Incorporating uncertainty in climate economic models
Brock and Hansen discuss the modeling challenges that emerge when they expand the notion of uncertainty to address better the ramifications of the limits to our understanding of climate economic systems. In particular they introduce three components of uncertainty: risk (probabilities assigned by a given model), ambiguity (level of confidence in alternative models), and misspecification (potential shortfalls in existing models). They argue that decision theory can be a valuable tool to help us understand better the consequences of this uncertainty.
Wrestling with Uncertainty in Climate Economic Models
Authors: William Brock, Lars Peter Hansen
From: ∗University of Wisconsin, University of Chicago
Uncertainty in baseline trajectories
Baseline trajectories determine the scale of the future economic system, a fundamental input in the calculation of the benefits and costs associated with climate change policies, including both market and non-market damages and the costs of emissions mitigation efforts. Gillingham and al. focus on three key uncertain parameters: population growth, total factor productivity growth, and equilibrium climate sensitivity. They find that the uncertainty in total factor productivity has a much greater influence on outcomes than the uncertainty about population or climate sensitivity.
Modeling Uncertainty in Integrated Assessment of Climate Change: A Multi-Model Comparison
Authors: Kenneth Gillingham, William Nordhaus, David Anthoff, Geoffrey Blanford, Valentina Bosetti, Peter Christensen, Haewon Mcjeon, John Reilly
From: Yale University, UC Berkeley, Electric Power Research Institute, Bocconi University, University of Illinois Urbana-Champaign, Joint Global Change Research Institute, MIT
