Decision-making under model misspecification: an application to climate policy

While models used to evaluate climate change are inherently simplified, and thus imperfect, representations of reality, they remain indispensable tools for quantifying policy impacts and guiding decision-making. How can we leverage these models while accounting for their potential misspecification -the possibility that none of the existing models is adequate? This paper addresses this question by applying recent advances in decision theory to analyze how concerns about model misspecification influence key climate strategies, including the stringency of emissions targets and the extent of climate overshoot. Using a decision-theoretic framework applied to emulators of IPCC-assessed scenarios, we quantify the trade-offs between mitigation costs and climate-induced economic damages. We show that when decision-makers explicitly account for the possibility of model misspecification, they rationally adopt more ambitious climate goals, characterized by stricter carbon budgets and reduced reliance on emissions overshoot. These results underscore the importance of integrating model misspecification concerns into climate policy design, providing a rigorous foundation for precautionary and robust decision-making under deep uncertainty.