Volatile nature of food prices pose challenges to inflation forecasting, says RBI’s Poonam Gupta

Kolkata: Reserve Bank of India deputy governor Poonam Gupta on Wednesday said that the high weightage of food in the Consumer Price Index and the volatile nature of food prices pose challenges to inflation forecasting, a key element in monetary policy making.

As a part of its mandate to conduct monetary policy under the flexible inflation targeting regime, RBI prepares and releases inflation and growth forecasts in every bi-monthly monetary policy announcement.
Any forecasting exercise across the world carries a risk of errors. Possibility of errors grows during periods of uncertainty and unpredictable shocks.


"Inflation forecasting is equally challenging in India, if not more so, given the high and outdated weight of food in the CPI basket and the volatile nature of food prices," Gupta said at a workshop on base revision of CPI, gross domestic product (GDP) and index of industrial production, held in Mumbai.

The RBI also follows a mandate to maintain price stability while keeping in mind the objective of growth.

"For the Monetary Policy Committee to fulfil its mandate effectively, it must therefore form a view not just of current conditions, but also of where the economy is likely to be in the near-term," the deputy governor in charge of monetary policy making said.

This specifically assumes importance because the monetary policy operates with well-recognised lags in transmission.

The bi-monthly MPC resolution provides forecasts of inflation and growth up to four quarters ahead.

In the October policy, RBI projected CPI inflation for 2025-26 at 2.6% with both the second and third quarters quarter at 1.8% while the fourth quarter at 4%.

The weightage of food in CPI hovers around 46% in India. Food inflation fell sharply to -5.02%, helping the CPI to fall to its lowest print in the current 2012‑base series, introduced in January 2015.

RBI relies on a multifaceted approach in forecasting inflation. This includes using a suite of structural and time-series models, each providing a different lens on the economy; examining historical patterns in data to identify the underlying momentum in prices, and assess the base effects, which often shape near-term inflation dynamics; drawing upon a wide range of high-frequency indicators and surveys to capture real-time movements in demand, supply, and their implications on prices.

The central bank also uses a varied set of approaches to generate its growth projections.

Gupta said that RBI's statistical offerings, data and techniques must keep pace with a high growth economy that has exhibited both resilience and agility.

Regularly updating and revising the existing data series, as well as constructing new ones, is essential to capture ongoing transformations.