The design and conduct of climate change policy necessarily confronts uncertainty along multiple fronts. We explore the consequences of ambiguity over various sources and configurations of models that impact how economic opportunities could be damaged in the future. We appeal to decision theory under risk, model ambiguity and misspecification concerns to provide an economically motivated approach to uncertainty quantification. We show how this approach reduces the many facets of uncertainty into a low dimensional characterization that depends on the uncertainty aversion of a decision-maker or fictitious social planner. In our computations, we take inventory of three alternative channels of uncertainty and provide a novel way to assess them. These include i) carbon dynamics that capture how carbon emissions impact atmospheric carbon in future time periods; ii) temperature dynamics that depict how atmospheric carbon alters temperature in future time periods; iii) damage functions that quantify how temperature changes diminish economic opportunities. We appeal to geoscientific modeling to quantify the first two channels. We show how these uncertainty sources interact for a social planner looking to design a prudent approach to the social pricing of carbon emissions.

More on this topic

BFI Working Paper·Jan 6, 2026

Green Waste

Ingvil Gaarder, Morten Grindaker, Tom G. Meling, and Magne Mogstad
Topics: Energy & Environment
BFI Working Paper·Jan 6, 2026

Renewable Energy Expansion: Key Challenges and Emerging Opportunities

Koichiro Ito
Topics: Energy & Environment
BFI Working Paper·Oct 21, 2025

Option Value of Apex Predators: Evidence from a River Discontinuity

Eyal Frank, Anouch Missirian, Dominic P. Parker, and Jennifer L. Raynor
Topics: Energy & Environment