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Cognitive Uncertainty


  • Benjamin Enke
  • Thomas Graeber


This paper introduces a formal definition and an experimental measurement of the concept of cognitive uncertainty: people’s subjective uncertainty about what the optimal action is. This concept allows us to bring together and partially explain a set of behavioral anomalies identified across four distinct domains of decision-making: choice under risk, choice under ambiguity, belief updating, and survey expectations about economic variables. In each of these domains, behavior in experiments and surveys tends to be insensitive to variation in probabilities, as in the classical probability weighting function. Building on existing models of noisy Bayesian cognition, we formally propose that cognitive uncertainty generates these patterns by inducing people to compress probabilities towards a mental default of 50:50. We document experimentally that the responses of individuals with higher cognitive uncertainty indeed exhibit stronger compression of probabilities in choice under risk and ambiguity, belief updating, and survey expectations. Our framework makes predictions that we test using exogenous manipulations of both cognitive uncertainty and the location of the mental default. The results provide causal evidence for the role of cognitive uncertainty in belief formation and choice, which we quantify through structural estimations.

Suggested Citation

  • Benjamin Enke & Thomas Graeber, 2019. "Cognitive Uncertainty," CESifo Working Paper Series 7971, CESifo.
  • Handle: RePEc:ces:ceswps:_7971

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    References listed on IDEAS

    1. Jakub Steiner & Colin Stewart, 2016. "Perceiving Prospects Properly," American Economic Review, American Economic Association, vol. 106(7), pages 1601-1631, July.
    2. Ambuehl, Sandro & Li, Shengwu, 2018. "Belief updating and the demand for information," Games and Economic Behavior, Elsevier, vol. 109(C), pages 21-39.
    3. Stephen G. Dimmock & Roy Kouwenberg & Peter P. Wakker, 2016. "Ambiguity Attitudes in a Large Representative Sample," Management Science, INFORMS, vol. 62(5), pages 1363-1380, May.
    4. Jonathan Robinson & Cheskie Rosenzweig & Aaron J Moss & Leib Litman, 2019. "Tapped out or barely tapped? Recommendations for how to harness the vast and largely unused potential of the Mechanical Turk participant pool," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-29, December.
    5. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    6. David J. Butler & Graham C. Loomes, 2007. "Imprecision as an Account of the Preference Reversal Phenomenon," American Economic Review, American Economic Association, vol. 97(1), pages 277-297, March.
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    Cited by:

    1. Haaland, Ingar & Roth, Christopher & Wohlfart. Johannes, 2020. "Designing Information Provision Experiments," The Warwick Economics Research Paper Series (TWERPS) 1275, University of Warwick, Department of Economics.
    2. Quentin Cavalan & Vincent de Gardelle & Jean-Christophe Vergnaud, 2020. "Overestimate yourself or underestimate others? Two sources of bias in bargaining with joint production," Post-Print halshs-02492289, HAL.

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    More about this item


    cognitive uncertainty; beliefs; bounded rationality;
    All these keywords.

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

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