2014/10/01 by Tamás Csermely, Csermely, Tamás, Alexander Rabas +1
Business, Management and Accounting · Decision Sciences · Economics, Econometrics and Finance · Mathematics · #Actuarial science #Artificial intelligence #Computer science #Consistency (knowledge bases) #Consumer Market Behavior and Pricing #Decision-Making and Behavioral Economics #Econometrics #Economic and Environmental Valuation #Economics #Field (mathematics) #Mathematical economics #Mathematics #Multitude #Order (exchange) #Predictive power #Selection (genetic algorithm) #Stochastic game #Time consistency
paper · open access · doi:10.57938/a6fa10ac-1597-4f68-9cc9-94f451eb9a77
published in RePEc: Research Papers in Economics (Federal Reserve Bank of St. Louis)
openalex publication_date 2014/10/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
The question of how to measure and classify people´s risk preferences is of substantial importance in the field of <br/>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. (authors' abstract)