Modeling of timber harvesting options using timber prices as a mean reverting process with stochastic trend

Proper characterization of the timber price process plays a vital role in forest management decisions. The process of long-run timber prices and its implications for harvesting decisions are analyzed for a forest in Ontario, Canada. Timber prices are modeled as a mean reverting process with stochastic trend. The Kalman filter is used to estimate the state–space model. The forecasted prices from the model are used in real options analysis to determine the optimal investment time and optimal investment rule. The results provide insight different from that of other specifications used in earlier literature.

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