Setting India’s statistical house in order

Until last week, GDP and IIP (Index of Industrial Production) data seemed like strange bedfellows.

Published: 19th May 2017 04:00 AM  |   Last Updated: 19th May 2017 12:04 AM   |  A+A-

Until last week, GDP and IIP (Index of Industrial Production) data seemed like strange bedfellows. If national accounts showed India growing at a world-beating 7 per cent, IIP—a bellwether economic indicator—showed shades of a slump. This divergence raised concerns: Could the data be trusted? Some even hinted the government was dressing up headline numbers, as supporting metrics like IIP, WPI, and merchandise exports were visibly going downhill. But in hindsight, the difference in the base year was partly responsible for the dissonance.

The IMF’s advisors remind nations to change the base year for key indicators every five years as an outdated reference year leads to severe underestimation of ground realities. For instance, when Ghana rebased the indicators in 2011, the World Bank had to upgrade its status from a poor country to a low-middle income group. Like a human body, economic structures also undergo changes. A sector that was small five years ago, but then grew, could contribute proportionally more than its true weight. Also, changes in data compilation, classification systems, consumption and spending patterns influence public expenditure, taxes and growth differently.

Enough reasons exist for rebasing key indicators. First, our economy is still developing, the industrial sector is rapidly evolving and there’s an overlap in definition and categorisation of items. In 60 years, the GDP estimates have been rebased just six times, and when the National Statistical Commission proposed a change, the NDA regime wasted no time. Starting with CPI to GDP, to IIP and WPI now, India’s statistical house has been set in order. But the government is aware the job is half-done and has directed efforts to introduce a producers price index to determine ex-factory price, jobs data, the key metric followed globally and an MSME index to complete the data pool. While our statisticians go to unusual depths to make indices stronger and robust, it’s a fact that perfect numbers, like perfect men, are rare.

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