2021-22 Q1 GDP Data Overestimates: Economic Shocks Question Methodology

Worse, the estimation is based on a) projections for the same quarter in the preceding year same quarter, b) in many cases, the projection is not just for the quarter but for the year as a whole and then it is divided into four to get the data for one quarter and c) cases where targets, not actual production data. are used to estimate the contribution to GDP.

Fishing and aquaculture, mining and quarrying, and quasi-corporate and the unorganised sector are a few sectors which belong to the first group. Some sectors belonging to the second category are other crops, major livestock products, other livestock products and forestry and logging. Livestock belongs to the third category, where annual targets/projections are used.

This procedure is clearly inadequate but maybe acceptable in a normal year. But when there is a shock to the economy, does it make sense? If there is a projection from the previous year, it is likely to give an upward bias since the economy was performing better in the preceding year. Further, projections have to be based on some indicators and the data on these indicators were only partially available due to the lockdown.

Finally, how can the annual projection be made and then divided into four to obtain the quarterly estimate when the economy is highly variable from quarter to quarter. In 2020, each quarter was very different from the previous one.

Next, if the data for 2020-21 is erroneous, when there was a massive slump in the economy, the shock continues into 2021-22. How can projections be made from the 2020-21 to 2021-22? Thus, there would be large errors in the quarterly data for the current year. This will then be fed into the data for 2022-23. Therefore, the shock to the economy will play itself out for several years.

Impact on other Macro Variables

Quarterly data are also published for other macro variables like consumption, and investment by public and private sectors. The government-related data is available in the Budget documents, but the private sector data poses a huge challenge. These estimates are, again, based on projections from the previous year, and in some cases, annual estimates are divided between quarters. Production data is also used to project consumption and investment by the private sector. So, if the former is incorrect, as pointed out above, then the estimates for the latter will also be erroneous.

The RBI’s survey of the organised sector showed that capacity utilisation was down to 63% in January 2021, but the official quarterly data was showing a growth of 1.3% rather than a decline of 10%. Thus, the quarterly data was not representative of even the organised sector.

Similarly, consumer sentiment was down to 55.5 compared to 105 a year back, implying that even the organised sector consumption had not recovered to the pre-pandemic levels. Both these variables were further dented in the second wave of COVID-19 in Q1 of 2021-22. The implication is that the data on these variables is also not reliable.

If the production data is an overestimate due to the use of projections from the last year, the consumption and investment data would also be over projections. The further implication is that if the data for 2020-21 is not right, the quarterly data for 2021-22, projected from the previous year, will also be erroneous and overestimate.

Analysis of Macro Variables for Q1 of 2021-22

For the moment, let us analyse the Q1 data leaving aside the errors pointed out above. When the economy was in decline in the preceding year, comparing rates of growth makes less sense than comparing the level of GDP.

On a low base of 2020-21 (-24.4%), the rate of growth for 2021-22 looks impressive (+20.1%). But it is 9.2% less than the pre-pandemic Q1 of 2019-20—i.e., the economy has not recovered to the pre-pandemic level.

Further, if the economy was growing at the pre-pandemic rate, the economy would have expanded another 7.5% in two years. Thus, compared to the possible level of GDP in 2021-22, it is down by about 16%.

Except for agriculture and the utilities sectors, data shows that none of the other sectors have recovered to the levels in 2019-20. Private final consumption expenditure is down by 11.9% and gross fixed capital formation by 17.1%. Government consumption expenditure and exports have increased compared to their levels in 2019-20. The former does give a boost to the economy by increasing demand but the latter does not since imports remain much higher than exports.

Therefore, out of the four sources of demand, only government expenditure has increased—but this is not enough to compensate for the decline in the other three and that is why the economy is still down compared to 2019-20.

It may be argued that over time, data undergoes revision as more data becomes available. But the situation now is unusual due to the pandemic. This necessitated a major revision in the methodology itself due to lack of data and consequent non-comparability across quarters and years.

 The views expressed are those of the author.