Structural Estimation of the Stochastic Dynamic Decision Problems of Resource Users: An Application to the Timber Harvest Decision

This paper examines a method for structural estimation of the stochastic dynamic decision problems of resource users. The method involves nesting a stochastic dynamic programming algorithm within a maximum likelihood routine. An application to the timber harvest decision indicates that owners of slash pine plantations in southeast Georgia use a low discount rate and treat timber price as a random walk. Moreover, the harvest decision is apparently dominated by profit shocks overlooked in the usual models of the harvest decision.