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Cognitive heterogeneity and complex belief elicitation

Published online by Cambridge University Press:  14 March 2025

Ingrid Burfurd*
Affiliation:
Centre for Market Design, Department of Economics, The University of Melbourne, Melbourne, Australia
Tom Wilkening*
Affiliation:
Deparment of Economics, The University of Melbourne, Melbourne, Australia

Abstract

The Stochastic Becker-DeGroot-Marschak (SBDM) mechanism is a theoretically elegant way of eliciting incentive-compatible beliefs under a variety of risk preferences. However, the mechanism is complex and there is concern that some participants may misunderstand its incentive properties. We use a two-part design to evaluate the relationship between participants’ probabilistic reasoning skills, task complexity, and belief elicitation. We first identify participants whose decision-making is consistent and inconsistent with probabilistic reasoning using a task in which non-Bayesian modes of decision-making lead to violations of stochastic dominance. We then elicit participants’ beliefs in both easy and hard decision problems. Relative to Introspection, there is less variation in belief errors between easy and hard problems in the SBDM mechanism. However, there is a greater difference in belief errors between consistent and inconsistent participants. These results suggest that while the SBDM mechanism encourages individuals to think more carefully about beliefs, it is more sensitive to heterogeneity in probabilistic reasoning. In a follow-up experiment, we also identify participants with high and low fluid intelligence with a Raven task, and high and low proclivities for cognitive effort using an extended Cognitive Reflection Test. Although performance on these tasks strongly predict errors in both the SBDM mechanism and Introspection, there is no significant interaction effect between the elicitation mechanism and either ability or effort. Our results suggest that mechanism complexity is an important consideration when using elicitation mechanisms, and that participants’ probabilistic reasoning is an important consideration when interpreting elicited beliefs.

Type
Original Paper
Copyright
Copyright © 2021 Economic Science Association

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Footnotes

Electronic supplementary material The online version of this article (https://doi.org/10.1007/s10683-021-09722-x) contains supplementary material, which is available to authorized users.

We gratefully acknowledge the financial support of the Australian Research Council (DE140101014) as well as the Faculty of Business and Economics at the University of Melbourne. Raw data, the programs used to analyze the data, and the programs used to run the experiment are available at https://osf.io/ex26f/.

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