Gauging the industrial environment is not easy

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New Delhi | Published: August 31, 2018 2:52:11 AM

Is there a leading indicator for industrial growth? Not really. A part of the reason is that industry has been subject to significant disruptions like policy upheaval, stalled projects, volatile consumer demand, global influences, demonetisation, GST, etc, which have made the index numbers extremely volatile.

Four variables have been looked at for the last five years to ascertain if there is a correlation with industrial growth. (Representational photo)

Gauging the industrial environment is not really easy. Very often, we tend to look at various variables and then conclude that there has been a turnaround. But within a couple of months, the same variable appears to be a mirage. Recently, the high level of capacity utilisation in the Q4 of FY18 was taken to be a positive sign of industry turning around, and the argument looked credible given that industrial growth has been steady.
However, given past experiences, it does appear that it would be premature to celebrate as the low base effect of last year on account of GST led to some degree of turbulence, which depressed production numbers as de-stocking took place, and which was replaced during the course of the year. Besides, Q4 is normally a good time for these capacity utilisation numbers as companies, too, increase production to meet the targets. Are there any leading indicators for industrial growth?

Four variables have been looked at for the last five years to ascertain if there is a correlation with industrial growth. The information on capacity utilisation is a quarterly handout by the Reserve Bank of India (RBI), which has been linked to the quarterly Index of Industrial Production (IIP) growth. The same has been done with growth in sales of non-financial companies, which, ideally, should be related to production. For bank credit and Purchasing Managers’ Index (PMI)—which are the other indicators that are available on a contemporary basis—the monthly data has been analysed. For bank credit, quarterly growth rates are also linked with industrial growth. The brief answer to the question as to whether these variables can be the lead indicators is a big ‘no’.

The accompanying graphic shows that high capacity utilisation does not go along with higher industrial growth as the coefficient of correlation is just 0.13. In fact, in each of the five years looked at, the Q4 capacity utilisation was the highest and fell in the Q1 of the succeeding year. The number of 75.2% in FY18 is not unusual and was achieved in FY15, too, while in FY14 it was even higher at 76.1% in the fourth quarter, before it declined to the low seventies. Therefore, unless the capacity utilisation level keeps increasing progressively, it will be tricky to conclude that production has taken off on a new trajectory.

Second, the relation with corporate sales is better at 0.26. Theoretically, if sales are increasing at a steady pace, production, too, must be moving along in line. However, this relation does not appear to be too strong here, and a high growth in sales does not necessarily imply higher production and this is where the inventory management is critical. Sales can move independently of production if inventory is being drawn down. This could be severing the link between the two.

Third, the PMI also appears to be an approximate proxy, though not a strong one, as the coefficient of correlation is also at 0.26. This probably is understandable as IIP growth is always year-on-year while PMI is a survey-based approach that compares the state of industry today with that of last month’s. It is based on impressionistic statements such as whether dispatches or employment in the current month were better or worse than in the last month. Therefore, the two are not really comparable and the weak result is quite expected. The same test has also been done for PMI with IIP changes on a month-on-month basis, and the relation is even weaker at 0.13.

Fourth, bank credit is another variable often used to denote that industrial activity is picking up. Here again, one is in for a disappointment, as higher growth in credit has not been associated with similar tendencies in IIP. This is so because, in the last 3-4 years, bank credit is being led by retail loans, which have weak linkages with industry. Also, with other modes of finance such as bonds, external commercial borrowings (ECBs) and equity being used by companies to finance their funding requirements, bank credit is just one option. There has been evidence of constant substitution between market-driven rates of funding and bank loans, which makes the linkage with industrial growth difficult. The same relationship has also been looked at on a quarterly basis, and the coefficient of correlation is weaker at 0.15.

Probably the only indicator that does indicate, to an extent, the direction of industrial growth is the core sector data, which comes out 12 days before the IIP numbers are released, where the coefficient of correlation is 0.59. But then, this is a subset of IIP and hence would tend to be related given that it constitutes around 40% of the main index. While this can be treated as advance information, it may not be very useful to extrapolate into the future.

It does appear that it is hard to find a reliable and consistent leading indicator of the state of industrial activity. A part of the reason is that the sector has been subject to significant disruptions like policy upheaval, stalled projects, volatile consumer demand, global influences, demonetisation, GST, etc, which have made the index numbers extremely volatile. In fact, of late, this volatility has increased with the trajectory never being single-directional. The shifting of the base year to 2011-12 did increase the growth numbers, but the links with other economic variables remain tenuous. This may continue to be the norm as even the GDP calculation depends on the corporate results to a very large extent, and probably around 20% of the GDP gets related with IIP.

This also means that monthly industrial growth numbers will be very hard to predict based on other economic indicators, and trends in the growth rate, if any, would probably be more effective in forming opinions on the same. It does appear that PMI cannot be used as a proxy as it is much different from IIP. Also, the capacity utilisation rates, even if sustained in the upward direction, may not get related to higher industrial growth numbers. Conjectures would, at best, be guesswork, where the indicators analysed may, at times, provide clues, but will never be sustained.

-The author is Chief Economist, CARE Ratings. Author of ‘Economics of India: How to Fool all People for all Times’. Views are personal

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