Did 250 million Indians exit poverty? Explaining the math behind the data

Multidimensional poverty: how to read the data (Madhu Kapparath)
Multidimensional poverty: how to read the data (Madhu Kapparath)

Summary

  • Last week, Niti Aayog said that more than 250 million people are out of multidimensional poverty. But what lies below the numbers?

In a new paper, the Niti Aayog said an estimated 248 million Indians exited ‘multidimensional poverty’ (MDP) in the nine-year period of 2013-14 and 2022-23. Prime Minister Narendra Modi has already used the data to suggest a reduction in ‘poverty’ during his tenure. Mint explains how to read it.

What is multidimensional poverty?

No measure of poverty is perfect. Traditionally, it’s measured in monetary terms (e.g. you’re ‘poor’ if you earn or spend below a certain threshold). India’s adaptation of a global multidimensional poverty index (MPI) tries to assess poverty by looking at 12 aspects of life beyond money—broadly classed under education, health, and living standards. These are seen as valuable, real-life indicators of poverty, making up for some of the flaws of monetary measures. A household is first judged ‘deprived’ separately on each of the 12 indicators, and based on the weightage of each indicator, if you turn out to be ‘deprived’ overall as well, you’re called ‘multidimensionally poor’ (MDP).

What’s the data source?

Household-level raw data comes from the National Family Health Surveys (NFHS), and Niti Aayog takes it ahead with its MDP calculations. The last three NFHS rounds took place in 2005-06 (NFHS-3), 2015-16 (NFHS-4), and 2019-21 (NFHS-5). Niti Aayog had already updated its numbers to reflect NFHS-5 findings in July 2023, and had estimated that 135 million Indians came out of multidimensional poverty between 2015-16 and 2019-21. Now, it’s gone one step ahead. The three available data points (2005-06, 2015-16, 2019-21), have been used to derive the same for 2013-14 and 2022-23 to establish the progress made in this nine-year period (i.e. “248 million Indians" out of MDP status).

How did data come for these two years?

For simplicity, let’s take the share of MDP Indians. It was 55% in 2005-06 and 25% in 2015-16. Assuming a uniform pace, the paper says it could be assumed to be 29% in 2013-14. Since the share fell to 15% in 2019-21, it could be said to have reduced further to 11% by 2022-23, and will fall to 9% this year, the paper says.

How healthy is this assumption?

The choice of 2013-14 as the starting point is vague, and will inevitably serve as an election pitch defining Modi’s nine years. Assuming a uniform pace in such a long period (2005-06 to 2015-16) is tricky: the derived 2013-14 baseline would be misleading if, say, a bulk of the progress was in 2005–2010. Such a claim should ideally be made for a period where the start or end point had actual data; here neither is (2013-14 relies on interpolation; 2022-23 on extrapolation). The ‘uniform’ pace assumption after 2019-21 also neglects the pandemic impact. Fieldwork for NFHS-5, which took place between June 2019 and April 2021, was already complete in 22 of the 36 states and Union territories, including some of the most populated ones, by February 2020. So extrapolating the same pace to 2022-23 and 2024-25 without taking into account the reversals during 2020–2021 could be faulty.

So what to make of it?

The choice, definition and weightage of indicators in any index can be debated: a minor tweak can turn you from MDP to non-MDP. Yet, such indices are valuable as they offer a combined view of multiple indicators. But it shouldn’t distract us from the long-awaited monetary poverty data; nor should it be confused with poverty itself, as several political leaders have done since July 2023. The welfare progress speaks for itself: the NFHS-recorded progress is evident, and India is indeed on the path to its goals. An exercise of interpolation and extrapolation to fit the period of a government’s tenure could be seen as selective maths.

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