The new GDP data has bewildered all, even invoking disbelief amongst some. Doubts have been raised on several counts but above all because the new growth profile, as per these estimates, appears completely out-of-whack with familiar lead indicators like the IIP, bank credit growth, corporate earnings, tax collections and so on. This particularly applies to the 7.5%-growth forecast for FY15, which is nearly percentage point uplift from last year’s 6.6% GVA at basic prices. At 7.4% in GDP (final expenditure) terms, this is a half point increase from 6.9% in FY14.
The curiosity is that even when almost everyone is sceptical, this hasn’t really prevented anyone from projecting a gradual recovery on track from FY14. Hence, growth in FY16 is predicted to lift upwards into the 7.6-8.5% region (from 7.5% in FY15); this includes the official agencies, national and international. This perplexity is understandable: For one, the national statistical agency (CSO) has cautioned not to expect the old, similar relationship between volume indices like the IIP, due to a different value-added concept underlying the new GDP compilation method.
Two, the fast speed of imported disinflation plus a changed economic structure has markedly affected the deflator, imparting a positive boost to real GDP growth. And three, mixed signals from several high-frequency indicators have likely influenced growth projections, imparting an upward bias.
Is there another way then of getting a handle on what exactly is the growth trajectory? Is a gradual acceleration on course? Is it restricted to some segments, while other parts of the economy might be trending downwards? What could be the possible net outcome, given new or different input-output linkages between the different parts of the economy than before?
We look at the evolution of capacity utilisation levels as captured by successive rounds of RBI’s Quarterly Order Books, Inventories and Capacity Utilization Survey (OBICUS). Juxtaposed with these is the new quarterly GDP series, available from FY14. The intention is to explore if capacity utilisation levels are in sync with projected growth for FY15, relative to the previous year.
Capacity utilisation is a well-regarded, accepted measure of economic slack at a point in the business cycle; its evolution over time offers a directional perspective. The information it provides is about the extent of idle or used production capacity in the economy; according to Wikipedia, “it is the relationship between actual output that ‘is’ actually produced with the installed equipment, and the potential output which ‘could’ be produced with it, if capacity was fully used.” It therefore measures the ‘output gap’, whether positive or negative; and depending on its coverage or representation, even the size. Intuitively, if growth were picking up with whatever momentum, capacity utilisation levels ought to be rising, i.e., the existing production slack should be getting used up; the opposite applies if utilisation levels are declining, suggesting deceleration in the economy.
Against this intuition, the story in the chart tells itself. If average quarterly capacity utilisation rate of approximately 1,300 manufacturing firms (government: 49, public: 903 and private: 345) responding to the OBICUS was 79% in the two years to FY12, this dropped to an average 74% in the next two years, i.e., FY13 and FY14. In the current year, the average capacity utilisation rate in the first three quarters is even lower at 71%. Apart from manufacturing, inventory levels rose steadily in the 12 months in the property segment too, indicating surplus capacity there as well.
Relative to this trend, GDP growth based on the new series rose from 5.1% to 6.9% in FY14. This has been explained by CSO as efficiency gains captured by the value-added concept, possibly from cost-cutting, retrenchment and lay-offs, and other like measures.
But the real puzzler is the FY15 growth forecast of a further uplift to 7.5%. How is the economy predicted to accelerate when existing production capacity is progressively getting less and less utilised? And for FY16, when growth is commonly projected to increase anywhere beyond 7.6%, how does this reconcile with the existing surplus capacity? When firms’ output from existing plant and equipment in the goods-producing segment is actually falling, or that there is excess capacity, surely, this is geared to demand for these goods, i.e., sales? Any firm can only produce as much as it is able to sell to consumers; it is more efficient for it to keep balance production capacity idle than pile up inventories. And given the link between capacity utilisation and a firm’s expansion plans, what does this tell us about resumption of the investment cycle?
Since the new GDP series is expected to be revised based on fresh data available with the CSO, we should soon know whether capacity utilisation is itself a leading indicator of GDP growth or not. And these indications are of but a small, visible segment (listed companies) against the much-wider, new coverage now of 5lakh-plus companies from the MCA database, which includes a large ‘invisible’ segment not captured by the high-frequency data. It is possible that aggregate capacity utilisation levels are possibly much higher, directionally upwards; or even that there might be divergent paths of the ‘visible’ and ‘invisible’ segments. After all, in the old days, when there was no MCA data, there often would be lagged, sharp GDP revisions when the Annual Survey of Industries survey data became available. A wider universe might therefore be showing acceleration against the trends observed from OBICUS.
The critical point here however is this: In a world of ‘no MCA database’, and just the OBICUS, RBI would have concluded the economy was decelerating and managed policy settings accordingly. From the trends reflected this chart, there is no way RBI could have claimed a recovery as it is now. So the new, wide but ‘invisible’ world captured by the new GDP estimates renders the central bank’s critical information input—the OBICUS—at variance with the predicted growth path and hugely increases the scope for monetary policy error. Considering that this information gap will persist, RBI ought perhaps to move very fast to either expand the scope of the current OBICUS, or launch a similar capacity utilisation survey of the ‘invisible’ segment to avoid monetary policy errors. There is little the CSO can do in this regard.
The author is a New Delhi-based macroeconomist
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