Dartmouth Events

Join us for a lunchtime talk with UC Berkeley PhD Candidate Lisa Rennels, who will discuss recent work that presents a path forward for considering structural uncertainty in climate-economy modeling and highlights the need for aggressive mitigation policy. Lunch will be served. Please RSVP by January 19.

About the Talk: Evaluating the economic impacts of climate change is crucial to inform policy designs. One typical approach uses integrated assessment models to analyze tradeoffs between the costs of reducing greenhouse gas emissions and the benefits of avoiding future climate damages. The deep uncertainty surrounding different models poses nontrivial challenges for policy makers. Typical approaches to handle this structural uncertainty include picking one model, averaging over a suite of models, or rejecting the use of integrated assessment models for policymaking altogether. A fairly new strand of literature breaks important ground by examining deep uncertainty of climate-economy models using robust decision-making methods. Here we apply a robust decision-making framework to evaluate mitigation policy. We show how this shift from expected utility maximization to regret aversion drives stricter mitigation policies, highlighting the potentially harsh consequences of inaction on climate change and motivating rapid, deep emissions cuts. Uncertainties about future socioeconomic trajectories and potentially non-linear or persistent climate damages create asymmetric regret from delayed or weak mitigation policy. This work presents a path forward for considering structural uncertainty in climate-economy modeling and highlights the need for aggressive mitigation policy. Our findings support precaution in the face of uncertainty and faster emissions cuts than currently implemented.

About the Speaker: Lisa Rennels is a PhD candidate in the Energy and Resources Group at UC Berkeley advised by Professor David Anthoff, and holds an  MSc. from the Computer Science Department. She employs her training in both computer science and environmental economics to carry out interdisciplinary research on the economic impacts of climate change and support policy-making in this area.