Recursive Preferences in Forest Management

In this study we find an optimal continuous harvest cutting schedule for a stochastically growing forest stand managed by a risk-averse forest owner. The stand in question is even-aged and the owner is strictly interested in monetary rewards. Expected Net Present Value is a commonly used criterion for determining optimal management schedule for stochastically growing forest stands. However, this method only applies to a case where the owner is risk neutral. If the owner has other risk preferences, the modeling should be done using a utility function. Expected Utility approach is the most common way to handle stochasticity in an atemporal framework, although there are some theoretical concerns in using Expected Utility. From a practical point of view, it leaves something to be desired as it does not reveal the behavioral motivation behind a chosen optimum, namely it cannot distinguish the effects of time preference and risk attitudes. Non-Expected Utility, or more specifically, a Recursive Preferences approach, is a reasonably recent development. The Recursive Preferences approach is able to disentangle risk-aversion and intertemporal substitution effects when measuring utility in a dynamic setting, and thus using this approach aforementioned problems can be overcome. In this paper the Recursive Preference approach is applied to the case of forest management. By using this framework the relative importance of reasons behind specific management schedule, namely risk aversion versus intertemporal substitution, can be weighted. In that way the new measure produces additional valuable information. Additionally, as Expected Utility is a special case of the Non-Expected Utility formulation, the outcomes from these models can be easily compared. The resulting measure is also less objectionate from theoretical grounds compared to the traditional Expected Utility measure. The approach has been used in macroeconomic literature during the past ten years, but it was only recently applied to a micro level resource problem.