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GTAP Events: Center Seminar Series

"Optimal Climate Policy in the Face of Uncertainty"
by Yongyang Cai

There is great uncertainty about how CO2 emissions will affect future economic welfare. DSICE (Dynamic Stochastic Integration of Climate and Economy), a DSGE extension of DICE, uses empirically plausible parameters for Epstein-Zin preferences to represent attitudes towards risk, and models uncertainty about future damages from irreversible climate tipping risks and economic growth with a long run risk. DSICE implies much higher carbon taxes than deterministic models, and indicates that optimal policies are much more sensitive to uncertainty than previously thought. The results show that the interplay between risk aversion and uncertainty in the climate risk and the economic growth with the long run risk is also nontrivial to the optimal carbon tax policy. The optimal global land use is also impacted by the climate and technological uncertainty in crop yields. The dynamic stochastic version of FABLE incorporates the stochastic and irreversible crop technology driven by uncertainty in underlying climate impact projections. The results show that the agricultural land use is much higher than in the deterministic solution under the worst case scenario, while the higher crop yields require smaller use of crop land. About the Speaker Dr. Yongyang Cai completed his PhD in 2010 at the Institute for Computational & Mathematical Engineering at Stanford University. He is currently a research scientist at the Becker Friedman Institute at University of Chicago and the Hoover Institution at Stanford University, working on projects for the Center for Robust Decision Making on Climate and Energy Policy (RDCEP) at the University of Chicago. His research interests include dynamic stochastic integrated assessment models, climate change and impact, and computational economics.

Date/Time: 5/16/2014   12:00 PM - 01:15 PM
Location: RAWLS 1071