Rural Distress, Urban Slow-Down, Overall Stagnation, and the Suppression of Data

One of the finest features of our country, of which we can be legitimately proud, is our post-Independence record of the statistical base of India’s economy and society. This data base is a vast and extraordinary enterprise which had its origins in the exemplary vision of—among other actors—the late, great physicist, statistician and institution-builder Professor P. C. Mahalanobis. Most sadly, and like other institutions that have witnessed swift decay in the course of the last few years of our democracy, the autonomy and independence of our data-generating agencies have also been compromised. We have had misleading messages put out on the growth rates of Gross Domestic Product and on the record of open defecation, which have since been called out by responsible critiques of the methodology underlying GDP growth statistics, and by the actual statistics themselves on open defecation. Information on a record level of unemployment was withheld before its delayed release in the form of the Periodic Labour Force Survey’s Report for 2017-18. Crime statistics on the incidence of lynching have not been released. There is lack of transparency on how the fiscal deficit is being managed, in terms of easy and complete access to information on tax revenues and on the extent and composition of cuts in government spending. And so on.

The consumption distribution data, which are released once every five years, are the single most important source of information we have for tracking poverty and inequality. The Ministry of Statistics and Programme Implementation (MoPSI) has, however, decided not to release the draft Report for 2017-18, on grounds of the alleged poor quality of its data. It would have been a different matter if the Government had released the data while expressing its own reservations on the quality of the data. But simply suppressing the draft Report in question is an altogether different matter. The motive for censorship would also inevitably be called into question if it turned out that the NSO’s 2017-18 draft Report reflects an unflattering picture of tendencies in welfare, poverty, and inequality indicators relating to consumer spending. This indeed appears to be the case, as suggested by analyses of a leaked copy of the 2017-18 draft Report carried out by a number of independent commentators, including, in particular, Somesh Jha and Abhishek Waghmare in the Business Standard, Varun Krishnan in The Hindu, and Pramit Bhattacharya and Sriharsha Devulapalli in the LiveMint financial daily.  

In what follows, I also undertake a processing of some of the data in the 2017-18 draft Report, to get a sense of what message it conveys on certain crucially important features of our economy. In an earlier article published in The India Forum [1], I had reviewed aspects of changes in rural welfare, poverty, and inequality, over the period 2011-12 to 2017-18, employing the National Sample Survey Office Report on consumer spending for 2011-12 (68 ^th Round) and Tables T3 and T4 of the National Statistical Office draft Report for 2017-18 (75 ^th Round), which, as already pointed out, has been ‘junked’ by the Government of India on grounds of the allegedly poor quality of its data. In the present article, and in the interests of completeness of record, I repeat some of these exercises for urban India, employing the previously mentioned data sources. I attempt to present a consolidated and comparative rural-urban picture of welfare, poverty, and inequality tendencies over the period 2011-12 to 2017-18. What we find is a deterioration of welfare in the rural areas, a slowing-down of improvement in the urban areas, and stagnation, if not worsening, at the aggregate all-India level. I also comment on the judgement that the data in the junked Report are of such poor quality as to be virtually un-usable.

I should perhaps warn that though I have tried my best to keep the discussion as non-technical and transparent as I could, there may nevertheless be elements of it which are a bit difficult for the non-specialist to completely comprehend. May I beg the reader’s indulgence for this deficiency, with the assurance that what really matters for an understanding of the article is the gist of its meaning, not the details of its numbers? Above all, 

1.     2011-12 to 2017-18: Changes in Aspects of Consumption

In Sections 1.1 to 1.3 I shall deal with some preliminary disaggregated statistics on consumption spending in both the rural and the urban areas of the country, for each of the years 2011-12 and 2017-18.

 1.1 The Cumulative Density Functions for 2011-12 and 2017-18

The cumulative density function (cdf) of a distribution just presents information on the cumulative proportion of the population below each specified consumption expenditure level, when these expenditure levels are arranged in ascending order. Information on the cdfs and changes in them for both rural and urban India are presented in Table 1. If the cdf of one distribution lies everywhere below that of another, then we have a case of ‘first order stochastic dominance’, which is a signal of the unambiguous welfare superiority of the first distribution vis-à-vis the second. In the case of rural India, we have an unambiguous worsening of welfare from 2011-12 to 2017-18, as reflected in the first order dominance of the 2011-12 distribution over the 2017-18 distribution. Such an unambiguous deterioration is not reflected by the cdfs for urban India, but neither do we have evidence of an unambiguous improvement: the two cdfs intersect, with the 2017-18 distribution lying below the 2011-12 distribution for the most part, but above it at higher levels of expenditure. The picture can be visualised from the numbers in Table 1, which shows that while the 2017-18 urban cdf lies below the 2011-12 cdf upto an expenditure level of about Rs.4500 per person per month, this outcome is reversed for higher levels of expenditure of Rs.4500 and above. 

Table 1: Cumulative Density Functions of Consumer Expenditure for Rural and Urban India in 2011-12 and 2017-18

Source: Computations based on data in the 2011-12 NSO Report on Consumer Expenditure (68 ^th Round) and Tables T3 and T4 of the 2017-18 NSO draft Report on Consumer Expenditure (2017-18) 

1.2 Decile-Wise Mean Per Capita Consumer Expenditure Levels for 2011-12 and 2017-18

In Table 2 we have information on the average (real) level of consumption expenditure for each decile of the rural and urban populations, from the lowest to the highest, for each of the years 2011-12 and 2017-18. While in rural India, every single decile registers a decline in its average level of spending, and overall average spending has declined by 8.8%, this pattern is almost completely inverted in urban India. Table 2 shows that in the urban areas every decile from the first to the ninth has a higher level of average spending in 2017-18 compared to 2011-12, with the rate of increase fairly systematically declining as we go up the decile ladder. However, the highest decile registers a fairly large proportionate decline in average consumption. Given that the tenth decile accounts for nearly 30% of the total urban expenditure, the large decline in its average level of spending combined with the relatively modest rates of increase registered by the lower deciles has spelt an overall increase of just around 2% in the aggregate average per capita consumption level. (I might add that ‘real’ levels of consumption expenditure have been obtained by employing the price deflator data on the Consumer Price Index of Industrial Workers furnished in Table T4 of the 2017-18 draft NSO Report). Subramanian and Lalvani (2018) report in Table 1 of their paper[1] that between 2004-05 to 2011-12, real average per capita consumption expenditure in the urban areas increased for every decile group and by about 32% overall, whereas between 2011-12 and 2017-18 we have a very modest aggregate increase of just 2%, signalling a considerable slow-down in urban consumption growth.

 Source: Same as Table 1

1.3 Inequality in the Distribution of Consumer Expenditure: 2011-12 and 2017-18

Table 3 carries information on the ordinates of the estimated Lorenz Curves for the distribution of consumption expenditure in 2011-12 and 2017-18. The Lorenz curve ia a simple graphical device for estimating the extent of inequality that obtains in a distribution. It is derived by plotting the cumulative income/expenditure share against the cumulative population proportion, arranged in ascending order of income/expenditure, for every population proportion from 0% to 100%. Thus, the Lorenz curve will enable us to tell the income share accounted for by the poorest 10%, the poorest 20%, the poorest 30%, and so on, of the population. If expenditure is perfectly equally distributed, then the poorest 10% of the population will account for exactly 10% of the total expenditure; the poorest 20% will account for exactly 20% of the total expenditure; and so on. The resulting Lorenz curve will then be represented by ‘the line of perfect equality’, which is just the diagonal of the unit square in which the Lorenz curve is drawn. But typically, distributions are unequal: the

1.4 A Consolidated Account of Changes in Welfare, Inequality, and Poverty

In Table 4, we have a summary picture of welfare indicators and how they have changed between 2011-12 and 2017-18. For purposes of comparison, I have juxtaposed the urban statistics with the rural statistics (which latter are drawn from Table 4 of my earlier article, previously alluded to, in The India Forum). Over the period 2011-12 to 2017-18, each of the following welfare indicators has registered a decline in rural India, and an increase in urban India: mean per capita consumption expenditure; the quintile expenditure statistic advanced by Kaushik Basu (which is just the average expenditure of the poorest 20% of the population, and can be interpreted both as a welfare and as a money-metric poverty indicator); the average income of the below-median half of the population; and Sen’s welfare index of ‘distributionally adjusted’ mean consumption expenditure.

Mean consumption is the simplest summary statistic we can have on the magnitude of consumer spending. That it should display a negative rate of growth in the rural areas—and for the first time in decades—is naturally cause for worry. As we have seen, a disaggregated analysis of fractile-specific expenditure trends reveals that in rural India, every single decile registered a decline in its average level of spending. This pattern, as it happens, is almost completely inverted in urban India: Table 2 shows that every decile from the first to the ninth has a higher level of average spending in 2017-18 compared to 2011-12, with the rate of increase fairly systematically declining as we go up the decile ladder. However, the highest decile registers a fairly large proportionate decline in average consumption. Overall, average per capita consumption expenditure has increased very modestly, by just around 2%, suggesting a considerable slow-down in urban consumption growth.

It is worth reiterating a simple point: all the welfare indicators we speak of have registered a modest, but nevertheless positive rate of change in the urban areas, in contrast to the uniform picture of deterioration revealed in the rural areas.

Inequality has declined unambiguously in both the rural and urban areas, as the relevant statistics on the Gini coefficient of inequality in the distribution of consumption expenditure reveal. As we have noted earlier, the rural reduction in inequality has been achieved by a proportionately greater reduction in the average expenditure levels of the richer deciles vis-à-vis the poorer ones: all decile means have declined. In the urban areas, however, we have modest and declining rates of increase in the average consumption levels of the poorest nine deciles; but an across-the-board improvement (which economists would typically call a ‘Pareto improvement’) is denied by the performance of the richest decile, whose mean expenditure level has declined quite considerably.