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

Jacopo Ghirri, Massimo Marinacci, Loïc Berger () and Massimo Tavoni
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Massimo Marinacci: Bocconi University [Milan, Italy]
Loïc Berger: CNRS - Centre National de la Recherche Scientifique, IÉSEG School Of Management [Puteaux], EIEE - European Institute on Economics and the Environment, CMCC - Centro Euro-Mediterraneo per i Cambiamenti Climatici [Bologna]
Massimo Tavoni: EIEE - European Institute on Economics and the Environment

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Abstract: 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.

Date: 2026-06-15
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Published in Decisions in Economics and Finance, 2026, ⟨10.1007/s10203-026-00579-4⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05773583

DOI: 10.1007/s10203-026-00579-4

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