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Department of Economics, UCSB
University of California, Santa Barbara

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When Optimal Choices Feel Wrong: A Laboratory Study of Bayesian Updating, Complexity, and Affect
Gary Charness, University of California, Santa Barbara
Dan Levin, Ohio State University

Download the Paper (167 K, PDF file) - October 24, 2003 Tell a colleague about it.
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ABSTRACT:

We examine decision-making under risk and uncertainty in a laboratory experiment. The heart of our design examines how one’s propensity to use Bayes’ rule is affected by whether this rule is aligned with reinforcement or clashes with it. In some cases, we create environments where Bayesian updating after a successful outcome should lead a decision-maker to make a change, while no change should be made after observing an unsuccessful outcome.

We observe striking patterns: When payoff reinforcement and Bayesian updating are aligned, nearly all people respond as expected. However, when these forces clash, around 50% of all decisions are inconsistent with Bayesian updating. While people tend to make costly initial choices that eliminate complexity in a subsequent decision, we find that complexity alone cannot explain our results. Finally, when a draw provides only information (and no payment), switching errors occur much less frequently, suggesting that the ‘emotional reinforcement’ (affect) induced by payments is a critical factor in deviations from Bayesian updating. There is considerable behavioral heterogeneity; we identify different types in the population and find that people who make ‘switching errors’ are more likely to have cross-period ‘reinforcement’ tendencies.

SUGGESTED CITATION:
Gary Charness and Dan Levin, "When Optimal Choices Feel Wrong: A Laboratory Study of Bayesian Updating, Complexity, and Affect" (October 24, 2003). Department of Economics, UCSB. Departmental Working Papers. Paper 9-03.
http://repositories.cdlib.org/ucsbecon/dwp/9-03

 
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