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Physical climate risks are not distributed evenly across the United States. In this article, Alice James, Investment Content Writer and Editor at EDHEC Business School’s Business Development Department and Nicolas Schneider, Senior Research Engineer – Macroeconomist at EDHEC Climate Institute, examine how geographical and climatic differences shape the long-term economic consequences of climate change, highlighting the importance of regional analysis in assessing climate-related financial risk.
The study uses EDHEC-CLIRMAP, a modelling framework that estimates the impact of changing average temperatures on regional economic output per capita. Drawing on historical data from more than 1,500 regions across 87 countries, the model applies estimates of the relationship between temperature and economic growth to future climate projections. Its results reveal substantial differences in projected economic impacts across US states, reflecting their distinct climate conditions and levels of exposure to rising temperatures.
Under a high-warming scenario, the model projects a reduction in regional GDP per capita by 2099 of 43% for Texas, 27.3% for California and 13.61% for Alaska, relative to a counterfactual without additional warming. These figures illustrate the potential scale of long-term economic disruption, although they represent temperature-related macroeconomic projections rather than estimates of losses caused by specific hazards.
The article also examines wildfires as an example of acute physical climate risk. Beyond the immediate destruction of homes, businesses and infrastructure, wildfires can generate substantial indirect costs through reduced labour productivity, health impacts, supply-chain disruption, agricultural losses and pressure on insurance markets. The January 2025 Los Angeles fires illustrate how these effects can extend well beyond the areas directly affected.
The authors emphasise that existing models may underestimate the full economic consequences of climate change, particularly when interacting hazards, cascading effects and climate tipping points are not adequately captured. They conclude that geographically granular analysis is essential to understanding the distribution of climate risk and its implications for economic resilience. This approach also supports the development of sovereign climate risk assessments, helping investors and policymakers better evaluate the long-term financial consequences of physical climate change.