements)

References 27 publications

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“…However, in contrast to scheduled castes, scheduled tribes are more likely to be marginal poor and vulnerable. Dehury and Mohanty (2015) have estimated the regional level multidimensional poverty in India using the Indian Human Development Survey (IHDS), 2004-05 data. Results indicate that about half of India's populations are multidimensional poor with large regional variations.…”

Section: Literature Review and Objectivesmentioning

confidence: 99%

Multidimensional Poverty: An Exploratory Study in Purulia District, West Bengal

Bagli¹

2019

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This paper explores the incidence and extent of multidimensional poverty for the households in Purulia district, the western most backward district of West Bengal in India. In context of Purulia district the decompositions of multidimensional poverty index (MPI) across the social castes and across the indicators have also been explained. MPI and its decomposition across the sub-groups have been computed using the methodology developed by Alkire and Foster (2007) and . This study covers twelve non income indicators under three dimensions education, health and living conditions. Collecting a set of primary data from 698 households in Purulia district during 2018, this study reveals that the incidence of multidimensional poverty in the district of Purulia is higher than that in national level. But the breadth of poverty is almost equal to that in India as a whole. In respect of poverty there is wide variation across the social castes. Among the indicators, use of dirty cooking fuel, not having improved sanitation have highest contribution to the district MPI.Highlights m This paper explores the incidence of multidimensional poverty for the households in Purulia district which is double in figure compared to that in India as a whole. Deprivation in access to improved sanitation is identified as the crucial indicator contributing highest in MPI of Purulia district.

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Section: Literature Review and Objectivesmentioning

confidence: 99%

Multidimensional Poverty: An Exploratory Study in Purulia District, West Bengal

Bagli¹

2019

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“…Reduction of multidimensional poverty is a prerequisite for improving the state of human development. However, the national pattern of multidimensional poverty conceals large variations across states, regions, rural and urban areas, and socioeconomic groups (Dehury & Mohanty, 2015). Disaggregated analyses on multidimensional poverty are of immense help in framing evidence-based policies.…”

Section: Introductionmentioning

confidence: 99%

Contextualizing multidimensional poverty in urban India

Mohanty

Vasishtha

2021

Poverty & Public Policy

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Urban poverty is complex and conventional money-metric poverty fails to measure the multiple deprivations of the urban population. Though recent estimates of multidimensional poverty do capture multiple deprivations, they do not capture the extent of multidimensional poverty in urban India. Using the urban sample from the National Family Health Survey, 2015-16, this paper estimates and decomposes multidimensional poverty in urban India. Urban poverty is measured in four key domains: Education, health, standard of living, and housing. A multilevel logistic model is used to decompose the variations in multidimensional poverty across geographical regions. Results suggest that about one-third of the urban Indian population is multidimensionally poor and one-sixth is vulnerable to multidimensional poverty. The state patterns of multidimensional poverty were diverse, with more than half of the urban population in Manipur and Bihar being multidimensionally poor, followed by Nagaland and Uttar Pradesh. On controlling for household characteristics, 17.5% of the total variation in multidimensional poverty was attributable to census enumeration blocks, 6.6% to districts, 1.8% to regions, and 9.9% to states. The odds of multidimensional poverty were higher among large households, female-headed households, widowed, and scheduled tribes. Contextualizing multidimensional poverty and prioritizing vulnerable groups and regions are essential for reducing multidimensional poverty in urban India.

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“…Our study also uses NSSO data, which is available for as recently as 2017-18. Our study will augment similar research that uses NSSO data to measure MPI (Chaudhuri et al 2017;Dehury and Mohanty 2015;Kumar et al 2015;Sarkar 2012;Tripathi and Yenneti 2019). This study estimates the MPI using four dimensions-health, education, income, and standard of living-for each household in both rural and urban areas using NSSO data from the NSSO 71st (2014-15) and 75th rounds .…”

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confidence: 57%

Estimates of multidimensional poverty for India using NSSO-71 and -75

Mothkoor¹,

Badgaiyan²

2021

WIDER Working Paper

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We measure multidimensional poverty in India using National Sample Survey Organization data from 2014–15 to 2017–18. We use income, health, education, and standard of living to measure the multidimensional poverty index (MPI). The MPI headcount declined from 26.9 to 13.75 per cent over the study period. The all-India estimates indicate that 144 million people were lifted from poverty during this period. We include different health dimensions, factoring in insurance, institutional coverage, antenatal care, and chronic conditions. Income is the dominant instrument with the highest contribution to the MPI, followed by insurance. Cooking, sanitation, and education also have significant weights. The decline in deprivation is steeper in rural areas than urban areas. Our state-level estimates reveal that 20 states report less than 10 per cent headcount poverty, up from six states. COVID-19 may lead to reversals of these gains, with poverty rising to pre-2014–15 levels, rising more steeply in rural areas.

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Regional Estimates of Multidimensional Poverty in India

Cited by 31 publications

References 27 publications

Multidimensional Poverty: An Exploratory Study in Purulia District, West Bengal

Multidimensional Poverty: An Exploratory Study in Purulia District, West Bengal

Contextualizing multidimensional poverty in urban India

Estimates of multidimensional poverty for India using NSSO-71 and -75

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