Uncertainty in Integrated Assessment Models of Climate Change: Alternative Analytical Approaches
Alexander Golub, Daiju Narita, Matthias G.W. Schmidt
D81, Q54, C61
Uncertainty, Learning, Economics of Climate Change, Integrated Assessment Models, Real Options
Climate Change and Sustainable Development
Uncertainty plays a key role in the economics of climate change, and the discussions surrounding its implications for climate policy are far from settled. We give an overview of the literature on uncertainty in integrated assessment models of climate change and identify some future research needs. In the paper, we pay particular attention to three different and complementary approaches that model uncertainty in association with integrated assessment models: the discrete uncertainty modeling, the most common way to incorporate uncertainty in complex climate-economy models: the real options analysis, a simplified way to identify and value flexibility: the continuous-time stochastic dynamic programming, which is computationally most challenging but necessary if persistent stochasticity is considered.