Stochastic Price Models and Optimal Tree Cutting: Results for Loblolly Pine
Abstract
An empirical investigation of stumpage price models and optimal harvest policies is conducted for loblolly pine plantations in the southeastern United States. The stationarity of monthly and quarterly series of sawtimber prices is analyzed using a unit root test. The statistical evidence supports stationary autoregressive models for the monthly series and for the quarterly series of opening month prices. In contrast, the evidence supports a non-stationary random walk model for the quarterly series of average prices. This conflicting result is likely an artifact of price averaging. The properties of these series significantly affect the forms of optimal price-dependent harvest rules and expected returns. Further, the results have implications for conclusions about market efficiency and the performance of a fixed rotation age.