Consequences of GDP over-estimation


Business Standard, 28 May 2018


Has Indian GDP been over-estimated from 2012 onwards? This is ordinarily an obscure debate of interest to a tiny set of economists. If GDP were mismeasured, this may change the thinking of global portfolio managers, but apart from that, nothing much seems to be at stake. But GDP measurement drives macro policy and numerical values of GDP directly go into fiscal planning. When GDP is over-estimated, it puts pressures in tax collection and in the government borrowing program.

The great Indian GDP measurement debate

In the tiny community of economists, there is an even smaller group of people who have an interest in economic measurement. That community has been absorbed, in recent years, in a debate about the difficulties of GDP measurement in India. When we compare with the firm data, GDP is over-estimated. When we compare against a large number of independent measures, GDP is over-estimated. If there is over-reporting of GDP growth in each year from 2012 onwards, this cumulatively adds up to a large over-statement of the level of GDP in 2018.

Many economists have retreated from taking Indian GDP data seriously, until the discrepancy is resolved. Alternative output proxies are utilised, through which business cycle conditions can be roughly measured, without requiring the use of official statistics. But as a card carrying economist, it gives me immense sadness to think that I cannot trust official statistics. GDP is a core concept of macroeconomics. A macroeconomist who is deprived of GDP data is like a doctor who is deprived of a thermometer.

Who cares?

This is edge-of-the-seat excitement for macroeconomists. But for most people, this is a storm in a teacup. Whether GDP is mismeasured or not appears to have little consequence in the practical plane. It may matter for the bragging rights of the administration, and it may shape the allocation of capital to India by global portfolio managers, but for the rest, nothing seems to turn on the numerical values of GDP. No manager in India waits for a GDP release, or uses this as a critical input into decisions about production, inventory or investment.

GDP mis-measurement and the policy process

However, macro policy is flying blind if GDP is not properly measured. When a business cycle downturn is coming, we want the fiscal deficit to enlarge and vice versa, but this is infeasible in India as we have shabby measurement. For the MPC to think about monetary policy, they need to know the state of the business cycle. For the finance commission to do its work, it requires SDP estimates. Weakness in measurement is hobbling our policy makers.

GDP over-estimation and the budget process

There is one place in the economy where numerical values of GDP play a mission critical role: the budget process. In February 2018, budget makers take a stand on their projected value for nominal GDP in 2018-19. That numerical value feeds into the entire budget process. The first draft of the budget for 2018-19 can be made by taking all ratios to GDP for last year and applying them to the new GDP value. As an example, if a certain tax yielded 3% of GDP last year, and if next year's GDP estimate is Rs.150 trillion, then we immediately get a first cut of the budget estimate for the coming year for that tax: 3% of Rs.150 trillion or Rs.4.5 trillion.

The budget process is shaped through and through by ratios to GDP. Whether we think about taxation, expenditure, deficits, borrowing or debt: in all these areas, the budget process uses the projected value for nominal GDP and multiplies this with a sound value for the ratio to GDP. As an example, the discussion on the fiscal deficit is only conducted as a percentage to GDP. Once the budget makers agree that they want a fiscal deficit of 2% of GDP, this is multiplied by the forecasted GDP to get the budget estimate for the fiscal deficit in the coming year, in rupees.

What would happen in the budget process if GDP were over-estimated? Tax targets would then be set too high. There would be gnawing problems in achieving those tax targets. This would result in many small decisions to increase tax rates, in order to get back to normative estimates for tax collections.

India has the remarkably bad concept of tax collection targets assigned to senior managers of the tax administration. When GDP is over-estimated, the targets sent to the CBDT hierarchy are too high. Perhaps this gives a greater propensity to use harsh tactics in collecting taxes.

Similar problems show up with deficits and the borrowing program. When GDP is over-estimated, a borrowing plan that appears reasonable in terms of the borrowing/GDP ratio is one that involves asking for too much debt from the economy. This results in stress where the market is not able to absorb the borrowing.

The scenario of over-estimation of the level of GDP thus results in three predictions: pressure to raise tax rates in tax policy, pressure to use harsh tactics in tax administration, and difficulties in executing the borrowing program. These three problems are indeed present in varying degress in the observed reality around us.

Measurement matters

This is a reminder of the importance of sound economic measurement. GDP measurement was once the prestige project of India's best economists. Many of the top economists of India of the previous two generations devoted enormous effort into building the statistical system, and they were proud of the edifice that they had constructed.

Unfortunately, the economists of my generation have lost interest in problems of measurement. We are now just users of data; we don't take interest in how it is made. The editors and referees of foreign journals think that data emanating from the government is always fully kosher, and academic economists are content with producing wrong research that is career-maximising. GDP data is, however, a mission-critical input into the fiscal process. We must diagnose what is wrong with GDP measurement, and build a capable statistical system.


Back up to Ajay Shah's 2018 media page
Back up to Ajay Shah's home page