A Binomial Tree Approach to Valuing Fixed Rotation Forests and Flexible Rotation Forests Under a Mean Reverting Timber Price Process
AbstractNPV and LEV are established and common approaches to valuing single rotation and infinite rotation forests respectively, when the rotation age is fixed in advanced. More recently, Real Options approaches have been employed to value single and infinite rotation forests with a flexible harvest age. Under a stochastic timber price process, it has been shown that the valuation of a flexible rotation forest is equal or higher than that of a fixed rotation forest, because a flexible harvest regime delays the harvest if the timber price is not favourable, whereas a fixed harvest regime would proceed to harvest regardless of the price. Often, valuation of fixed and flexible rotation ages are compared using 2 different methods – NPV (or LEV) and Real Options. The latter tends to have higher data requirements, employ different assumptions and is much more complex to estimate. Because of these differences, it may be difficult to isolate the cause of the increased valuation. In this work, we apply a relatively simple Binomial Tree method from Guthrie (2009) to value both fixed rotation and flexible rotation forests. This method uses the same data, with the same assumptions for both valuations. By holding everything equal, the difference in valuation is solely attributable to the fixed versus flexible harvesting decisions. Original results for both single and infinite rotations are presented using New Zealand Radiata Pine data. Under a mean reverting timber price process, the Binomial Tree approach offers useful insights on the increased valuation due to flexible harvest decisions.
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Bibliographic InfoPaper provided by New Zealand Agricultural and Resource Economics Society in its series 2010 Conference, August 26-27, 2010, Nelson, New Zealand with number 96836.
Date of creation: Aug 2010
Date of revision:
NPV; LEV; Real Options; Optimal Harvest Decision; Agribusiness; Crop Production/Industries; Environmental Economics and Policy; Land Economics/Use;
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