Bloated GDP Estimates? Highlights of ex-CEA Subramanian’s Paper

If Subramanian’s findings are indeed true, many of our projections can go haywire.

(Photo: The Quint)

Former chief economic advisor, and now Harvard professor, Arvind Subramanian begins his hotly debated paper in the following manner: ‘A Descartes of today’s data-addled era might well say, “As we measure, so we are.”’

A seventeenth century French philosopher, Rene Descartes is known for his quote ‘cogito ergo sum’ (I think; therefore I am). The philosopher belonged to an era dominated by ideas and hence the emphasis on primacy of thinking.

However, in the data-dominated world of ours, numbers determine how we perceive ourselves. Hence, the importance of preserving the sanctity of data. The Harvard professor’s paper, however, establishes that our GDP growth estimation has been horribly wrong since 2011.

He argues that “instead of the reported average growth of 6.9 percent between 2011 and 2016, actual growth was more likely to have been between 3.5 and 5.5 percent. Cumulatively, over five years, the level of GDP might have been overstated by about 9-21 percent.”

If this indeed is the case, many of our projections – fiscal and current account deficits, just to name two – can go haywire.

Here are 10 highlights from his paper:

• He has identified 17 real indicators to check whether there exists a strong correlation between GDP growth estimations and pace of acceleration/deceleration in these areas. They are: electricity consumption, two-wheeler sales, commercial vehicle sales, tractor sales, airline passenger traffic, foreign tourist arrivals, railway freight traffic, index of industrial production, index of industrial production (manufacturing), index of industrial production (consumer goods), petroleum consumption, cement, steel, overall real credit, real credit to industry, exports of goods and services, and imports of goods and services.
• He observes that “16 out of 17 indicators are positively correlated with GDP growth before 2011. However, post-2011, 11 out of 17 indicators are negatively correlated with GDP.” In other words, we could correctly predict the direction our economy was headed by looking at these lead indicators in the pre-2011 period.

(Photo: The Quint)

However, there is a disconnect now. While lead indicators like auto sales or exports suggest a trend towards deceleration, GDP numbers are still painting a rosy picture.

• He points out that while average annual growth of exports was 14.5 percent before 2011, it dropped to just 3.4 percent after that. “For imports (goods and services), the corresponding numbers are 15.6 percent and 2.5 percent, respectively; the behaviour of imports in itself provides compelling evidence of mismeasurement because such staggering declines are simply incompatible with stable underlying GDP growth; production of commercial vehicles grew at 19.1 percent before 2011 and minus 0.1 percent after 2011; and only petroleum consumption and electricity grew marginally faster post-2011 than pre-2011.”
• He has mapped the same real indicators-GDP growth correlation for 71 comparable countries and finds out that “India becomes a big outlier” post-2011 which was not the case in the preceding years.

(Photo: The Quint)

• One of the reasons for the overestimation of growth could be methodological changes that entailed moving from volume-based to value-based approach. There was a move from estimation based on data from Annual Survey of Industries and Index of Industrial Production (IIP) to financial accounts-based data procured from the ministry of corporate affairs. He argues that “the inappropriate use of single deflation can artificially inflate growth figures by significant amounts, when oil prices fall sharply, as they did in the post-2011 period, especially the post-2014 period.” He points out that the use of single deflator on the input as well as the output side distorts the overall estimation. The GDP deflator is used to remove the impact of price-induced change in national income. In that sense, it gives real picture of output growth minus the price impact. Suppose the output of a toy factory has gone up, in value terms, from Rs 100 to Rs 112 in a year.

(Photo: The Quint)

• The key contributor to inflated GDP growth numbers is overestimating formal manufacturing value-added growth.

(Photo: The Quint)

• He says that the average difference between IIP growth and manufacturing value-added growth used to be 0.9 percentage points in the pre-2011 period. “However, post-2011, under the new series, the divergence is almost entirely one way, with real GVA growth consistently exceeding IIP growth by about 5.9 percentage points on average. Under the new series, formal manufacturing real GVA has grown by 9.5 percent per annum between 2011-12 Q1 and 2018-19 Q3. For the same period average IIP growth has been 3.6 percent.” He reckons this is bizarre.
• He also argues that overestimating growth in the informal sector may also have contributed to the inflated GDP growth numbers.

“In 2017 and 2018, IIP manufacturing growth registered positive growth of 3.3 percent and 5.3 percent, respectively. But most likely the informal sector registered negative growth in these years because of demonetization and GST.”

Former CEA Arvind Subramanian

• The informal sector accounts for nearly 5 percent of Gross Value Added (GVA).
• The former CEA urges urgent review of the new methodology to estimate GDP as “the evidence is too broad and robust, the anomalies and puzzles too numerous, the magnitudes of over-estimation too large, and the stakes for the economy and country too high for this evidence not to be debated seriously.”

• Urging the government to set up a task force comprising top national and international experts to “restore the reputational damage suffered to data generation in India”, the renowned economist says:

“nothing less than the future of the Indian economy and the lives of 1.4 billion citizens rides on getting numbers and measurement right.”

• He suggests that “the revisiting of NIA estimation will throw up exciting, new opportunities, for example using the large amounts of transactions-level GST data to estimate – for the first time in India – expenditure-based estimates of GDP.”