Climate change is causing structural shifts in India’s inflation dynamics—forecasting must adapt

As India becomes increasingly vulnerable to climate change, its implications for inflation can no longer be ignored. Climate risk is now inflation risk too, requiring monetary policy frameworks to evolve and reflect this reality.

The Reserve Bank of India’s (RBI) Monetary Policy Report of April 2024 estimated that climate-induced shocks could add up to 100 basis points to headline inflation by 2050.

While India’s flexible inflation targeting (FIT) framework has a CPI inflation target of 4%, with a margin of 2% on either side, its primary tool—the repo rate—is effective against demand-driven inflation. So, we must evaluate how this band would change if climate shocks are incorporated.

This is especially important because food, which accounts for over one-third of the consumer price index (CPI), is highly climate-sensitive. Yet, a 6% inflation reading caused by a failed kharif harvest and one driven by excess liquidity appear identical in conventional models, despite requiring very different policy responses. Existing frameworks struggle to distinguish between the two.

Global evidence shows that excessive rainfall, heat stress and flood damage reduce productivity and disrupt supply chains. Inflation-targeting assumes supply shocks are temporary and self-correcting, but climate change has been making them more frequent, persistent and overlapping. This represents a structural shift in inflation dynamics.

The FIT framework largely treats all inflation deviations as alike, even though climate-induced inflation differs from demand-driven inflation in both persistence and policy implications.

The key challenge is to tell temporary price spikes apart from persistent climate shocks. Misreading a climate-driven inflation spike as excess demand could slow growth without easing inflation, while underestimating persistent climate shocks risks inflation expectations getting unanchored.

Climate change is reducing RBI’s margin for policy error. Research suggests food inflation is turning structural, with temperature shocks raising it by up to 0.4 percentage points.

India has made significant progress in integrating climate risks into policymaking through three key developments.

First, RBI’s Monetary Policy Committee (MPC) has increasingly recognized climate risks in its deliberations, citing El Niño (2023), excessive rainfall (2024) and a likely deficient southwest monsoon (2026) as risks to inflation and growth.

Second, Climate Risk Disclosure Frameworks require regulated entities to report climate exposures in line with principles outlined by the Task Force on Climate- related Financial Disclosures.

Third, RBI’s newly launched Reserve Bank-Climate Risk Information System (RB-CRIS) provides centralized climate data for climate-adjusted forecasting. Integrating these into policy models is the next challenge.

Despite these advances, climate risk largely enters policy through qualitative judgement rather than as a quantified input for inflation models. The next step is to systematically adopt inflation forecasting that duly takes climate data into account for policy calibration.

No major central bank has completely solved the climate-driven inflation riddle and they are at different stages in integrating climate risks into their policy frameworks. Three cases are instructive.

First, the European Central Bank’s (ECB) three-part taxonomy that has terms like ‘climateflation’ for supply-side price pressures caused by physical climate events, ‘fossilflation’ for energy volatility related to carbon pricing and ‘greenflation’ for input cost increases led by decarbonization efforts. These give policymakers a vocabulary for calibrated responses.

Second, the Bank of England’s (BoE) Climate Biennial Exploratory Scenario has extended its forecasting model to embed physical climate variables directly into the rate-decision process.

Third, the Reserve Bank of Australia publishes a climate scenario analysis that explicitly separates weather-driven supply shocks from demand-side inflation—a decomposition that India’s models currently cannot produce.

Much like India’s central bank, neither the ECB nor BoE has demystified climate inflation, but both have moved from recognizing climate risk to embedding it within their analytical frameworks that guide policy decisions. Led by these examples, India could also try routing RB-CRIS’s meteorological feeds into the macro-economic models that underpin inflation projections and let policymakers see how much of a CPI surprise can be traced to climate effects vis-à-vis other factors.

India is fast catching up with Western countries in developing climate-related data infrastructure and frameworks. We have moved from recognition of climate risks to the development of climate data infrastructure and could take the next leap of faith: i.e., using that infrastructure to provide tangible forecasts as inputs for policymakers.

It is amply clear that climate risks in India need to be integrated into its inflation targeting framework. This integration ought to take place before climate shocks become sufficiently persistent to weaken the central bank’s current framework.

These are the authors’ personal views.

The authors are, respectively, an economist and an economics student at Shiv Nadar University.