The Great India Poverty Debate – raising the question of whether COVID-19 and the related restrictions exacerbated poverty levels across urban and rural India – continues to take interesting turns, one study after another.
Economists are often infamous for not agreeing with each other, but the range of divergence observed in findings from one study to another begs the question: Is the debate on social policy in India (much like everything else) becoming increasingly politicised, polarised and confusing?
A recent study by Arvind Panagariya and Vishal More suggests that rural poverty as a percentage of total rural population declined continuously every quarter beginning July-September 2020. This claim presents a contrarian view to the claims of a large rise in poverty in both rural and urban areas post the COVID-19 pandemic.
According to Panagariya and More, “On a quarterly basis, urban poverty saw only a modest rise, though the increase lasted for four quarters beginning with the strict lockdown quarter of April-June 2020. But by April-June 2021 quarter, decline in urban poverty had resumed.”
Rural poverty too, according to authors, saw a “modest rise” during the strict lockdown period of April-June 2020. “These results are consistent with the robust performance of agriculture in 2019-20 and 2020-21, significant expansion of NREGA, and free distribution of 5 kg food grain per person per month on top of the same amount sold at highly subsidized prices under the Food Security Act,” argue Panagariya and More.
The other main findings of the paper estimate that poverty levels derived from the Periodic Labour Force Survey (PLFS) are not comparable to those derived from Consumer Expenditure Surveys (CESs) conducted in 2011-12 and earlier due to differences in sample design.
Surjit Bhalla and Karan Bhasin, in November 2022, had argued much on the lines of Panagariya and More’s findings, that their paper (as part of the IMF’s Working Paper series) had shown that the poverty decline in India has been persistent from 2011 onwards, and has somehow “declined faster under Modi Government (post 2015) than before”.
Jean Drèze went on to defuse this claim by Bhalla and Bhasin. He says, “Bhalla & Bhasin’s central claim is that poverty decline accelerated under Modi across the full range of 10 deprivations used in the calculation of “multidimensional poverty” (MP). The claim is based on a set of figures presented by B&B as deprivation-specific “headcount ratios” (HCRs) — the percentage of deprived persons in the population”.
“The deprivations of interest are those commonly used in MP calculations, and relate to three distinct domains — health, education and household amenities (also called “living standards”). HCR estimates for 2005-06, 2015-16 and 2019-21 are presented, based on successive National Family Health Surveys. The authors also insert, in this series, 2011-12 estimates based on the second India Human Development Survey (IHDS-2).”
The 2011-12 figures are plain wrong, as Drèze explains in his article here. “They are actually 2005-06 figures from an outdated MP series, copy-pasted by mistake. So, the alleged comparison between 2005-06 and “2011-12” is actually a comparison between two different sets of estimates for 2005-06 (indeed, the respective figures are very close to each other), and the comparison between “2011-12” and 2019-21 is actually a comparison between 2005-06 and 2019-21. No wonder Bhalla and Bhasin found that HCR decline was so slow before “2011-12”, and so rapid after that!”
What is happening here?
One set of economists argues one set of facts (poverty rising “modestly” and then declining “persistently”). Another contradicts that by saying the “methodology” used in refuting a given hypothesis (that poverty did increase post a given period of time) is questionable that allows speculative claims to be made, when the reality may be far different.
Drèze correctly argues that how we judge overall progress – from debates on inclusive growth to poverty expansion/reduction – depends on how much weight we attach to different indicators.
In Multi-Dimensional Poverty Index calculative work, for example, the convention is to give equal weight (one-third each) to health, education and amenities, and then equal weight to individual indicators within each domain. Based on the conventional MP weights, we find that the overall rate of decline of deprivation was the same in both periods (2005-2015 and 2015-21).
But, as important as it is to continuously dig deeper into existing data and tweak methodological designs to prove one hypothesis against another, this may simply be a never-ending debate.
Research in social sciences, not just in economics, has broadly transitioned to ‘proving hypothesis I or II’ rather than seeing the ‘data for what it actually is’ and then making reasonable conclusions. In other words, data is used for theory-validation rather than the other way around.
It is critical to explore, investigate and examine what different databases say about income-based poverty reduction/expansion for any period say, vs capability-based poverty reduction/expansion for that period too.
Poverty isn’t simply about knowing how income, food, deterministic consumption-baskets are determined, as Amartya Sen-Martha Nussbaum had long before argued. There is more to it.
Growth alone is a bad indicator of quality of life as it fails to tell us how deprived people are doing. Thinking of developmental goal in terms of utility has perhaps the only merit of looking at what processes do for people in letting them ‘be’ what ‘they want to be’.
Poverty, for worse, represents a state of powerlessness – lack of opportunity and possible upward-mobility for an identified group, one that often lives/positions itself on the bottom of consumption-income pyramid.
And, as JNU economist Himanshu argues, “The differences in poverty estimates are due to the measure of income/consumption used as much as their choice of poverty lines.”
Part of the reason there are conflicting estimates of poverty for the same period is the loss of reliable data and a yardstick to measure poverty and inequality after 2011-12.
Until then, according to Himanshu, “the responsibility of providing official poverty estimates based on comparable and acceptable criteria was the government’s, in particular the erstwhile Planning Commission. Panels would regularly define and update our poverty line for use with NSO data, all of which was freely available, allowing for a healthy debate on poverty. Indeed, India can rightfully claim to be a pioneer in poverty studies as well as household consumption surveys, which were acclaimed and adapted by such agencies as the World Bank.”
The real issue at hand – apart from the highlighted concern of agreeing to a common understanding of poverty’s conceptual and definitive meaning, which is critical in influencing the way it is ‘measured’ and analytically argued/presented – is the fact that public statistical data infrastructure (and its interpretation) in India has become severely politicised.
There is a poverty of statistics that crowds out any meaningful policy or academic discourse on the statistics of poverty – and much of other social policy.
Economists, dare I say, are increasingly toeing the government narrative when it suits them, and oft dismiss any critical insight that brings the government (or its own policy-methodology) to account. With Surjeet Bhalla and Arvind Panagariya, this can be argued, as both have been selected by the Modi government at different officiating positions.
Similarly, some simply keep critiquing all of what’s formulated and presented. Deconstructive critique is a first step that is critical to dialogue and theorising in the social sciences, even in economics, but there needs to be a way forward beyond that. The core issue is the trust and faith invested in the credibility of India’s public-statistical architecture.
As an author argues, we are in a situation where the last consumption survey of 2017-18 was abruptly junked without any official study or abnormality findings being made public. Even for committees that defined poverty line, the last panel led by C. Rangarajan has not seen any action by the government though its report was submitted eight years ago. The much-awaited and long-overdue national census is yet to be conducted.
“The absence of an official poverty line and consumption data has forced researchers to use alternative ways of estimation. This has created more confusion than clarity on how hard-up Indians have fared,” according to Himanshu.
Poverty estimates, as rightly argued by Himanshu, “are not just an academic exercise but are crucial parameters to judge policy outcomes and the overall functioning of the government”.
I have argued earlier how this is also true of GDP data calculation and interpretations, on which there are subsequently endless debates (belonging to a polarised rhetorical axis), leading to more noise than concrete answers.
Unless we take conscious measures, at the level of authority and the state, to consciously depoliticise data and encourage independent critical scrutiny of existing (and new) methodologies of public data accounting/analysis, there is little hope on what we might do on both social and economic policy. Poverty and income distribution are issues for public discussion as much as they are instruments of governance and public policy for an economy which still has a substantial population that’s financially vulnerable even if not officially poor.
Any government of the day must see this and realise the value of giving preference to critical reason for better scholarship and policy-action, rather than letting scholars rally around noise.
Deepanshu Mohan is an associate professor of economics and director at the Centre for New Economics Studies at Jindal School of Liberal Arts and Humanities, OP Jindal Global.