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Managing Self-Confidence: Theory and Experimental Evidence

Author

Listed:
  • Markus M. Möbius

    (Microsoft Research New England, Cambridge, Massachusetts 02142; University of Michigan, Ann Arbor, Michigan 48109; National Bureau of Economic Research, Cambridge, Massachusetts 02138)

  • Muriel Niederle

    (National Bureau of Economic Research, Cambridge, Massachusetts 02138; Stanford University, Stanford, California 94305)

  • Paul Niehaus

    (National Bureau of Economic Research, Cambridge, Massachusetts 02138; University of California San Diego, La Jolla, California 92093)

  • Tanya S. Rosenblat

    (University of Michigan, Ann Arbor, Michigan 48109)

Abstract

We use a series of experiments to understand whether and how people’s beliefs about their own abilities are biased relative to the Bayesian benchmark and how these beliefs then affect behavior. We find that subjects systematically and substantially overweight positive feedback relative to negative (asymmetry) and also update too little overall (conservatism). These biases are substantially less pronounced in an ego-free control experiment. Updating does retain enough of the structure of Bayes’ rule to let us model it coherently in an optimizing framework, in which, interestingly, asymmetry and conservatism emerge as complementary biases. We also find that exogenous changes in beliefs affect subjects’ decisions to enter into a competition and do so similarly for more and less biased subjects, suggesting that people cannot “undo” their biases when the time comes to decide.

Suggested Citation

  • Markus M. Möbius & Muriel Niederle & Paul Niehaus & Tanya S. Rosenblat, 2022. "Managing Self-Confidence: Theory and Experimental Evidence," Management Science, INFORMS, vol. 68(11), pages 7793-7817, November.
  • Handle: RePEc:inm:ormnsc:v:68:y:2022:i:11:p:7793-7817
    DOI: 10.1287/mnsc.2021.4294
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    More about this item

    Keywords

    asymmetric belief updating; conservatism; information aversion; overconfidence;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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