Inflation and Climate Change

The first in a series of papers published as part of the Inspire sustainable central banking toolbox, this policy briefing examines climate-related data in the economic models used by central banks for policy analysis and inflation forecasting. Climatic shocks and trends are still generally absent from these models, the paper finds, offering a series of recommendations to integrate climate-related risks into forecasting frameworks.

Written by two senior European Central Bank economists, the paper begins by outlining the role that macroeconomic models play in monetary policy. It goes on to review the growing body of literature documenting how droughts, heat waves, floods, asset stranding and other aspects of climate change and biodiversity loss affect price, economic and financial stability.

According to the authors, the accelerating green transition will imply substantial changes in the level and volatility of energy prices, the obsolescence of existing capital stock, and the reallocation of labour and capital, with major implications for monetary policy.

The paper then explores six ways in which macroeconomic models ignore climate change. Workhorse models currently used by central banks do not include a consistent analytical framework linking climate and macroeconomic outcomes, do not use meteorological or carbon pricing data, and do not distinguish between financing of high carbon activities and sustainable alternatives. Central banks’ modelling also largely ignores geographic and sectoral differences as well as global interlinkages in both the real economy and financial sector.

The energy sector is also modelled simplistically, the study says, often focusing on oil alone and failing to account for climate change policies or for the role of energy as an input factor.

Climate-specific models are strong in representing climate-related risks but represent the economy in a very simplified way, contrasting them with macroeconomic models which offer much more detail on the economy but ignore climate-related forces. Acknowledging that a lack of data has been a major barrier in modelling climate change, the authors also point to a range of disclosure and reporting initiatives which are addressing this problem.

The paper concludes with a series of recommendations, including that central banks adopt a “suite of climate models” approach to integrate a range of climate-related risks into their forecasting frameworks. Central banks should also collaborate with meteorologists, climate scientists, engineers and other researchers, it suggests, and should use scenario analysis in a way that acknowledges the radical uncertainty associated with climate change.