 "rural India")
Bucking the national trend, consumption inequality rose in rural areas of 11 states as the Gini coefficient of total consumption expenditure saw an increase between the periods 2011-12 and 2022-23, an analysis by the Household Consumption Expenditure Survey (HCES), released on Friday, showed.
Of the 25 states taken for analysis, Gini coefficient in rural areas has seen an increase in Bihar, Chhattisgarh, Jharkhand, Maharashtra, Manipur, Meghalaya, Mizoram, Nagaland, Sikkim, Himachal Pradesh and Rajasthan.
Comparable data for Telangana, Goa and Arunachal Pradesh was not available.
The rise in Gini coefficient was the sharpest in Nagaland (0.244 from 0.192), followed by Jharkhand (0.255 from 0.206), Maharashtra (0.291 from 0.253), Rajasthan (0.283 from 0.248), Meghalaya (0.223 from 0.19) and Chhattisgarh (0.266 from 0.234).
Meanwhile, the data also shows that the Gini coefficient for consumption expenditure has also risen in urban areas as well in three states. These are Meghalaya (0.266 from 0.226), Himachal Pradesh (0.311 from 0.29) and Manipur (0.221 from 0.209).
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This rise in Gini coefficient in these areas comes on the back of a general decline seen in the coefficient of total consumption expenditure over this time period at the national level.
At the all-India level, the Gini coefficient has gone down to 0.266 in 2022-23 from 0.283 in 2011-12 (rural areas). For urban areas, it has gone down to 0.314 from 0.363 during the same period. This fall in Gini coefficient shows a decline in spending inequality in the country.
Used to depict income inequality, the Gini coefficient measures inequality on a scale of 0 to 1. Higher values indicate higher inequality. This can sometimes be shown as a percentage from 0 to 100 per cent as the Gini Index.
Pronab Sen, chairperson, Standing Committee on Statistics, says the current HCES dataset that shows decline in consumption inequality at the national level is an outlier. This is because increase in income inequality in India is a widely accepted and corroborated phenomenon of the past three decades.
“Affluent households typically do not report their spending well and now with the survey spanning over three visits, the chances of data being faulty have increased. It (index) is overly sensitive to certain income quartiles. It doesn't capture very explicitly changes in the affluent quartiles. That has been a problem with data collection techniques in the NSSO surveys for a long time, especially in urban areas. So, to conclude with this set of data that spending inequality has come down in the past decade is not correct. A lot of other datasets point to the contrary. Then, there are questions on the comparability of this round with the previous rounds as well,” he added.
