On Learning and Growth
CIRPEE Working Paper 13-36
60 Pages Posted: 26 Oct 2013 Last revised: 20 Oct 2015
Date Written: October 2015
Abstract
We study optimal growth under learning. We extend the Mirman-Zilcha stochastic growth results characterizing optimal programs for general utility and production functions to the case of learning. We then use recursive methods to study the effect of learning on the dynamic program by considering the case of iso-elastic utility and linear production, for general distributions of the random shocks and beliefs (i.e., without the use of conjugate priors), for any horizon. Finally, we address the issue of experimentation by providing a solution to an infinite-horizon optimal dynamic program.
Keywords: Brock-Mirman environment, Dynamic programming, Euler equation, Experimentation, Learning, Optimal growth
JEL Classification: D8, D9, E2
Suggested Citation: Suggested Citation