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Uneven burden of multidimensional poverty in India: A caste based analysis.

Itishree PradhanBinayak KandapanJalandhar Pradhan
Published in: PloS one (2022)
Poverty is multifaceted. The global poverty profile shows 41% of multidimensionally poor people living in South Asian countries. Though castes and tribes are a more prevalent line of social stratification in India, and their socio-economic characteristics also vary remarkably, hardly any study has explored these dimensions while analysing multidimensional poverty in India. Hence, this study attempts to assess the multidimensional status of poverty among the social groups in India. National Family Health Survey, 2015-16 (NFHS-4) is a source of rich information on 579,698 households' well-being for this analysis. Alkire- Foster technique was applied to decompose the Multidimensional Poverty Index (M0) across its dimensions and indicators for all the social groups. Three broad dimensions of deprivation-Health, Education and Standard of Living-include 12 indicators, guided by the poverty literature, data availability and the country's sustainable Development Goals (SDGs). There were three main findings in this study: (1) Scheduled Tribes (STs) are the most disadvantaged subgroup in India with remarkably high values of headcount (H = 0.444;), intensity (A = 0.486), and M0 (0.216), followed by Scheduled Castes (SCs) (H = 0.292; A = 0.473; M0 = 0.138), and Other Backward Classes (OBCs) (H = 0.245; A = 0.465; M0 = 0.114); and Others category is the most privileged with very low values of H = 0.149, A = 0.463, and M0 = 0.069; (2) STs contribute nearly twice their population share for both H and M0, and the SCs contribution is also noticeably higher than their population share; (3) States located in the central and eastern regions of India have the higher H, A and M0 for all the social groups. This suggests that there is a need for a thorough assessment of poverty at specific levels to uncover the poverty situation in society, improve the effectiveness of evidence-based planning and effective policymaking.
Keyphrases
  • healthcare
  • mental health
  • randomized controlled trial
  • risk factors
  • big data
  • social media
  • climate change
  • open label