economic inequality in india

Subramanian and Jayaraj

26 Challenge/July–August 2013

Challenge, vol. 56, no. 4, July/August 2013, pp. 26–37.© 2013 M.E. Sharpe, Inc. All rights reserved. Permissions: www.copyright.com

ISSN 0577-5132 (print)/ISSN 1558-1489 (online)DOI: 10.2753/0577-5132560403

Good Jobs

Economic Inequality in IndiaValue-Free Measurement

S. Subramanian and D. Jayaraj

If the income of the poor falls or rises by the same percentage as it does for the rich, economists generally say that income inequality has not changed. But not all analysts believe this is true assessment of social and economic equity, especially in poorer countries. A 10 percent increase for the poor in a developing country is usually trivial compared to a 10 percent increase even for middle-income people, no less the rich. The authors propose a better way to measure income inequality, and it shows that in India, for example, inequality is on the rise.

We live at a time when some experts tell us that nothing particularly alarming has been happening to economic inequality in much of the world, whereas our common

experience—as reflected in such phenomena as the Occupy Wall Street movement—suggests, to the contrary, that economic inequality has been escalating. One clue to the puzzle, we claim,

S. SUBRAMANIAN ANd d. JAYARAJ are professors of economics at the Madras Institute of Develop-ment Studies in Chennai, India. They are the authors of Poverty, Inequality, and Population: Essays in Development and Applied Measurement (Delhi: Oxford University Press, 2012).

Economic Inequality in India

Challenge/July–August 2013 27

resides in the measures on which experts have traditionally relied. Professional economists have generally employed what are called “relative” measures of inequality, which have a built-in tendency to understate increases in economic inequality at a time of growth in average income or wealth. “Absolute” measures are not prone to this problem. However, one can argue that both relative (or “rightist”) and absolute (or “leftist”) measures reflect the values of those who use them. There is, then, a case for employing moderate “intermediate” or “centrist” measures of inequality. This article shows, however, that reasonable centrist measures do indeed display a rising trend in economic inequality in India, in line with popular perception and against the grain of what standard relative measures of inequality suggest.

The article is based on earlier research done by the present authors, in particular Jayaraj and Subramanian (2012a, 2012b) and Subramanian and Jayaraj (2012, 2013). We often shall draw directly on our work, both published and unpublished, and—given the constraints on space and the essentially expository nature of this piece—with little emphasis on nuance or detail. The objective is to present a reasonably easily accessible account of the evolution of inequality in the distribution of both consumption and household assets in India and of how this account could vary depending on how we choose to measure inequality—that is, on a relative, absolute, or intermediate basis. This exercise has lessons for the assessment of inequality trends in other countries and in the world as a whole.

“Inclusive” Growth?

India, as is well known, has experienced impressive levels of growth in per capita income in the past couple of decades or so. How inclusive, or equitable, has this growth been? One way of addressing the question would be to ask: What is a minimally egalitarian way of distributing the product of growth (“egalitarianism” being interpreted as the requirement that the poorer of two individuals never receives a smaller share of the incremental pie)? The answer,



some would say, is a procedure in which each individual is enabled to retain her initial income and then receives an equal share of what is left over from the product of growth. At a grosser level of aggregation, we could require this “equal division rule” to hold for all deciles, or quintiles, or other proportions of the population. The problem bears a deep structural similarity to what game theorists know as “Talmudic estate problems” and distributional analysts know as “optimal anti-poverty budget allocation problems.”

Let us consider in particular the distribution of consumption expenditures (the National Sample Survey Office [NSSO] of India’s Central Statistical Organization has a time-series of surveys on consumption expenditure, though India does not have a systematic database on the distribution of private disposable income). We divide the population into quintiles and look at the performance of the poorest 20 percent and the richest 20 percent over time.1 In particular, if we look at the data over the period 1970–71 to 2009–10, then we can perform the following simple exercise.

Starting in 1970–71, we can find out what the “warranted” consumption of each quintile should be in the terminal year 2009–10, the warranted consumption of any quintile being the average consumption that the quintile would receive if it were entitled to the outcome of the equal division rule described above—an equal share of the gains in the economy. For each quintile, one can then compute the warranted compound annual rate of growth of mean consumption and, applying this growth rate, infer the warranted consumption level in each of the intermediate years between 1970–71 and 2009–10 for which data on the distribution of consumption expenditure are available. For each quintile, and for each data point in our time-series, it is then a simple matter to obtain the warranted consumption, the actual consumption, and the ratio of the actual consumption to the warranted consumption. In a regime of minimally equitable growth of the type that would be dictated by the “equal division rule” to which we have alluded, the ratio of actual- to warranted consumption should be exactly 1 for each quintile at each point of time. As it happens, when we plot this ratio over time, we find that the ratio



Figure 1a. Ratios of Actual to Warranted Mean Consumption Expenditure of the Bottom and Top Quintiles of Rural India Under the “Pareto-Respecting Equal Division” Rule

Source: Reprinted from Jayaraj and Subramanian (2012b), figure 1a.

Note: RBQ = rural bottom quintile; RTQ = rural top quintile.

Figure 1b. Ratios of Actual to Warranted Real Mean Consumption Expenditure of the Bottom and Top Quintiles of Urban India Under the “Pareto-Respecting Equal Division” Rule

Source: Reprinted from Jayaraj and Subramanian (2012b), figure 1b.

Note: UBQ = urban bottom quintile; UTQ = urban top quintile.



Figure 2a. Ratios of Actual to Warranted Real Mean Consumption Expenditure of the Bottom and Top Halves of Rural India Under the “Pareto-Inclusive Equal Division” Rule

Source: Reprinted from Jayaraj and Subramanian (2012b), figure 2a.

Note: RBMEDIAN = rural below median; RAMEDIAN = rural above median.

Figure 2b. Ratios of Actual to Warranted Real Mean Consumption Expenditure of the Bottom and Top Halves of Urban India Under the “Pareto-Inclusive Equal Division” Rule

Source: Reprinted from Jayaraj and Subramanian (2012b), figure 2b.

Note: UBMEDIAN = urban below median; UAMEDIAN = urban above median.



is systematically less than 1 for the poorest quintile, and generally greater than 1 for the richest quintile; and, furthermore, the ratio diverges over time in a widening fork. From Jayaraj and Subramanian (2012b), we have the following self-explanatory pictures of the time-profile of the ratio of actual-to-warranted consumption levels for the poorest and the richest quintiles, in both the rural and the urban areas of the country. A similar picture obtains for the below-median and above-median populations (see Figures 1a, 1b, 2a, and 2b). The visual impression that results is one of the very opposite of inclusive growth.

Received Wisdom on Economic Inequality in India

Commentators such as Ahluwalia (2011) and Bhalla (2011) have maintained that there has been, by and large, little evidence of increased inequality in the distribution of consumption expenditure in India, especially in the rural areas, which, because of their dominating population share, might also be expected to largely determine the all-India (rural-cum-urban) picture. The present authors (Subramanian and Jayaraj 2008) point to a similar rough stationarity in the inequality of household wealth in the country. How does one reconcile these claims of “inclusive” growth with the plainly noninclusive picture that emerges from an analysis of dynamic inequality of the type undertaken in the preceding section? We submit that the answer resides in the fact that alternative approaches are available for the assessment and measurement of inequality. Standard, applied distributional analysis has tended, by and large,2 to concentrate solely on what are called relative measures of inequality—of which the (Relative) Gini coefficient of inequality (also the measure employed by Ahluwallia 2011, Bhalla 2011, and Subramanian and Jayaraj 2008) is a well-worn workhorse. It is our strong belief that both diagnosis and policy can be severely biased by the absence of open-minded plurality in the approach to inequality assessment, and, far from being an arcane pursuit, attention to some important underpinnings of the conceptualization of inequality is



dictated by practical considerations of getting magnitudes and trends as nearly “right” as possible.

Inequality Measures: Right, Left, and Center

Consider a two-person ordered income distribution (10,40). Suppose that each person’s income is doubled. Then the new distribution is (20,80). In purely relative terms, the two individuals are in the same relationship to each other in both distributions (the richer person’s income is four times the poorer person’s income in both cases). All standard “relative” measures of inequality, which subscribe to the “scale invariance” property (namely, that inequality remains unchanged if all incomes are scaled uniformly up or down by the same factor), would judge that inequality has remained unchanged in the transition from (10,40) to (20,80). Notice, however, that from one perspective, inequality has increased in the transition, since the absolute difference in the two individuals’ incomes has doubled, from 30 to 60. Those who subscribe to “translation invariance”3 would hold that it is not equi-proportionate but simply equal increases to all incomes that ought to leave measured inequality unchanged. This may make more sense in a poor country than in a rich one. The poor start at so low a base that mere proportionate increases in income are not adequate to describe a genuine move toward greater equality. Adherents of scale invariance would insist that growth is inclusive whenever all individuals experience the same rate of growth in their respective incomes, while adherents of translation invariance would insist that growth is inclusive when all individuals experience the same addition (the absolute value) to their respective incomes—hence, the differing perspectives on India’s growth experience reviewed above.

For obvious reasons related to the ideological value orientations underlying these alternative approaches to inequality measurement, Kolm (1976a, 1976b) referred to relative measures as “rightist” measures and to absolute measures as “leftist” measures. The standard Relative Gini coefficient and the coefficient of variation



are well-known examples of relative measures, but there is also an Absolute Gini coefficient (see Moyes 1987) (which for the technically oriented is the Relative Gini times the mean income). The Absolute Gini and the standard deviation are well-known examples of absolute measures. But one can steer clear of both of these “extreme” values of right- and left-wing inequality measures and utilize what Kolm (1976a, 1976b) calls “centrist” measures. These inequality measures rise when all incomes go up by the same percentage and fall when all incomes are increased by the same absolute amount. There is indeed an Intermediate Gini (GI) to reflect this centrist view. (It is the product of the Relative Gini (GR) and the Absolute Gini (GA)). Another example of a centrist measure is referred to as K, developed by Krtscha (1994), which, for those interested in the technicalities, is the product of the coefficient of variation and the standard deviation.

Consumption and Wealth Inequality in India Reconsidered

Our assessment of inequality trends thus could be widely different when we switch from a relative conception to an absolute concep-tion of inequality. Suppose we do not insist on absolute measures of inequality, but are willing to settle for intermediate measures. That is—in terms of the earlier discussion on “inequality measures: right, left, and center”—suppose we reject both “rightist” (relative) and “leftist” (absolute) conceptions of inequality, and accept instead a moderate “centrist” approach to interpretation. What do we find? Are the temporal trends in Indian inequality declining, rising, or neither? What does statistical analysis of alternative conceptions of inequality suggest?

Elaborate quantitative and graphical analyses of trends in inequal-ity in the distribution of consumption expenditure are available in Subramanian and Jayaraj (2012, 2013). There would be little point in reproducing the statistical details of these exercises here, but they suggest the following. Taking the period 1970–71 to 2009–10 as the reference period of our study, the Relative (rightist) and the Intermedi-



ate (centrist) Gini coefficients show that inequality has a statistically significant rising trend over time in urban areas. The case is different in rural areas. The Intermediate Gini shows rising inequality but not the relative Gini. Since rural India dominates the picture countrywide, an exclusive reliance on the Relative Gini measure is compatible with an inference of essentially unchanging inequality—an inference that is altered, as we have just noted, by the behavior over time of the In-termediate Gini. Similarly, if we employ unit (household)-level data made available by the NSSO beginning in 1983 and drop the fifty-fifth round (corresponding to 1999–2000) from our time series,4 then again we find that, while in urban areas both the coefficient of variation (a relative measure) and the Krtscha measure (an intermediate index) of inequality display a statistically significant rising trend, it is only the latter that we can claim, with a reasonable measure of statistical confidence, displays such behavior in rural areas.

Finally, when it comes to inequality in the distribution of household assets, again it turns out that when we consider the decennial surveys on debt and investment carried out by the NSSO or jointly by the NSSO

Table 1

Absolute, Relative, and Intermediate Measures of Inequality in the Distribution of Household Assets in India, 1961–2003

Relative Gini, GR Absolute Gini, GA Intermediate Gini, GI

Rural Urban Rural Urban Rural Urban

1961–62 0.6440 — 17,574.76 — 11,318.15 —

1971–72 0.6564 — 20,177.74 — 13,244.67 —

1981–82 0.6354 0.7037 22,930.95 28,546.29 14,570.33 20,088.03

1991–92 0.6207 0.6805 32,009.50 47,333.54 19,868.30 32,210.47

2002–3 0.6289 0.6643 41,909.90 69,528.30 26,357.13 46,187.65

Source: Authors’ calculations based in part on published decennial surveys on the distribution of household assets and debt and in part on Subramanian and Jayaraj (2008), table 6.3; and Subrama-nian and Jayaraj 2013. Note: Absolute and Intermediate Gini coefficients are in constant (1981–82) prices. The price defla-tor employed is the wholesale price index. The Relative Gini has been computed by the “trap-ezoidal approximation method” from the grouped data available in the decennial surveys on the distribution of household assets and debt.



and the Reserve Bank of India over the period 1960–61 to 2002–3, the Relative Gini displays no rising trend in inequality, but the Intermediate Gini does display a rising trend. Table 1 makes this clear.

In summary, what is important to grasp in the findings reported above is not the precise technical content of the measures of inequal-ity referred to as the Relative Gini, the Absolute Gini, the Intermedi-ate Gini, the standard deviation, the coefficient of variation, and the Krtscha measure. What is salient, rather is the interpretation of “rela-tive,” “absolute,” and “intermediate” measures of inequality. What essentially matters is that relative inequality measures widely cited are based on a “conservative” conception of inequality, absolute measures are based on a “radical left” conception, and intermediate measures on a moderate “middle-of-the-road” conception. The excessive and arguably biased emphasis on relative measures in the theoretical and applied literature is what has contributed to the dominant scholarly impression of a rough stationarity of inequality in the distribution of both consumption expenditure and household wealth in India. A more reasonable “centrist” approach—even if it falls short of a prop-erly “radical” interpretation—suffices to demonstrate that economic inequality in India has been increasing.

Concluding Observations

In the common perception, economic growth in India has also been accompanied by widening economic inequality. The singular emphasis, in scholarly work, on a relative conceptualization of inequality has tended to negate the common perception in favor of a thesis of economic inequality that is roughly unchanging over time. We argue here the case for a more pluralistic approach to the measurement of inequality. Such an approach vindicates the common perception that India, in the past quarter- to half-century, has been a society of rising economic inequality. The same is probably true for the world as a whole. This has serious implications for considerations of efficiency, conflict, and public health, apart from the intrinsic fairness of a society committed, in principle, to growth with social



and economic justice. Policy, presumably, must be predicated on accurate diagnosis, and this article is an invitation, in exercises aimed at diagnosis and policy prescription, for a clear declaration of one’s underlying value orientation toward inequality.

Notes1. On the general merits of the “quintile income statistic,” see Basu (2001,

2006).2. For recent and very important exceptions, see the work of, among others,

Atkinson and Brandolini (2004); Bosmans, Decancq, and Decoster (2011); and Del Rio and Ruiz-Castillo (2000, 2001).

3. See Kolm (1976a, 1976b) for a pioneering contribution to this subject of inquiry.

4. Because of a switch in the “recall period” for which the consumption expen-diture schedules were canvassed, the NSSO’s 55th Round estimates for 1999–2000 are widely considered to be unusable for intertemporal consumption-related com-parisons. For a particularly cogent critique of the 55th Round and a validation of this point, see Sen (2001).

For Further ReadingAhluwalia, M.S. 2011. “Prospects and Policy Challenges in the Twelfth Plan.” Eco-

nomic and Political Weekly 56, no. 21: 88–105.Atkinson, A.B., and A. Brandolini. 2004. “Global World Inequality: Absolute, Rela-

tive or Intermediate?” Paper presented at the 28th General Conference of the International Association for Research in Income and Wealth, Cork, Ireland, August 22–28, www.iariw.org/papers/2004/brand.pdf.

Basu, K. 2001. “On the Goals of Development.” In Frontiers of Development Econom-ics: The Future in Perspective, ed. G.M. Meier and J. E. Stiglitz, 61–86. New York: Oxford University Press.

———. 2006. “Globalization, Poverty, and Inequality: What Is the Relationship? What Can Be Done?” World Development 34, no. 8: 1361–73.

Bhalla, S.S. 2011. “Inclusion and Growth in India: Some Facts, Some Conclusions.” LSE Asia Research Centre Working Paper 39. London.

Bosmans, K., K. Decancq, and A. Decoster. 2011. “The Evolution of Global Inequal-ity: Absolute, Relative and Intermediate Views.” Center for Economic Studies Discussion Paper Series (DPS) 11.03, Catholic University of Leuven.

Del Rio, C., and J. Ruiz-Castillo. 2000. “Intermediate Inequality and Welfare.” Social Choice and Welfare 17, no. 2: 223–39.

———. 2001. “Intermediate Inequality and Welfare: The Case of Spain.” Review of Income and Wealth 47, no. 2: 221–37.

Jayaraj, D., and S. Subramanian. 2012a. “On the ‘Inclusiveness’ of India’s Consump-



tion Expenditure Growth.” UNU-WIDER Working Paper 2012/57, Helsinki.———. 2012b. “On the Interpersonal Inclusiveness of India’s Consumption Expen-

diture Growth.” Economic and Political Weekly 57, no. 45: 56–66.Kolm, S.C. 1976a. “Unequal Inequalities I.” Journal of Economic Theory 12, no. 3:

416–54.———. 1976b. “Unequal Inequalities II.” Journal of Economic Theory 13, no. 1:

82–111.Krtscha, M. 1994. “A New Compromise Measure of Inequality.” In Models and

Measurement of Welfare and Inequality, ed. W. Eichhorn, 111–20. Heidelberg: Springer.

Moyes, P. 1987. “A New Concept of Lorenz Domination.” Economics Letters 23, no. 2: 203–7.

Sen, A. 2001. “Consumer Expenditure, Distribution and Poverty: Implications of the NSS 55th Round.” Macroscan: An Alternative Economics Webcentre, www.macroscan.org/anl/jan01/Abhijit_Sen.pdf.

Subramanian, S., and D. Jayaraj. 2008. “The Distribution of Household Wealth in India.” In Personal Wealth from a Global Perspective, ed. James B. Davies, 112–33. New York: Oxford University Press.

———. 2012. “The Evolution of Consumption and Wealth Inequality in India: A Quan-titative Assessment.” Madras Institute of Development Studies, Chennai.

———. 2013. “Growth and Inequality in the Distribution of India’s Consumption Expenditure.” Madras Institute of Development Studies, Chennai.

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