GDP Data Overestimates: Economic Shocks Question Methodology

GST authorities :

GDP Data Overestimates:  THE Reserve Bank of India (RBI) has maintained its growth projection for 2021-22 at 9.5% while the World Bank has retained it at 8.3%. These are based on the union government’s growth estimate of 20.1% for first quarter of 2021-22—an unprecedented growth rate based on the low base in the same quarter of 2020-21, which witnessed a massive decline of 24.1%.

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A sharp rise in growth after a steep fall in the preceding year is not a new phenomenon for the economy. Prior to 1999, only annual, not quarterly, data was available. Official data shows that the economy has risen sharply several times since independence: 1953-54 (6.2%), 1958-59 (7.3%), 1967-68 (7.7%), 1975-76 (9.2%) 1980-81 (6.8%), 1988-89 (9.4%) and 2010-11 (9.8%). The data after 2011-12 base revision was controversial. For instance, the new series shows a high growth rate of 8.3% for 2016-17 though it is well known that demonetisation devastated the economy.


If the new series, using 2011-12 as the base year, shows a high growth rate for 2016-17, the methodology is not right. This has been extensively discussed since 2015, when the series was announced. A major change has been the use of the data provided by the union ministry of corporate affairs, called the MCA-21 database, since 2015. But it has been pointed out that many of the companies in this database are shell firms and the government shut down several of them in 2018. Further, many companies were found to be missing.

Another problem pointed out, starting the year of demonetisation, is that the measurement of the contribution of the unorganised sector—which constitutes 45% of the GDP—is not based on independent data.

GDP Data Overestimates: The data for the non-agriculture sector is collected during surveys every five years. In between these years, the organised sector is largely used as a proxy and projections are made from the past. Both these features of estimation pose a problem when there is a shock to the economy.

The demonetisation shock impacted the unorganised sector far more adversely than it did the organised sector. Hence, after demonetisation, the organised sector data should not have been used as a proxy to measure the contribution of the unorganised sector. Further, due to the shock, projections from the past will not be a valid procedure. This problem was accentuated by the implementation of the Goods and Services Tax (GST), which again impacted the unorganised sector more adversely.

Thus, 31% of the economy is not being measured, and by all accounts, this part is declining, not growing. Therefore, GDP growth is far lower than what has been officially projected since 2016-17.

GDP Data Overestimates: pandemic and the lockdown have administered the biggest shock to the economy. But the organised sector was hit far less than the unorganised sector. The split between the two sectors has been far greater than due to demonetisation or GST. Therefore, there is an urgent need to revise the method of calculating GDP—also, projections from the past do not make sense.

The problem is even greater when projecting quarterly GDP growth. The data used is sketchier than the annual data. Not only most of the data for the unorganised sector is unavailable (except for agriculture), even the organised sector data is partial. For instance, the data for businesses is based on companies that declare their results in that quarter. Only a few hundred companies out of the thousands might be declaring such data.

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.

GDP Data Overestimates: 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.

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