Suspect figures

It is scandalous that the Index of Industrial Production (IIP) for January 2012 had to be drastically revised downward because of errors in the compilation of data. The originally announced IIP figure for January had showed a 6.8 per cent industrial growth but it now turns  out that the actual growth was only 1.1 per cent. There was hope that the January growth had marked a fairly good industrial pickup but the revision shows there was hardly any improvement. The error was caused by a gross overestimate of sugar production which was wrongly taken as 134.08 lakh tonnes while the actual output was only 58.09 lakh tonnes. The figures were provided by the directorate of sugar and it is mind-boggling how such a mistake could have been made. Even school students would find it difficult to make such an elementary mistake. Was there no one to take a second look at the figure when there was such a large discrepancy?  

Sugar does not have a high weightage in the IIP and yet the revised production figure resulted in the downward revision of the index by a whopping 80 per cent. This casts serious doubts about the reliability of  the economic data put out by the government. It leads to the suspicion whether other elements of the IIP were correctly reported and even the revised 1.1 per cent is correct. The IIP for February was 4.1 per cent. But it is difficult to vouch for it in the light of the January bloomer. It is not the first time that such mistakes have occurred and not just with the IIP, though a mistake of this magnitude is unprecedented. The RBI has in the past expressed doubts about the veracity of the IIP data. 

The integrity and credibility of economic data are very vital for policy-makers, economists, analysts and students. A policy decision taken by the government on the basis of the original January IIP data or a business decision taken by anybody would obviously have bad consequences. Collating data from different sources in a large country like India is not easy. But a minimum standard of dependability and the least margin for error is expected. The government has the responsibility to make the best quality data available to the people. When it does not do so, even the correct figures and claims become suspect.