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Confidence biases and learning among intuitive Bayesians

Author

Listed:
  • Louis Lévy-Garboua

    () (Université Paris 1 Pantheon-Sorbonne, and Centre d’Economie de la Sorbonne, 106-112 Bd de l’Hôpital)

  • Muniza Askari

    () (Centre d’Economie de la Sorbonne)

  • Marco Gazel

    () (Université Paris 1 Pantheon-Sorbonne, and Centre d’Economie de la Sorbonne, 106-112 Bd de l’Hôpital)

Abstract

We design a double-or-quits game to compare the speed of learning one’s specific ability with the speed of rising confidence as the task gets increasingly difficult. We find that people on average learn to be overconfident faster than they learn their true ability and we present an intuitive-Bayesian model of confidence which integrates confidence biases and learning. Uncertainty about one’s true ability to perform a task in isolation can be responsible for large and stable confidence biases, namely limited discrimination, the hard–easy effect, the Dunning–Kruger effect, conservative learning from experience and the overprecision phenomenon (without underprecision) if subjects act as Bayesian learners who rely only on sequentially perceived performance cues and contrarian illusory signals induced by doubt. Moreover, these biases are likely to persist since the Bayesian aggregation of past information consolidates the accumulation of errors and the perception of contrarian illusory signals generates conservatism and under-reaction to events. Taken together, these two features may explain why intuitive Bayesians make systematically wrong predictions of their own performance.

Suggested Citation

  • Louis Lévy-Garboua & Muniza Askari & Marco Gazel, 2018. "Confidence biases and learning among intuitive Bayesians," Theory and Decision, Springer, vol. 84(3), pages 453-482, May.
  • Handle: RePEc:kap:theord:v:84:y:2018:i:3:d:10.1007_s11238-017-9612-1
    DOI: 10.1007/s11238-017-9612-1
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    More about this item

    Keywords

    Confidence biases; Intuitive-Bayesian; Learning; Double or quits experimental game; Doubt; Contrarian illusory signals;
    All these keywords.

    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
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles

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