Solving Infinite Horizon Growth Models with an Environmental Sector

This paper concerns computational models in environmental economics and policy, particularly so-called integrated assessment models. For the most part, such models are simply extensions of standard neoclassical growth models, extended by including the environment and pollution generation. We review the structure of integrated assessment models, distinguishing between finite horizon and infinite horizon models, both deterministic and stochastic. We present a new solution algorithm for infinite horizon integrated assessment models, relying on a neural net approximation of the value function within an iterative version of the Bellman equation. ∗ Research supported by US Department of Energy grant number DE-FG03-96ER62277 to the University of California, Santa Barbara. Department of Economics, University of Miami, Box 248126, Coral Gables, FL 33124. Department of Economics, Bren School of Environmental Science and Management, and Environmental Studies Program, University of California, Santa Barbara, CA 93106-9210.