Home / Opinion / Views /  Gaps in how we study the impact of covid on inequality

At the onset of the covid pandemic, early last year, I argued in an essay that the virus’s global spread and socio-economic impact would make it the ‘great leveller’, flattening or reducing high wealth/income inequities at a global level, while redefining pre-existent political and economic arrangements from one country to another. My argument then, entrenched in a set of claims, was drawn broadly from a study of the economic history of such shocks and their effect on global income inequality. These claims seem to validate through empirical evidence provided by Nobel Laureate Angus Deaton in his recent paper Covid-19 and Global Income Inequality.

On closely studying data on cross-country covid mortality rates and per capita incomes, Deaton offers three key analytical points in his paper on what happened to global income inequality in 2020. He states: a) Richer countries had higher covid mortality rates, despite better and more technically-advanced medical systems, than less developed nations; b) Economic growth levels fell more rapidly in countries with higher per-capita gross domestic product (GDP); and c) More generally, for a given shock like covid, economic growth tends to fall for nations with higher income-per-head, but the relationship of this one-to-one effect remains less significant if one includes data on nations “weighted for their population sizes". What the last point means is that a small country like Macao cannot be equated with a highly populous one like China while studying the link between a shock and its economic impact. The pandemic, by Deaton’s findings, reduced global unweighted inequality, but increased global population-weighted income inequality.

In explaining these contradictory findings, Deaton is cautious, and expresses humility in acknowledging how measuring ‘global inequality’ operates under key caveats and economists must work under severe methodological limitations. More research may be needed on what happens to ‘inequalities of income distribution’ within nations, which seem to have got exacerbated by the pandemic.

This also raises questions on the conceptual design and framework for analysing economic inequality, which is still largely measured by a macro-income-centred approach, using inhibitive indicators like ‘GDP per capita incomes’ and ‘GDP’ that hardly reflect or explain the true nature, form and substance of inequities experienced by individuals or groups, both in and between nations. Before critiquing Deaton’s study, let’s consider the dominant macro-economists’ view on inequality, seen in terms of income distributions (what the Gini coefficient seeks to do).

Three concepts are generally used for inequality measurement. The first considers the dispersion of per-capita income among nations, with each a unit of observation. Here, each country is treated as an ‘individual’, and calculations are made of inequality levels between one another. The second considers the dispersion of per-capita income between countries, but with each weighted by population. This concept pretends that each person in the world has his or her country’s per capita income, and then calculates inequality among all those persons. Both concepts examine inequality between nations and ignore it within each.

The distribution of income between all persons in the world, which Branko Milanovic (2011) calls Concept 3 inequality, extends the second concept by adding the distribution of income within countries. The changes on this during the pandemic have been vast. But Deaton’s study, like many other economists’ studies on inequality done recently, do little to examine this aspect of it.

Even though income inequalities between countries may or may not have increased, depending on how one picks the data (weighted by country population or not), we still do not know how inequities have worsened within nations, especially for less developed economies (like China, India, Brazil, Nigeria, etc.). More importantly, any such discourse on inequality and its measurement from the perspective of per-capita incomes alone, whether observed under a global or national lens, says very little about the actual inequities that people experience and live with.

There is thus a pressing need to incorporate a more ‘inter-relational’ perspective in the development of a granular, meso-level approach to inequality studies (as argued by scholars like Amartya Sen and many others), which would complement and align with macro findings both in terms of measurement and analytical scrutiny. The pandemic has wreaked havoc on the lives and livelihoods of those living in poorer nations that are characterized by large unorganized and informal socio-economic landscapes. Informality and how it shapes the relative life outcomes of various people is rarely studied for economic diagnoses of inequality.

A relational, inter-subjective lens would help one understand how inequities persist and worsen almost as a continuum. For analysis, we could look at the differential access that individuals/groups have to economic resources, social opportunities, welfare-safety nets, etc. Differential access tends to circumscribe human agency, and so it allows inequality to ‘relatively’ widen from one to another over time. It is about time that even social aggregates of gender, class, caste, race and ethnicity are considered in widening the conceptual base of how we view inequality. Income data-sets are important, but many economists, including Deaton in his paper, fail to include or even discuss other aspects.

Deepanshu Mohan is associate professor of economics at OP Jindal Global University

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