The calculation of Gross Domestic Product numbers is not a subject of general interest. It is complicated and boring for non-practitioners. So, it takes special circumstances for GDP to become a cocktail party topic. The last time I remember that happening was in mid-1991, when India was pledging gold, and reserves were down to less than a month of import cover. Given the economy is in a reasonable shape at the moment, it has taken a special kind of public relations incompetence to turn GDP into a subject of debate.
The methodology for calculating GDP in India was changed in 2014-’15, with the base year moved from 2004-’05 to 2011-’12. Changing the base year is a routine exercise and happens every five years or so. Changing the methodology, though, took many years of preparation with the Ministry of Statistics and Programme Implementation integrating newer data resources such as the MCA 21 corporate database. The new methodology of “value addition” is closer to the global norms and should, in theory, give a more accurate snapshot of the economy.
Whenever the base year is changed, a “back series” is released, modifying GDP calculations for previous years according to the new standards so as to allow comparison. This is mandatory. Introducing a new methodology of calculation makes releasing a back series even more important. This is done by government statisticians, regardless of the political formation in power.
Only this time, the Narendra Modi government did not release a back series. The new methodology hinted that GDP growth may have been higher in 2011-’12 and 2012-’13 under the previous government led by the Congress. This led to the suspicion that growth under Manmohan Singh’s 10-year stewardship may have been stronger than under this government.
As of now, there is still no back series. One excuse for the delay is that the MCA 21 corporate database is only available from 2007-’08 and “unstable” until 2011-’12, making it difficult to generate a back series for the previous years. But a back series has not been released even for the period for which MCA 21 is available. Moreover, a “front series” of GDP calculated under the old methodology for the period 2011-’12 to 2017-’18 could have been easily prepared to allow for comparison. But there is no front series either.
There are multiple ways of reconciling the new series GDP data with the old, and there are alternative sources for corporate data, as shown by the Committee on Real Sector Statistics chaired by Sudipto Mundle which submitted its report to the National Statistical Commission earlier this month. The report includes an “example calculation” linking the new methodology to the old GDP series, using the “production shift” method to create a back series till 1994-’95. The method used is explained in detail, along with two other possible methods of calculation. This is one of those exercises that normally interests only practitioners. In this case, the back series indicated that growth under the Manmohan Singh government was consistently higher than under Modi. For some reason, this is considered embarrassing by the current regime.
A few geeks quoted this “example back series”, but nobody outside a small circle of macroeconomists would have cared had the Modi government not responded absurdly and created a Streisand Effect. The American singer and actress Barbara Streisand went to court to suppress a digital study of beach erosion in California as it contained aerial shots of her beachfront home. Nobody except her lawyers had seen the pictures until she went to court. Once the case went to trial, there were half a million downloads of the pictures.
The government acted similarly, declaring the example back series was not official even though nobody had claimed it was and, indeed, disclaimers to the effect were in place. It also said the data was not to be quoted – and, of course, it was promptly quoted all over social media by people who would never have heard of the Mundle report otherwise.
So, laypersons learnt, unsurprisingly, that Manmohan Singh consistently delivered higher growth than Modi has. In more technical terms, there is little difference between the new GDP series and the earlier one but the new series consistently registers slightly higher growth.
The Modi government also used another line of defence: its predecessor pushed the current account deficit quite high and saw the rupee take a hammering so what if it achieved higher growth? Well, the Manmohan Singh government coped with two major global crises and suffered multiple years of crude prices trending at over $100 a barrel. The Modi government has enjoyed more benign conditions and yet failed to deliver similar growth. Moreover, as crude prices have risen, the current account deficit has risen and the rupee fallen under this government as well.
The debate over it may seem esoteric, but GDP data is vital when it comes to public policymaking. This is especially true for a large and heterogeneous country with massive regional differences, and disparities. Budgets cannot be made without understanding where taxes may come from and how public money can be efficiently allocated. Areas of concern cannot be identified without GDP data and it is difficult to understand if a given policy is delivering the desired outcomes.
India has focused on creating infrastructure since the early 2000s, across sectors. Then there is the Mahatma Gandhi National Rural Employment Guarantee Act, the proliferation of Aadhaar, demonetisation, Goods and Services Tax, public health insurance scheme, changes in customs tariff structures, changes in bond market and banking regulations, changes in energy policy. How many of these have delivered the desired outcomes? There is no way to know without credible GDP data.
GDP calculations can be done in many ways but all require access to masses of data that only the government possesses. There will always be errors and discrepancies in such calculations. Those errors are especially large for India given its big informal sector and the large component of services, which are more difficult to price than goods.
The processes of collecting, crunching and releasing data must be robust, transparent and continuous, regardless of the political formation in charge. A government embarrassed by the thought that the previous government may have done a better job is a government that is less comfortable about transparency, or about generating clean data. It is also a government that is more likely to make policy errors. Sounds familiar?