Made in Humane Club
According to a Forbes report, India has a little over 100 billionaires in 2020 – fourth highest in the world behind China (389) and the United States (614).[1] A natural hypothesis would be to suppose that the number of billionaires is related to the size of the economy. Popov (2018) examined this relationship in a cross-country regression. We see that India has more billionaires than would be predicted by the GDP (measured in purchasing power parity terms) alone. So, what else could be going on? Is this because of a worsening in income inequality? And what does data say about it?
In a recent study published in the journal Review of Income and Wealth, Chancel and Piketty (2019) examine income inequality and its evolution in India. Such studies are few because government surveys do not collect information about income.
Consumption expenditure is often studied as a proxy. This is unsatisfactory for two reasons. First, it does not capture savings and since it is primarily the rich who save, expenditure inequality understates income inequality. Second, while the expenditure surveys from the National Sample Survey Organization (NSSO) do a good job of capturing consumption expenditures of the poor, the consumption of the rich is under-reported. Thus, while consumption surveys can be relied for tracking living standards of those at the lower of the income distribution, they can be quite misleading for reading the trends in income inequality.
As a result, research has increasingly turned to combining administrative data from income tax returns with survey data. The former is relied on capturing incomes at the top end (now termed top incomes) while the latter is used for the rest of the incomes. As might be expected, these estimates show a greater degree of inequality than the surveys. More recent work also combines data from national accounts and household wealth surveys. The World Inequality Database (https://wid.world) uses these approaches to put together inequality estimates for a number of countries
The Chancel and Piketty paper on India is an example of this approach. Essentially, tax data is the primary source for incomes of the top 7%. The remainder distribution is estimated from NSS expenditure surveys. An intermediate step converts the expenditures to incomes. All incomes are rescaled so that they match aggregate income from national accounts. The authors admit that alternative assumptions are possible at each step and track 54 possible scenarios! The paper claims that trends are robust and chooses a benchmark scenario that is plausible and where top incomes grow slower than most of the other scenarios.
While the interested reader is directed to the paper for more details, I wish to draw attention to one particular graph – the so-called `cobra’ curve of inequality. The figure reproduced here plots the per adult real income growth rate for each percentile between the period 1980-2015. The incomes for the bottom 90% of the population rises at a pretty uniform rate. While it is hard to read this rate from the graph, a table in the paper reveals that the incomes of the bottom 50% grew by 90% and that of the top 40% grew by 94%. Thus, if the top 10% are thrown out from the data, income inequality would not seem to have changed at all.
All the action is at the top end demonstrating the difference that tax data makes to the analysis. The `cobra’ curve suggests there are indeed, at least, two Indias if not more. The bottom 90% constitutes one reality. The top decile is united only in being different from those below. But, otherwise, there is great differentiation in that group as well. Someone who is at the bottom end of the top decile has much more in common (in income growth rates) with somebody in the bottom 50% than with somebody in the top 1%.
Figure 1: The Cobra Curve: Income growth across different deciles, 1980-2015
Source: Chancel and Piketty (2019)
The Chancel-Piketty estimates of the threshold income that puts a two-adult household in the top decile of the income distribution is Rs. 391,000 per annum or Rs. 32,575 per month.
Interestingly, crude back of the envelope calculations by Ghatak, Kotwal and Ramaswami (2020), using an entirely different data set, also came up with a similar figure for the pre-Covid-19 period of late 2019. On that basis, that article concluded that skilled technical and managerial workers in the organized sector mostly fall within the top decile. This is also supported by the ICE survey of the People’s Research on the Consumer Economy conducted in 2013/14 that showed that the top two deciles to be overwhelmingly urban. It also showed that `middle India’ (located between 20 and 80 percentiles of the income distribution) is “largely composed of those who lack a high school education” (Bhattacharya 2016).
The Chancel-Piketty analysis suggests that it is the well-educated workers that have gained the most – an argument that is consistent with the narrative of Indian economic growth being driven by the high skill segment of the service sector (Kotwal, Ramaswami and Wadhwa, 2011). That, however, does not mean that income inequality is only the product of competitive markets rewarding the skilled and educated. Besides the fact that educational inequalities are closely correlated with traditional divisions in our society, the hypothesis of competitive markets is prima facie inconsistent with the extreme inequality at the top end.
In 1974, a Brazilian economist, Edmar Bacha, imagined a country that had a few rich individuals (he called them Belgians) surrounded by a vast multitude of poor (he called them Indians). He called this country Belindia and it served as a parable for his own country of Brazil. The point of his story was that if the economy’s growth rate was calculated as a simple average of individual income growth rates, it would be far lower than the GDP growth rate (which assign greater weights to the growth in incomes at the top). In 2015, it would seem that Belindia is not a bad description of India itself.
References
Bhattacharya, 2016, Pramit, India’s richest 20% account for 45% of income, Mint, 02 December, https://www.livemint.com/Politics/AvHvyHVJIhR0Q629wkPS5M/Indias-richest-20-account-for-45-of-income.html
Chancel, Lucas, and Thomas Piketty. 2019. ‘Indian Income Inequality, 1922‐2015: From British Raj to Billionaire Raj?’ Review of Income and Wealth 65: S33–S62.
Ghatak, Maitreesh, Ashok Kotwal and Bharat Ramaswami, 2020, What Would Make India’s Growth Sustainable? The India Forum, September 4, https://www.theindiaforum.in/article/what-would-make-india-s-growth-sustainable
Kotwal, Ashok, Bharat Ramaswami, and Wilima Wadhwa. 2011. “Economic liberalization and Indian economic growth: What’s the evidence?.” Journal of Economic Literature 49 (4): 1152–99.
Popov, Vladimir. “Why Some Countries Have More Billionaires Than Others?: Explaining Variations in the Billionaire-Intensity of GDP.” Explaining Variations in the Billionaire-Intensity of GDP (June 1, 2018) (2018). Available at https://doc-research.org/wp-content/uploads/2018/09/Popov_Billionaires_Download-file.pdf
Endnotes
[1]https://www.forbes.com/sites/jonathanponciano/2020/04/08/the-countries-with-the-most-billionaires-in-2020/?sh=738b37c74429
To cite this analysis: Bharat Ramaswami (2020). “India as Belindia” Centre for Economic Data and Analysis (CEDA), Ashoka University. Published on ceda.ashoka.edu.in
If you wish to republish this article or use an extract or chart, please read CEDA’s republishing guidelines.
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