How to reveal people's preferences: Comparing time consistency and predictive power of multiple price list risk elicitation methods

The question of how to measure and classify people’s risk preferences is of substantial importance in the field of Economics. Inspired by the multitude of ways used to elicit risk preferences, we conduct a holistic investigation of the most prevalent method, the multiple price list (MPL) and its derivations. In accordance with previous literature, we find that revealed preferences differ under various and even the same versions of the MPL. Thus, an arbitrary selection of a particular risk assessment method can lead to biased results especially if researchers investigate its connection to other phenomena. In order to resolve this issue, we determine the most stable version of the MPL by using multiple measures of within-method consistency, and the version with the highest forecast accuracy by using behavior in two economically relevant games as benchmarks. A derivation of the well-known method by Holt and Laury (2002), where the highest payoff is varied instead of probabilities, emerges as the best MPL method in both dimensions.