The first Chief Statistician of India and currently principal adviser to the Planning Commission Pronab Sen talks to Santosh Tiwari about the recent Central Administrative Tribunal order quashing the appointment of current Chief Statistician T C A Anant and the Reserve Bank of India’s concerns about the volatility of official data. Edited excerpts:
The Central Administrative Tribunal (CAT) order means that only those with a background in statistics can become Chief Statistician of India (CSI), right?
Basically, the CAT order is saying anybody who is from academics is ab initio non-eligible. This was not the intent when the post of chief statistician was created. The basic intent, to my knowledge, was to induct fresh talent to provide a much larger perspective than anybody from the statistical service could, to do something more than what official statisticians can do. Academics is one of the main areas to look for such people. For instance, I am a macro-economist. My connection with statistics is that of an application. The current Chief Statistician, T C A Anant, is an econometrician, which is a branch of statistics.
The CAT order specifies that CSI should have statistical and managerial experience. Is this valid?
There is nothing wrong in qualifications requiring both knowledge in statistics and managerial experience. But the CAT order goes beyond that. It says you must have managerial experience in a statistical organisation. Now, that is a rare commodity. In effect, what the order is saying is that you reserve the chief statistician’s office for Indian Statistical Service [ISS] officers.
So it’s become a fight between ISS officials and outsiders?
What might well end up happening is that if you look at the chief statistician as a statistician, then only ISS officials will be eligible and perhaps people who are in the Reserve Bank of India’s [RBI’s] statistical division. That’s pretty much it. On the other hand, you do have some administrative officers who head the statistical divisions in the states or who head the census. They would be eligible. But, essentially, you keep it within the government system.
What is the solution in the light of the CAT order?
That’s very difficult to say. It makes life very difficult for Professor Anant because until the case is finally decided, whether at the high court or Supreme Court, his authority has been seriously diluted. He will find it operationally much more difficult than it was earlier.
This clearly means that work at CSI will be impacted. What should the government do?
The government has only one of two choices. It can accept the CAT judgment and ask the select committee to appoint a new CSI. If the government decides to appeal, then it depends on the speed at which courts hear the case and give a judgment. Till that time, Professor Anant can certainly continue if the high court stays the CAT order. But, as I said, his authority will be diluted. The worst-case scenario would be if the government appeals and the high court admits the appeal but doesn’t give a stay, which means Professor Anant would no longer be CSI till the court takes a decision. In effect, the system would be headless.
Increasingly, the posts of various regulators are being occupied by a particular cadre. Will CSI go the same way?
That is probably the intention behind the case. The post of CSI would certainly become bureaucratised. The Rangarajan Commission recommended the creation of CSI essentially because of the dissatisfaction with the leadership coming from the statistical system. With this judgment, you are going back to the pre-2006 situation.
Data volatility has been an issue with the statistical department. RBI has also raised concerns. How serious is the problem?
I am afraid RBI has overreacted. I hate to say this but it sounds as though RBI has lost its institutional memory. It has been the experience not just in India but in other countries also that when you do a base change in any index, there is lot of volatility in the first couple of years because new firms are submitting data. They are not used to it. Often, they are not used to the definitions and data, therefore, doesn’t really conform to what you want from them. So, typically, it takes two years or so for the systems to stabilise.
Now, there are ways of getting over that problem. Make the whole base change process a lot more frequent. When you change the base in 15 years, a very large number of firms drop out of the system and a very large number of new firms come into the sample. That affects the stability. But if you do it at much shorter intervals, then the number of existing firms in the sample would remain fairly large and the number of new firms would be relatively small and, therefore, you get more stability. Unfortunately, it took 15 years to do the base change. This is the consequence of that. Ideally, we should change the base every five years.
The data collection mechanism is also an issue.
IIP [index of industrial production] and WPI [wholesale price index] are returns-based. That is, it’s a voluntary submission of data by companies and we continue to have it that way. But now we have the Collection of Statistics Act, which means if there are companies that are not responding we can invoke the Act and force them to give data. I don’t think too much of it has been done yet but the provision is there.
For WPI, data is collected from mandis. Is that accurate?
Actually, mandi data is very good. The problem that we have is on the manufacturing side.
You are suggesting that the frequency of data revisions will come down as we move forward?
We have been in this base change only since April. It will take another year before it settles. It’s just that it has come at an unfortunate time. If the change would have happened at a low level of inflation, nobody would have made a fuss.
Is our data more volatile than other countries?
I have looked at the equivalents of IIP in other countries and they are just as volatile as ours. If you do an index of volatility, the Indian IIP is not as volatile if you compare it in the international context.
But data volatility impacts policy-making.
As an economist, I would say volatility itself gives information. If the data is accurate and is showing volatility, that is important information for policy. It’s telling you something about the economic system. To say that I would much rather have a stable thing is, in a sense, closing your eyes if the data is correct.
But data changes make policy decisions inaccurate.
Any monetary policy takes six to nine months to take effect. The data is corrected within two months. If you goofed in taking a policy decision, you will get the corrected data in two months and your policy would take effect six months later. That’s the nature of monetary policy. Monetary policy affects nothing immediately.
