A Monte Carlo Methodology for Solving the Optimal Timber Harvest Problem with Stochastic Timber and Carbon Prices

This article presents a Monte Carlo methodology for solving the stochastic optimal timber harvest problem modeled as a recurrent American call option. A detailed description of the proposed methodology is given, and the Monte Carlo technique is contrasted with finite difference methods typically used to find solutions of the optimal harvest problem with stochastic prices. The use of the methodology is then demonstrated via an example. In the example, expected bare land values and optimal harvest policies are calculated for a Douglas-fir stand in western Washington State. It is assumed that the forest owner derives revenue from traditional timber sales and carbon sequestration, and that prices of timber and carbon follow a known stochastic process. Results of the calculations are discussed.