How to Reveal People's Preferences: Comparing Time Consistency and Predictive Power of Multiple Price List Risk Elicitation Methods

Tamms Csermely,Alexander Rabas

doi:10.2139/ssrn.2573544

Tamms Csermely, Alexander Rabas

Open Access

https://doi.org/10.2139/ssrn.2573544

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Abstract

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 them, we conduct a holistic investigation of the most prevalent method, the multiple price list (MPL) and its derivations. In our experiment, we find that revealed preferences differ under various versions of MPLs as well as yield unstable results within a 30-minute time frame. We determine the most stable elicitation method with the highest forecast accuracy by using multiple measures of within-method consistency and 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. As we pinpoint each MPL characteristic's effect on the revealed preference and its consistency, our results have implications for preference elicitation procedures in general.

Highlights

Risk is a fundamental concept that affects human behavior and decisions in many real-life situations
Due to the ample evidence on the violations of expected utility theory (EUT), we provide the same regressions by taking probability weighting,30 prospect theory31 and cumulative prospect theory into consideration
Our findings are further supported by the fact that we controlled for personality traits, order effects, various socioeconomic factors and cognitive reflection in our analyses

Summary

Introduction

Risk is a fundamental concept that affects human behavior and decisions in many real-life situations. Since the seminal papers by Holt and Laury (2002, 2005), approximately 20 methods have been published which provide alternatives to elicit risk preferences. They differ from each other in terms of the varied parameters, representation and framing. There are significant differences in results depending on the method used, as an increasing amount of evidence suggests It follows that if someone’s revealed preference is dependent on the measurement method used, scientific results and real-world conclusions might be biased and misleading

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Conclusion