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On Prior Confidence and Belief Updating

Author

Listed:
  • Kenneth Chan
  • Gary Charness
  • Chetan Dave
  • J. Lucas Reddinger

Abstract

We experimentally investigate how confidence over multiple priors affects belief updating. Theory predicts that the average Bayesian posterior is unaffected by confidence over multiple priors if average priors are the same. We manipulate confidence by varying the time subjects view a black-and-white grid, the proportion representing the prior in a Bernoulli distribution. We find that when subjects view the grid for a longer duration, they have more confidence, under-update more, and place more (less) weight on priors (signals). Overall, confidence over multiple priors matters when it should not, while confidence in prior beliefs does not matter when it should.

Suggested Citation

  • Kenneth Chan & Gary Charness & Chetan Dave & J. Lucas Reddinger, 2024. "On Prior Confidence and Belief Updating," Papers 2412.10662, arXiv.org, revised May 2025.
    • Handle: RePEc:arx:papers:2412.10662
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    References listed on IDEAS

    as
    1. Ned Augenblick & Eben Lazarus & Michael Thaler, 2025. "Overinference from Weak Signals and Underinference from Strong Signals," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 140(1), pages 335-401.
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    More about this item

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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