The mystery of lower food inflation
We need more synchronisation between market understanding and RBI communication, lest we fall into the familiar trap of signal extraction
Like the night sky, our stars keep moving. To respond to an evolving macroeconomic environment and set monetary policy appropriately, we keep track of the changes in the underlying state of the economy. Regularly explaining our view of the stars helps financial market participants and others better understand our analytical framework and policy decisions.”
These words by a Reserve Bank of New Zealand assistant governor sum up the two most important unobservable trends impacting monetary policy setting in India. First, the puzzling behaviour of food inflation consistently undershooting even from the most conservative projections. Related to it is also the stickiness in core inflation. Second, liquidity management by the Reserve Bank of India (RBI). This understanding is important as it has a direct influence on efficient price discovery in markets — so important now in the context of market uncertainties.
Take food inflation. We believe there should now be a comprehensive understanding of why the food inflation has consistently undershot inflation projections. If we take the September 2018 deviation of food inflation from the mean (May 2014-September 2018), it is an increase of only 6 per cent (vegetables show a deviation of only 4 per cent). The only item that shows double digit increase is prepared meals, snacks and sweets (possibly, because of changing lifestyle). There could be several reasons for such tranquility. First, the interlinkage between global food prices (that has been declining) and domestic food prices. Second, structural reforms undertaken across states. However, what we think is most important is the changing pattern of consumption expenditure by households.
The data on the pattern of consumer expenditure provided by the NSSO (available till 2012, and forecast till 2017) suggests that household expenditure behaviour has changed significantly over the decades. For example, since 1994 the expenditure on services, particularly in health and education, is increasing steadily. This could be due to more awareness and access to banking (more recently, with the Pradhan Mantri Jan Dhan Yojana or PMJDY) and people’s preference for better standards of living.
A recent paper (2018, Agarwal, Ghosh etc) finds that there is evidence of a jump in health expenses both at the overall level and on individual, health-related items (medicine costs and doctors’ fees), in rural areas after the opening of the JDY accounts. This study also finds a statistically significant and economically meaningful relative decrease in the consumption of intoxicants in rural areas post the opening of JDY accounts. This evidence is consistent with global findings that savings in the bank account help individuals circumvent behavioural biases.
This could also mean that core inflation could be relatively sticky and is driven more by services — again, a global trend. This in turn could raise questions about the viability of the output gap analysis in monetary policy setting.
Second, the liquidity management by RBI. The RBI Monetary Policy Report has summarised the key drivers and management of liquidity (Chapter 4). In essence, financial markets in India need to clearly differentiate between monetary policy stance (more long-term in nature) and the strategy of monetary operations (essentially short term). In this context, the report espouses the need to supply durable liquidity through open market operations (OMO) to balance the movement in autonomous liquidity (government cash balances, currency expansion and intervention in the forex market) to facilitate growth.
How can the market benefit from RBI’s liquidity management operations? The actions of the RBI, through market operations, media interactions and published reports, may reveal part of its superior information set to market participants, but it creates a signal extraction problem. For example, with the system currently in liquidity deficit mode (~1 trillion), the markets are expecting more OMOs. A potential way out of this problem is for the RBI to publish the forecasts of autonomous factors that it anticipates and assuage market concerns. Clearly, we need more synchronisation between market understanding and RBI communication, lest we fall into the familiar trap of signal extraction.