Effects of stochastic interest rates in decision making under risk: A Markov decision process model for forest management

Most economic studies of forest decision making under risk assume a fixed interest rate. This paper investigated some implications of this stochastic nature of interest rates. Markov decision process (MDP) models, used previously to integrate stochastic stand growth and prices, can be extended to include variable interest rates as well. This method was applied to Douglas-fir/western hemlock forests in the Pacific Northwest of the United States. An MDP model was used to find the harvest decisions that maximized the forest value of a stand in a particular state, given the price level and interest rate. This optimal policy was compared with the policy that would hold in the same context but with an interest rate fixed at its historical average. The results showed that when the interest rate was lower than its historical average, the best decision differed for 52 of the 192 possible combinations of stand state and price level. Assuming a fixed interest rate underestimated the forest value by 4% to 16% depending on the initial condition. However, applying the harvest policy derived with a fixed interest rate led to a loss of no more than 7% depending on the initial condition. Taking explicit account of the variability of interest rate in setting harvest policies had some unexpected ecological benefits.

Research highlights► Markov decision process models take into account risk in forest growth, stumpage prices, and interest rates. ► Optimal harvest decisions are adaptive to risk and improve the net present value.