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When Optimal Choices Feel Wrong: A Laboratory Study of Bayesian Updating, Complexity, and Affect

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  • Charness, Gary
  • Levin, Dan

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.

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Bibliographic Info

Paper provided by Department of Economics, UC Santa Barbara in its series University of California at Santa Barbara, Economics Working Paper Series with number qt7g63k28w.

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Date of creation: 24 Oct 2003
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Handle: RePEc:cdl:ucsbec:qt7g63k28w

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Keywords: Bayesian updating; Reinforcement; Affect; Experimental economics;

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  1. Grether, David M., 1992. "Testing bayes rule and the representativeness heuristic: Some experimental evidence," Journal of Economic Behavior & Organization, Elsevier, Elsevier, vol. 17(1), pages 31-57, January.
  2. Camerer, Colin & Weber, Martin, 1992. " Recent Developments in Modeling Preferences: Uncertainty and Ambiguity," Journal of Risk and Uncertainty, Springer, Springer, vol. 5(4), pages 325-70, October.
  3. Charness, Gary & Levin, Dan, 2003. "When Optimal Choices Feel Wrong: A Laboratory Study of Bayesian Updating, Complexity, and Affect," University of California at Santa Barbara, Economics Working Paper Series, Department of Economics, UC Santa Barbara qt7g63k28w, Department of Economics, UC Santa Barbara.
  4. Drew Fudenberg & David K. Levine, 1996. "The Theory of Learning in Games," Levine's Working Paper Archive 624, David K. Levine.
  5. Camerer, Colin & Ho, Teck-Hua, 1997. "Experience-Weighted Attraction Learning in Games: A Unifying Approach," Working Papers, California Institute of Technology, Division of the Humanities and Social Sciences 1003, California Institute of Technology, Division of the Humanities and Social Sciences.
  6. Grether, David M., . "Bayes Rule as a Descriptive Model: The Representativeness Heuristic," Working Papers, California Institute of Technology, Division of the Humanities and Social Sciences 245, California Institute of Technology, Division of the Humanities and Social Sciences.
  7. Ouwersloot, Hans & Nijkamp, Peter & Rietveld, Piet, 1998. "Errors in probability updating behaviour : Measurement and impact analysis," Journal of Economic Psychology, Elsevier, Elsevier, vol. 19(5), pages 535-563, October.
  8. Samuelson, William & Zeckhauser, Richard, 1988. " Status Quo Bias in Decision Making," Journal of Risk and Uncertainty, Springer, Springer, vol. 1(1), pages 7-59, March.
  9. Gilboa,Itzhak & Schmeidler,David, 2001. "A Theory of Case-Based Decisions," Cambridge Books, Cambridge University Press, Cambridge University Press, number 9780521003117.
  10. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, Elsevier, vol. 8(1), pages 164-212.
  11. Zizzo, Daniel John & Stolarz-Fantino, Stephanie & Wen, Julie & Fantino, Edmund, 2000. "A violation of the monotonicity axiom: experimental evidence on the conjunction fallacy," Journal of Economic Behavior & Organization, Elsevier, Elsevier, vol. 41(3), pages 263-276, March.
  12. Itzhak Gilboa & David Schmeidler, 1992. "Case-Based Decision Theory," Discussion Papers, Northwestern University, Center for Mathematical Studies in Economics and Management Science 994, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
  13. Loomes, Graham & Sugden, Robert, 1982. "Regret Theory: An Alternative Theory of Rational Choice under Uncertainty," Economic Journal, Royal Economic Society, Royal Economic Society, vol. 92(368), pages 805-24, December.
  14. Cheung, Yin-Wong & Friedman, Daniel, 1997. "Individual Learning in Normal Form Games: Some Laboratory Results," Games and Economic Behavior, Elsevier, Elsevier, vol. 19(1), pages 46-76, April.
  15. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, American Economic Association, vol. 88(4), pages 848-81, September.
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