With the September 11 inflation rate now at 9.72% (vis-?-vis 9.78% in August), there are fears of a rate hike.

In fact, recent speeches by RBI have added to an apprehension that the apex bank will continue to hike rates even in the October 25 policy. Without getting into the rate hike debate, in this article we would like to raise our concerns regarding (a) the debate on inflationary expectations and (b) too much reliance on statistical artifacts by the market and RBI in its successive monetary policy statements. To put it simply, such statistics to justify policy actions at one?s convenience may sometimes give a distorted picture. That this is the case has been revealed in the latest monetary policy review statement by RBI on September 16, and perhaps in the July statement, as well.

First, let?s take the case of inflationary expectations. As per RBI, inflation expectations play an important part in an inflation-targeting regime. For example, among others, if companies expect general inflation to be higher in the future, they may be more inclined to raise prices, believing that they can do so without suffering a drop in demand for their output.

In the Indian context, measuring inflationary expectations is a difficult task. RBI publishes an inflationary expectations survey for households. Additionally, results from the FICCI Business Confidence Survey could be taken as a proxy for measuring inflationary expectations for corporates. For example, as Figure 2 shows, Price Index is the sum of all net positive responses of companies expecting the selling prices to be higher for the next six months (similar interpretation for Output Index). As we can see from the table, there is a progressive decline in Price Index & Output Index from Q3FY11 onwards (the Price Index is, in fact, negative now and akin to the post-Lehman period). Thus, if inflationary expectations are the basis for RBI going for a monetary tightening, there is now enough justification for a pause in rate hikes.

Next, let?s take the example of statistical artifacts. For example, regarding the argument for a rate hike, RBI supported it with two primary facts in the September monetary policy statement. First, that the Index of Industrial Production (IIP) excluding the volatile capital goods grew at 6.7% y-o-y in July 2011, higher than the aggregate IIP index at 3.3%.

According to this RBI monetary policy statement, ?The IIP slowed down from 8.8% y-o-y in June to 3.3% in July. However, excluding capital goods, the growth of IIP was higher at 6.7% in July as compared with 4.4% in June.? The message of this statement is obvious; industrial growth has still not moderated and hence the urgent need for monetary tightening. But this data-driven analysis tells only one side of the story and it is incomplete.

We plotted the aggregate IIP series excluding capital goods (CG) and aggregate IIP including the CG for the period April 06-July l, 2011 (Figure 1). We divided the trend analysis into three distinct phases. Phase I from April 2006-January 2009; Phase II from February 2009-January 2010; and Phase III from January 2010 onwards.

The graph shows that during Phase I, aggregate IIP including CG was consistently higher than aggregate IIP excluding CG. This clearly implies that investment demand was pulling up IIP growth during this period. In Phase II, post the Lehman crisis, there was a trend reversal with capital goods growth plummeting, which, in turn, pulled down the IIP. This was reflected with aggregate IIP including CG being consistently lower than aggregate IIP excluding CG.

However, in Phase III (coinciding with RBI?s monetary tightening cycle), the worrying point is that aggregate IIP excluding CG has been higher than aggregate IIP including CG on some occasions; for example, in July 2011, when the gap was the second highest after June 2009. The problem here is that this latest data trend is quoted to justify that industry growth excluding the volatile CG has not moderated/is the highest in four months of the current fiscal year; this is used as justification for a rate hike. But this completely hides the bigger picture. For example, aggregate IIP excluding CG was consistently lower vis-?-vis aggregate IIP including CG in the first quarter of the current fiscal, and the trend got reversed in July 2011. Alternatively, the July data trend has clear signs of a moderation in investment demand. In fact, the recently released August 11 data portends that IIP excluding and including CG are nearly identical, implying that investment demand is virtually stagnating! The persistence of this trend is ominous because weakening investment demand is a manifestation of a slowdown. It is evident that incorrectly interpreting IIP to support policy actions may turn out to be dangerous.

Now, let us highlight the statement from RBI?s July monetary policy statement: ?According to the 66th NSSO round, the share of protein-rich items in total consumer expenditure increased both in rural and urban areas?.

However, such a statement again tells only one side of the story. The percentage share of protein-rich food in total consumption expenditure has shown a decline as per NSSO data, over the entire period FY88-FY10. For urban areas, there has been a decline in the case of all the three segments of protein rich food (pulses, egg, fish and meat, and milk products). In contrast, in case of rural areas the increase was evident in the case of egg, fish and meat. Agreeing with the RBI contention that there is a structural shift in food consumption, particularly in rural areas during FY05-FY10 towards more protein-rich items, it is equally true that this is not a new phenomenon (rural consumption of protein-rich items as on FY10 is still nearly at par with FY88 levels in terms of share), but only a trend reversal!

While RBI?s resolve to fight inflation is commendable, particularly as this is being done without any support from fiscal policy actions, the central bank may have done better by looking at other policy actions. For example, RBI could tweak the risk-weights, rather than concentrate only on rate hikes. Relying almost exclusively on statistical data for one variable?the wholesale price index?for important policy actions may result in unintended consequences.

Soumya Kanti Ghosh is Director-Economics & Research, FICCI. Anshuman Khanna is Additional Director, Economics & Research, FICCI. Views are personal