Don’t blame it on NSO (The Hindu)

Mains Paper 3: Economy
Prelims level:GDP data
Mains level: Revision of GDP data estimates

Context:

• To global markets as fears of the coronavirus turning into a world-wide pandemic affected markets adversely, India included (it was also impacted by news of Yes Bank).
• During all this, the latest GDP data witnessed significant revisions that have gone largely unnoticed.
• In the last few years there has been a lot of noise regarding the data revisions.
• While part of it requires closer examination, we must be fair to our statistical system as such revisions are, in large part, due diligence and happen globally.

Background:

• Let us first look at the history of GDP data revisions. The first table shows the extent of GDP data revisions since FY15, when the new series was introduced.
• The first column in the table explains the simultaneous revisions that have taken place over the years.
• The NSO releases the first estimates of any fiscal year in January, revises it in February and then again in May.
• It revises the previous year estimates in February, alongside the February data release.
• The primary criticism, apparently, with the current year’s fiscal data is that the revisions in February for 2019-20 and the 4th revision in 2018-19 are almost identical, implying that the sanctity of 5 per cent growth was statistically protected.

Criticism of such revisions:

• There is precedence to the first and second quarter revisions for the current financial year that happen in February.
• Example: while in the current fiscal, .....................................................

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Reasons behind the rise of unconditional bias:

• It is common for such unconditional bias to arise due to the fact that the statistical reporting agency produces releases according to an asymmetric loss function.
• For example, there may be a preference for an optimistic/pessimistic release in the first stage, followed by a more pessimistic/optimistic one in the later stage.
• Intuitively, one might argue that the cost of a downward readjustment of the preliminary data is higher than the cost of an upward adjustment.
• This asymmetric loss function is not so relevant at the reporting stage, but at the forecasting stage.
• A statistical reporting agency like the NSO simply does not have all the data at hand and has to forecast the values of the yet to be collected data.
• It is at that moment that the asymmetric loss function comes into play. So, we must be careful about interpreting data revisions by the NSO by attributing ulterior motives as we more often tend to do.

Developing technology to access big data:

• We must develop an ecosystem that is high quality, timely and accessible.
• Big data and artificial ..........................

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Way forward:

• Recent independent research also shows significant divergence between the consumer price index for industrial workers and the consumer price index (urban) in recent times, when in terms of the composition of the basket and the target population, the two are quite similar.
• But to be fair to both the RBI and the NSO, the volatility of oil prices and structural changes in the economy make the forecasting of inflation and GDP a difficult job indeed.
• However, we should supplement our existing measurement practices with “big data” to make our statistical system more comprehensive and robust.

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  General Studies Pre. Cum Mains Study Materials

Prelims Questions:

Q.1) With reference to the Active Pharmaceutical Ingredient (API), consider the following statements:
1. All drugs are made up of two core components: Active Pharmaceutical Ingredient (API) and excipients.
2. The Active Pharmaceutical Ingredient (API) is the part of any drug that not at all produces any effects.

Which of the statements given above is/are correct?
(a) 1 only
(b) 2 only
(c) Both 1 and 2
(d) Neither 1 nor 2

Answer: ............................

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Mains Questions:
Q.1) How can the supplement of our existing measurement practices with “big data” to make our statistical system robust?