Approximating Risk Aversion in Decision Analysis Applications

This paper investigates the impact of risk aversion in decision analyses under uncertainty with a single evaluation measure and presents a simple procedure for approximately addressing risk aversion in a way that is defensible for many decisions. Speci ̄cally, a simulation study is presented that leads to guidelines for determining when an expected utility analysis should be conducted for a decision, rather than simply an expected value analysis, and what form of utility function should be used for this expected utility analysis. The simulation study shows that a sensitivity analysis using an exponential utility function should be conducted for most decision analyses, but that this sensitivity analysis can often establish, without requiring utility information from the decision maker, that no further utility analysis is required. In addition, when further utility analysis is required, the simulation study shows that this can be done in a simple way using an exponential utility function that will be accurate for many decision analyses. However, in situations where there is equal or greater downside risk than upside potential a more detailed study of the decision maker's utility function may be necessary. Approximating Risk Aversion in Decision Analysis Applications