Stochastic Control Modelling for Forest Stand Management Under Uncertain Environments

Abstract

In this paper, a stochastic control model is constructed by incorporating geometric Brownian motion to capture uncertain price dynamics into a one-stage and two-state stochastic dynamic programming model. The proposed model is to search for optimal harvest timing under price uncertainty without considering other forestry operations, e.g., thinning. We consider an additional option to replant a forest stand or to abandon the management for another use of a forest land besides harvesting. Our experimental analysis shows that optimal harvest timing under stochastic log prices is delayed when the price level is crucial to maintain the management. It is also showed that when the current log price is sufficiently high, optimal harvest timing from the stochastic and the deterministic approach becomes the same. With a downward trend on price dynamics, optimal harvest timing tends to be hastened overall. This stems from the fact of a depreciation effect on the future return, which stimulates harvesting at an earlier period.