Economic Concepts, Methods, and Tools for Risk Analysis in Forestry under Climate Change

Abstract

Climate change will affect the expected values and distributions of key variables that influence forest management decisions. Risk analysis will likely play a more prominent role in forestry decision making. There are, however, different types of risk problems and different types of models and approaches to choose from. Three possible models that could have application in a climate change risk context are: (1) the Markowitz Portfolio Frontier Model; (2) Expected Value-variance/Chance Constraint Hybrid Model; (3) Discrete Stochastic Programming. These models are applicable in different contexts and answer different questions. For example, the Markowitz model looks for the asset mix that minimizes portfolio variance subject to a minimum expected return. The expected value-variance/chance constraint model accounts for risk preferences and uncertainty in both objective function and constraints variables. The objective function is to maximize certainty equivalent. The discrete stochastic programming model allows for learning to occur and for the decision maker to modify his/her decisions as new information becomes available over a planning horizon.