Statsguru: Six charts explain another dimension of poverty in India

The latest global multidimensional poverty index (MPI) report does not have any new data from India — the last analysis was based on NFHS 2015-16 data. Researchers have, however, found a new dimension to multidimensional poverty in the country.
 
The report highlights that differences among social groups define the incidence and intensity of poverty. Five of the six multidimensional poor in the country belonged to lower social groups, with Scheduled Tribe (ST) population at the bottom of the pyramid. The incidence of poverty or the headcount ratio was the highest among STs. Over half of the ST population was multidimensionally poor, followed by Scheduled Caste groups, where a third were affected by multidimensional poverty.

The all-India average was 27.9 per cent (chart 1). The intensity of multidimensional poverty, which illustrates the average share of deprivation experienced by the poor, was marginally higher for STs (chart 2).

 

The latest MPI is based on a paper, “Examining multidimensional poverty reduction in India 2005/6–2015/16: Insights and oversights of the headcount ratio”, published by Sabina Alkire, Christian Oldiges and Usha Kanagaratnam earlier this year. The paper analysing results from NFHS 2015-16 also shows the difference in incidence and intensity of multidimensional poverty among religious groups. Muslims had a higher headcount ratio, followed by Hindus and Christians (chart 3).

The All India Debt and Investment Survey (AIDIS), released last month, based on 2018 data, illustrates similar trends regarding asset holdings of social groups. About 98.8 per cent of ST households in rural areas had assets vis-à-vis 99.4 per cent national average. In urban areas, the divide was even starker with only 93 per cent of ST households having assets, compared to 98 per cent national average.

 
Even though the MPI indicates a higher incidence of poverty in Other Backward Classes than “Others” category, AIDIS data showed that their asset holdings in both rural and urban areas were higher than the “Others” category (chart 4). The average value of assets was higher for STs than SCs, as per AIDIS data. Rural inequality was higher than urban inequality (chart 5).
 

The multidimensional poverty index or the AIDIS data does not show the depravation caused by the Covid-19 pandemic. A Pew Research Centre study indicates that India may have added 75 million poor because of the disruption (chart 6).

StatsGuru is a weekly feature. Every Monday, Business Standard guides you through the numbers you need to know to make sense of the headlines