Be skeptical. Be very skeptical.

In recent months, we’ve had a few slip-ups by the official statistical system in India:

  • Yesterday’s IIP release was preceded by a mistake. Mint says: On Monday, the government was guilty of a similar error in its factory output data. Till it corrected the number pertaining to capital goods output, analysts were left scrambling for explanations as to how this had grown 25.5% while overall factory growth had shrunk 5.1%. (The answer: it hadn’t, and had actually shrunk by 25.5%).
  • On 9 December, we discovered there were important mistakes in the exports data.
  • In December 2010, RBI modified the numbers that it releases about its trading on the currency market.
  • In September 2010, there was a mistake in the quarterly GDP data released by CSO.
These examples are part of a larger theme, of problems of the official statistical system. The Indian statistical system is afflicted by three levels of problems:
  1. The first level is conceptual problems and analytical errors. As an example, the weights of the WPI basket are wrong; the estimation methods used in the IIP are likely to be wrong, etc. Quarterly GDP measurement does not have a demand side (which requires a quarterly household survey, which the government does not know how to do).
  2. The second level is the lack of rugged IT systems. The production of statistics requires high quality enterprise IT systems. The government does not have the ability or incentive to roll these out. As an example, the September 2010 mistake in quarterly GDP data seems to have come about because quarterly GDP data is produced in a spreadsheet. As with all usage of spreadsheets, this is highly error prone.
  3. The third level is the problems of truant front-line staff. In a country which is not able to get civil servants to show up at school to teach, it is not surprising that front-line staff of statistical agencies are untrustworthy in going out into the field and filling out survey forms.
The mistakes that we’re seeing are merely a reflection of #2 (the lack of rugged enterprise IT systems). But there is much more going on which holds back the usefulness of official statistics.
Government officials in this field have pinned a lot of hope on the implementation of the report of the statistical commission (headed by C. Rangarajan, 2001). I am personally not optimistic about this. The report seems to emphasise an incremental agenda of building the statistical system, emphasising the interests of the incumbents. What is required is a ground-up rethink about the statistical system, from first principles, so as to address the three difficulties above.
Turning to the users of official statistics, most economists attach enormous prestige to phrases like GDP, IIP, CPI, etc. But in India, we cannot unthinkingly use some numbers just because they come with the label `GDP’ from some government agency. We have to always skeptically ask first principles questions about how the data is generated. All too often, the standard Indian government data is useless.
In the class of government data that I know of, I feel the CPI is reasonably okay. The WPI is a fairly useful database about prices but useless as a price index. The quarterly GDP data, IIP, NSSO, ASI are untrustworthy.
Decision makers in government and in the private sector need to struggle with these issues, carefully thinking about what statistics are allowed to influence their decision processes. Academic users of data need to be much more careful about avoiding garbage-in-garbage-out problems.
For more on this subject, you might like to look at the label `statistical system’ on this blog.

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