An analytic framework for assessing the impacts of physical risk through a (climate-related) expected shortfall

Abstract

This paper introduces a novel measure, that is the climate-related Expected Shortfall, employing a quadratic damage function to capture the nonlinear effects of global warming on economic losses. We find a contrasting geographical pattern: as global warming rises, welfare economic losses in Central Europe (Southern) increase, whilst losses at lower southern latitudes decrease due to the nonlinear effect of climate tipping damage. Additionally, we demonstrate that the ES model is a more coherent measure compared to the VaR model, which lacks the subadditivity axiom and overlooks the “hidden” risks. The results offer a forward-looking tool for regulators and policymakers, enhancing our understanding of practical solutions for measuring climate-related financial risks and encouraging further research in this field.