Demand slowdown likely to result in low Q4 FY19 GDP growth, signs of structural weakness warrant a coordinated policy response.
Anybody will tell you that forecasting economic activity in India is a fraught and perilous exercise; difficult for the official system, but really parlous for outside analysts with much more limited access to official data. So here goes, more in the form of revisiting trends of various components of GDP rather than actual forecasts, and trying to connect disparate dots.
The latest FY19 GDP update is Provisional Estimates (PE). The first Advance Estimates (1AE), released in January 2019, pegged growth at 7.2%, and then this was revised down just before the interim Budget to 7%. The corresponding growth rates for Gross Value Added (which is the actual measure for economic activity) were 7% and 6.8%, respectively.
Based on the current high frequency data, Q4 FY19 numbers are likely to be weak. We forecast a 6.1% GDP and 5.9% GVA Q4 growth, bringing the FY19 GDP growth lower to 6.8-6.9%. Of course, this is subject to revisions of growth rates of earlier FY19 quarters.
The downward revision is emanating largely from agriculture, and more modestly, from industrial activity, offsetting a slight rise in services GDP (see accompanied graphic). Our forecast is of a flat agricultural output and about a 6% growth in industrial activity (more on this later)—the combined effect of growth and weights in the GDP as the contributions of the respective segments to overall GDP.
A drop in both cereals and horticulture is contributing to the agri slowdown. We await the results of the 3rd update of the 2019 rabi (winter) crop harvest, which, reports indicate, has been late to arrive in markets.
Industrial activity growth is expected to have held up in Q4 (at 5.6%) despite a sharp drop in the Q4 IIP growth to 0.5% from 4.7% over Q1-Q3. The reason is that GVA measure of output combines IIP with the P&L results of manufacturing companies that declare results. We proxy “value added” of a company’s sales as the sum of its PBDIT and employee costs. A sample of 824 manufacturing companies shows 11% growth in net sales in Q4, only a moderate slowdown from 13.2% in Q3 (and 13.8% in Q4 FY18). Within the industry complex, the largest component is manufacturing, and relative growths in the IIP manufacturing vs sales of manufacturing companies is shown in the accompanying graphic.
Similarly, among the trends in (and our forecasts of) the various components of services GDP the one which stands out is growth in Public Admin, almost half of which is government services [see accompanied graphic]. This estimate has the potential of going wrong, but we have based this on a reported 30% in central government spends in Jan-Feb ’19. We expect March spending to have curtailed, post start of election model code (and seemingly validated by high government balances with RBI). If spends are lower, GDP growth will correspondingly fall, maybe to 6.8% for FY19. The other uncertain segment is Trade, Hotels, etc., post the introduction of GST; our understanding of the proxies used for this is still quite inadequate.
The concern is that within our sample of sales results of about 1,000 non-financial, oil and trading companies, a large quantum of the already slower growth is contributed by the top 100 companies (by sales). While this skew towards the larger companies is usually the case, the contribution of these subsets of companies in Q4 has been inordinately high, and has been higher in H2 FY19 than normal. The focus of a policy stimulus has to be, hence, on the smaller companies.
A word on the GDP deflators used for transforming nominal sales growth into real inflation-adjusted growth—these deflators are constructed from CPI and WPI inflation indexes. The occasional large divergences of these metrics distort real GDP growth (as can be seen in the divergences in GDP and GVA deflators in previous years), but these deflators have converged very close in FY19. The implication is that the slowdown is quite real.
The question for a policy response, then, is how much of this slowdown is a transient, pre-election phenomenon, and how much is structural. Unfortunately, the credit squeeze in some segments of financial intermediaries seems to have exacerbated a slowing demand, which in turn seems to have led a seeming lack of confidence in expanding capacity. Facilitating a reduction in borrowing costs will certainly help, but this has to be part of a set of coordinated stimulus response.
With contributions from Vikram Chhabra