ABSTRACT
Forests are subject to survival risks, usually caused by calamities like insects, fire or storm. If a calamity hits a forest stand, it will reduce its value. Survival functions can be used to provide a probabilistic description of such an event. Economic models for optimal forest management should incorporate this information. Available modeling approaches are usually based on quite specific stochastic assumptions, and most require simulation studies. Here, we provide a more general approach. It is only assumed that the survival function is known, but no assumptions on specific properties are made. It is then shown how survival risks will change optimal management decisions in a stochastic, Faustmann-type model in discrete time. Furthermore, the costs associated with survival risks are exemplified based on real-world data and a Weibull-type survival function. The costs are found to be substantial, dependent on age and particularly on tree species. Consequently, ignoring survival risks in forest management is likely to result in substantial losses.
