Home Economy and Finance The discussion around GDP data is driven by political and ideological belief, not data and facts

The discussion around GDP data is driven by political and ideological belief, not data and facts

While the quality of India’s economic data remains just as it was in the past, it is imperative that the government considers reforming our statistical systems to ensure that such questions don’t arise in the future.

There has been a lot of discussion regarding the data on GDP and the discussion on this has been driven more based on ideological beliefs rather than a rigorous review of the issue at hand. There is no denying that India does need to improve its statistical systems but the important question to ask is if the quality of new data is worse than the quality of data that was made available to us before. The answer to this is likely to be a no as the quality of our data is still as good as (or as bad as) it was before.

Another important point is to keep this debate limited to a discussion amongst statistical experts rather than having politicians jump in to try to use this for petty political points. The fact does remain that the new GDP methodology is far more robust and reflective of the true picture of the Indian economy (You can read an earlier article that explored this issue by clicking here). As discussed, revision of base years and recalculation of previous years is a routine statistical procedure. In fact, many times such revision tends to lower the value of GDP for previous years.

The recent debate regarding the GDP has come with the backdrop of a report that suggests that the MCA-21 database has 36% of its companies unsuitable for collection of data. The MCA-21 is the new dataset that is used by the Ministry of Statistics and Programme Implementation while estimating the GDP based on the revised methodology. It must also be stated the new methodology is based on the United Nations System of National Accounts (2008) and is, therefore, it has been vetted by international experts. Yet, this debate continues to be politicized and the focus shifts from the genuine discussions on improving India’s statistical systems.

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Critics point out that the presence of shell companies is likely to lead to a downward revision of the GDP in preceding years. However, a downward revision of previous estimates of GDP solely because of the presence of these companies is highly unlikely for many reasons. An alternative source of data on the performance of the economy (in the industrial sector) is the Annual Survey of Industries. It is evident that when the industrial sector grows, the service sector is likely to grow and therefore, ASI data can help us understand the broad trend in directional sense of the Indian economy.

Dr Surjit Bhalla highlighted the findings of the ASI data in an earlier article as he showed how ASI showed a significant acceleration in the industrial sector post-2014. Table 1 presents this data as it becomes evident that indeed there has been an acceleration in the growth rates from 2014 onwards. Therefore, the economy is likely to have performed better in this duration than in 2011-13.

Another important issue worth considering is that the problem concerned is with companies in the service sector. One needs to realistically evaluate the extent of this issue with the MCA-21 database but it is also important to stress that the CSO also takes into consideration all available data of economic indicators as available to them as it routinely revises these estimates and publishes detailed press notes on such revisions. Therefore, if there was any downward revision say in the Index of Industrial Production or the agricultural production data, CSO would have taken it into consideration and revised the estimates downwards. Thus, any discrepancy in what the MCA-21 is showing and other datasets show would be identifiable and thus, could be corrected for in subsequent revisions. The fact that this did not happen, combined with the available data makes one conclude that the revision of GDP because this report is highly unlikely.

Besides, it is very important to understand what shell companies are and whether they create value to be added in the GDP computations or not. Shell companies are created purely for taxation purposes as it enables firms to pay lesser tax through the division of value creation between multiple companies. For instance, suppose there is a manufacturer who produces a good and he creates a company that trades the good. The reason why a firm is likely to do this is in the event of a high excise tax compared to sales tax, the manufacturer can sell the product to the trading company at a lower rate to avoid paying the high tax. In doing so, the manufacturer allocates a greater share of value addition to the trading company than the manufacturing company. The trading company may just be a shell company while the value addition is happening solely at the manufacturing stage. But, for the computation of GDP, it is important that the overall value addition is computed and hence, for estimation purposes, the economic value of shell companies should well be accounted for. Dr Pronab Sen has also highlighted this issue in an article for the Hindu.

It is important to understand that even in a directional sense India’s growth rate post-2014 is better than during 2009-13, while we may disagree on the magnitude, but broad indicators do point out that due to the strong macroeconomic fundamentals growth has indeed been higher. Therefore, what is needed is to strengthen India’s statistical systems further and ensure that discussions on economic indicators are free from politics and driven by logic rather than ideologies.

While the quality of India’s economic data remains just as it was in the past, it is imperative that the government considers reforming our statistical systems to ensure that such questions don’t arise in the future. What is also important is for the MCA-21 to be made public so that independent researchers can use it to find any inconsistencies and suggest potential changes to improve the reliability of this dataset.

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