India’s new IIP series suffers from old problems of unreliability and high volatility

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India’s official gauge of factory output showed that growth in factory output accelerated to 3.8% in March, after rising at a tepid pace of 1.9% in February, compared to the year-ago period. But the numbers for April released last week seem to suggest that the pace of industrial production has decelerated again, falling to 3.1% over the year-ago period.

Such oscillations have been a hallmark of India’s index of industrial production (IIP) for many years. And despite methodological improvements, the new IIP series continues to suffer from the same old problems, a Mint analysis shows.

The old IIP series, with 2004-05 as base year, had changed direction in 42 of the 58 months between June 2012 and March 2017, a whopping 72% of the time. The new IIP series, with 2011-12 as the base year, changed direction at a slightly lower rate of 66%. In other words, if IIP shows an improvement in a given month, then there is a 66% chance that in the next month it will show deterioration.

The new series of IIP, unveiled last month, did make some important changes to the methodology. The number of items included in the index have been increased and production of capital goods will take into account the level of “work in progress” to reduce volatility. The changes seem to have had some impact, with the capital goods segment showing lower volatility than earlier. Yet, the overall volatility of the index remains quite high. As the chart below shows, the volatility of the IIP series is on the higher side compared to other major economies of the world.

We use trend-reversal as a way to capture volatility to ensure that the measurement of volatility is comparable across regions, and across time.

Not only is India’s gauge of factory output more volatile than in other major economies, it also comes with a much greater lag. The lag of six weeks in releasing the estimate is among the highest time-lag across major economies of the world.

The delay could have been ignored if the estimates provided a better and more realistic idea of factory production in the country. But as the chart below shows, IIP is a poor predictor of actual industrial growth.

The initial estimates of GDP use IIP as a proxy, along with corporate filings, to compute the share of industry in the national income. However, during the second round of revisions which take place after two years, the IIP-based estimates are replaced with results from the more comprehensive annual survey of industries (ASI). It is then that the true extent of discrepancy between IIP and actual industrial GVA is revealed.
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As the chart above shows, the growth rates implied by both the old and new IIP series were very different from the actual growth in industrial gross value added (GVA). The reason we restrict the comparison till fiscal year 2015 is because GVA data for the more recent years themselves relies on inferences from IIP.

Overall, the new IIP series has some welcome methodological improvements but fails the test of being an accurate and robust indicator of industrial production in the country.

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