Opinion Express View on poverty estimation in India: Mind the data gaps

Estimates of poverty and inequality in India have been deeply contested. Differences exist among economists not only on data which forms the basis of their estimation, but also on trends over past decades. In the absence of official data for recent years — the last consumption expenditure survey, which forms the basis of poverty and inequality estimates, was for 2011-12 — the issue has been particularly contentious. More so, given the sharp differences of opinion on the extent to which the pandemic exacerbated poverty and inequality. In the absence of official data, several economists have put forth their estimates based on different data sources. For instance, Arvind Panagariya and Vishal More, using PLFS data, find that rural poverty “saw a modest rise” only during the strict lockdown period of April-June 2020, and then declined as sharply as in the pre-Covid period. And that while urban poverty also saw a “modest rise” in 2020-21, by April-June 2021 its decline had resumed.

These trends are, however, at odds with studies that draw on other data sources to estimate poverty. In the “State of working India 2021” report, economists at Azim Premji University, based on CMIE data, found that the pandemic led to a “sudden increase in poverty”. As per the report, over an eight month period (March to October 2020), average incomes of the bottom 10 per cent of households were lower by Rs 15,700. This income shock caused an increase in the poverty rate (below the national minimum wage threshold) by 15 percentage points in rural areas and nearly 20 percentage points in urban areas. Research by Arpit Gupta, Anup Malani and Bartosz Woda, based on CMIE data, found that income poverty, applying the World Bank’s $1.9 cutoff, rose from 7.6 per cent in November 2019 to 50.5 per cent in April 2020. And that while poverty did fall subsequently, it did not recover to pre-pandemic levels. Other indicators suggest that more workers fell back on agriculture indicating the absence of non-farm employment. More individuals worked under MGNREGA than in the pre-pandemic period. Regular real wages witnessed a decline. And, sales of two-wheelers remain subdued.

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In the absence of official consumption expenditure data, reliance on alternate data sources has only risen, giving rise to conflicting trends. As understanding the trends in poverty and inequality, and their underlying reasons, is critical for designing government policies and programmes, this scenario is harmful for policy formulation. The absence of timely and reliable data, especially during times of uncertainty, needs to be addressed. While some steps have been taken — employment surveys are now carried out with greater regularity — more needs to be done. The country’s statistical system needs to be strengthened.