Predicting the Present Value Distribution of a Forest Plantation Investment

Abstract

Abstract Forestry investment decisions may be based on the probability distribution of financial return in addition to a point estimate of mean return. This study describes an approach to predicting the present value distribution of a plantation investment using actual data on timber price and yield. Changes in stumpage price are modeled with a lognormal diffusion process called geometric Brownian motion (GBM). Timber yield is modeled with a variant of GBM that includes an age-dependent growth component. Model parameters are estimated with time-series observations of loblolly pine (Pinus taeda L.) price and yield in the southeastern United States. Because GBM models have lognormally distributed errors, present value distributions are skewed with extremely long right-hand tails. The median and quartiles of the distribution provide a better measure of central tendency and spread than do the mean and standard deviation. A median-maximizing feedback cutting rule does not perform any better than a median-maximizing fixed rotation age suggesting that no economic gain can be obtained by monitoring timber price and yield under the assumptions of our models. The forecast error, measured by the distance between quartiles, is about twice the size of the median present value. System error is the primary cause, and error in the price process contributes more to the variability in present value than does error in the yield process. Parameter uncertainty increases forecast error 15 to 35%. The large forecast error raises the question of whether better predictive models can be built or whether the present value of a plantation investment is inherently uncertain. For. Sci. 42(3):378-388.