The GDP fudge

Print edition : October 12, 2018

WHEN the figures for economic growth in the first quarter of the current year were released, there was much celebration within the Narendra Modi government and among its acolytes. The fact that the economy had grown at a fair clip, 8.2 per cent in that period, was enough for them to claim that all was well with the Indian economy. Also, the fact that this rate of growth was the highest in the last nine quarters was more than enough cause for celebration. The experience in the last two years ought to have had a sobering effect on those who were rejoicing in these numbers.

In 2016-17, the growth in the first quarter was 8.1 per cent but fell sequentially in each of the succeeding three quarters. The annual growth was finally 7.1 per cent, way below what was registered in the first quarter. Much of this deceleration would have been caused by the demonetisation master stroke of November 2016, but Modi and his acolytes would be embarrassed to admit it. The first quarter GDP growth estimate for 2017-18 was 5.7 per cent, but the economy managed a far more respectable growth rate of 6.7 per cent in the full year despite the twin strokes of demonetisation and good and services tax. That is not how economists are supposed to interpret data. In an environment in which investment is not happening—evident from the slide in the capital goods sector—and in which employment is simply not picking up, they asked: Where is this growth happening? How is it that an economy that is growing in excess of 8 per cent in a world that is witnessing a far slower recovery shows no evidence of the scorching pace that ought to be in evidence somewhere?

In any branch of statistics one set of data is often correlated with another to check how far it reflects observed reality. Thus, in the case of the GDP numbers, the obvious question would be to look for components of GDP that would have enabled this rapid increase—employment, performance of various industries, the value of agricultural output, performance of export industries and various other indicators.

Supporters of the Modi government cited data from the Employees’ Provident Fund Organisation (EPFO) to claim that employment growth has been robust. Of course, this claim ignored the serious methodological pitfalls in making use of the data to make such claims. For one, critics pointed out that given the nature of semi-formal employment in large parts of the country, and given the footloose nature of such employment, there is serious risk of counting the same worker again in multiple locations and establishments.

Other critics who sifted through the data came up with the finding that almost half the increase in employment in the EPFO data came from establishments that were deploying outsourced labour, effectively acting as labour contractors. What this meant was that the perceived increase in employment was actually greater casualisation within what has been regarded as the organised sector. Thus, the logical inference seemed to be that if economic growth was about better jobs that was not the case in Modi’s India.

Even more damaging for Indian economic statistics, for long considered to be among the best in the developing world, has been the manner in which the ruler that measures the value of output and, therefore, growth has been bent out of shape. This pertains to the new series introduced by the Central Statistical Organisation with the base year set at 2011-12.

The fundamental problem with statistics is that it cannot be used to compare the output generated by the economy in the past. The point in measuring the output of today is to be able to compare it with yesterday; and, what is observed today serves as a benchmark to measure output that happens in the future. The serious problem with the new methodology is that it remains incompatible with the data of the past measured by the older series. A task force set up by the government is now examining how this can be rectified.

A recent study by R. Nagaraj, researcher at the Indira Gandhi Institute for Development Research (Mumbai), who has studied empirical issues in Indian industry for long, reveals serious methodological flaws in the new index. Since one of the most contentious issues in the new methodology pertains to the apparently upward bias in measuring output emanating in the manufacturing sector, Nagaraj’s study focussed on this. It appears that the shift in the choice of data source—from the earlier system of using data from the Annual Survey of Industries (ASI) to the reliance on the Ministry of Corporate Affairs (MoCA)—explains the persistent tendency of the data to exaggerate manufacturing output.

Nagaraj and his colleagues point out that the new series measures value of output at current prices by as much as two percentage points more than in the previous series; needless to say, these are also reflected in the estimates of growth. The change in the methodology is such that for some years even the direction of growth in value of output changes.

For example, for 2013-14, the growth of gross value added in manufacturing, according to the old series, was -0.7 per cent, but magically, the new series estimates the growth at 5.3 per cent.

Flawed methodology

One of the claims made by the advocates of the new methodology is that the data from the MoCA come quicker because companies have to mandatorily file data with the Ministry and that the coverage is better. There is also the claim that the MoCA’s data are better at capturing value added vertically within an enterprise, which may happen outside the production site, which is the factory, in the ASI’s methodology. The MoCA data, which are based on submissions made by companies, are of dubious quality in terms of economic authenticity. Moreover, the MoCA does not have the expertise to analyse and process the data. Nagaraj’s study, evidently based on a painstaking analysis by one of his co-authors based in Gujarat, dismantles this claim and points out that not only is the methodology flawed, its logic is not available for researchers to verify and examine.

What has happened to economic data and their presentation in the last four years reflects a mindset that is focussed on the spectacle instead of ensuring the system’s institutional integrity. This was aggressively exhibited by policy mandarins after demonetisation. It took the government and the Reserve Bank of India more than 20 months to reveal how much of the banned currency came back into the system.

For a regime that has drawn more attention for its eagerness to fan intolerance, respect for reason and logic has a poor chance. So, what chance do poor data stand in these times.

V. Sridhar

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