‘Credibility of agency vital for data reliability’

Pronab Sen says that the Central Statistics Office (CSO) should not be in the business of making forecasts, and must focus only on giving hard data indicating the economic trend.

Sen, who currently is the Programme Director for International Growth Centre (IGC) India, was the first Chief Statistician of India. He is opposed to the Reserve Bank of India and Finance Ministry asking the CSO to make full year GDP projections on the basis of numbers of only two-and-half quarters.

In a conversation with BusinessLine , he said “You are forcing them to make forecast, which is not right. Stop this.” But, he was quick to stress that why they (RBI and MoF) do so is because of the credibility which CSO has, which now is being questioned thanks to NITI Aayog releasing the back series data. Excerpts:

You can’t, you don’t, and you will never get a reliable number. The reliability of this kind of statistical data depends on the credibility of the agency, which means credibility of CSO, which it was having till now. Had the back series data been released by CSO, people would have believed it. But, now you are hearing it being called fudged.

See, if a feeling gets around that the National Statistical Data are being manipulated to fit political lines then the credibility of the data goes for a toss. People base their economic decisions on this data and now they don’t know whether the data is reliable.

One of the things most countries agree upon is that data should be kept as free of politics as is feasible. That has been the case in India as well. So when you have a data release that is presided over by NITI Aayog, it immediately raises suspicion. The data may not actually have been politically motivated, but just to have NITI Aayog there raises the suspicion.

Till now the data was released by the CSO, then people go to ministries or NITI Aayog to understand the data — their implication — but not the release of data.

In fact, we did not get to see the data until they were released to the press. There were only three people who got to see the data — the Prime Minister, the Finance Minister, and the Vice-Chairman NITI Aayog. They got to see it two hours prior to release. So in a sense the tradition of data being released first is broken. How serious are the implications we do not know. It depends on perceptions. How the perceptions are playing out I don’t know. But, I am concerned.

You see, when we did the base change in 2011-12, various new data sets were available at that time. One data set was the survey of retail and wholesale trade sector and that showed a massive over-estimation of value-added services in that sector in the 2004-05 series, which needed to be corrected downwards.

On the other hand, in the manufacturing there was massive up-scaling. The old data had been under-estimating it. So I had expected that to get corrected. You have two contradictory movements happening — the services sector being brought down and secondary sector going up. But, the new back series shows both declining.

No, it depends upon how you see it. Let us take manufacturing. The growth comes from four factors — new products coming in (not accounted for earlier), increase in output of existing products (volumes go up), productivity, and quality of the product. When the MCA data came, the upward increase in manufacturing did not come from volumes, it came from the other three factors. Now, if you say that I will be only see volume then you are missing out the growth that was coming from the other factors.

If you look at data post 2011-12, then volume growth is even lower than earlier. The bulk of the growth came from essentially productivity and quality improvements. Then you get completely non-comparable figures. If I use the same volume based projections from 2011-12 till now I would get much, much lower growth.

The numbers were tallying, but what was happening in manufacturing was that it was lower than what it should have been. So when you started looking at MCA data you found that you have under-estimated the growth.

For example, you asked about car sales. You have to be careful when you see the sales number — are you looking at value or volume. For instance Maruti produces 800 and Ciaz. Ciaz is four times the cost of 800. Now supposing in 2004-05 Maruti was producing 100 Maruti 800s and today it has stopped producing 800 and produces 100 Ciaz. Maruti’s turnover would have gone up three times, but the number of cars produced would have remained the same. So are you saying that’s not growth? That’s what volume index does.

Well in certain cases it is inferior, in some it is superior. In production shift method, source is not known. So what I will do is take the difference between the new estimates and the old estimates and I will back cast them so that this difference goes to zero at some point in past.The problem is that the difference could come from prices as well. The sensible thing to do is to go sector by sector and ask the question which methodology is better. As it turned out, in my opinion the NSC committee methodology was better for manufacturing.

Yes, we are. People misunderstand the SNA. The SNA is not the recipe, but gives you different options and then it is left to the respective national statistical authorities to pick an option that is most suitable for them.

GDP deflators are a residue that come out in a wash after you have projected the current price and the constant price. Essentially what has happened is that if you look at the GDP deflator between the period 2004-05 and 2011-12, the average is 10 per cent, which is 4 per cent higher than what anybody would have thought of.

Actually the mechanism is quite simple. As far as current prices are concerned you have to treat 2004-05 and 2011-12 as fixed price. These cannot change as they are your base years. What you are changing is the constant price. As I said if you are using the volume based approach all changes get ascribed to price change and inflation gets pushed up.

You see it will depend upon whether the economy is undergoing structural change. From 2004 till now we have seen huge structural change.

Everything depends upon how you use the term flexible. The term used is flexible inflation targeting. How do you interpret it? Is it that the inflation is your number one target, but given the other requirements of the economy whether it’s growth or exchange rate or import-export or is it trade balance? You are given certain amount of flexibility to take care of secondary objectives. That is one way of looking at it.

The other way of interpreting flexibility is that you don’t have to be at 4 per cent, you can be at 6 per cent. I would prefer to interpret it in the former way — that inflation is my prime target but I have flexibility to target other objectives as well.

The RBI seems to be interpreting it in the second way.