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Incentives to Learn Calibration: A Gender-Dependent Impact

Author

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  • Marie-Pierre Dargnies

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Guillaume Hollard

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique, PSE - Paris School of Economics - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS-PSL - École normale supérieure - Paris - PSL - Université Paris Sciences et Lettres - EHESS - École des hautes études en sciences sociales - ENPC - École nationale des ponts et chaussées - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

Abstract

Miscalibration can be defined as the fact that people think that their knowledge is more precise than it actually is. In a typical miscalibration experiment, subjects are asked to provide subjective confidence intervals. A very robust finding is that subjects provide too narrow intervals at the 90% level. As a result a lot less than 90% of correct answers fall inside the 90% intervals provided. As miscalibration is linked with bad results on an experimental financial market (Biais et al., 2005) and entrepreneurial success is positively correlated with good calibration (Regner et al., 2006), it appears interesting to look for a way to cure or at least reduce miscalibration. Previous attempts to remove the miscalibration bias relied on extremely long and tedious procedures. Here, we design an experimental setting that provides several different incentives, in particular strong monetary incentives i.e. that make miscalibration costly. Our main result is that a thirty-minute training session has an effect on men's calibration but no effect on women's.

Suggested Citation

  • Marie-Pierre Dargnies & Guillaume Hollard, 2009. "Incentives to Learn Calibration: A Gender-Dependent Impact," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00649246, HAL.
  • Handle: RePEc:hal:cesptp:hal-00649246
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    Cited by:

    1. Madiès, Thierry & Villeval, Marie Claire & Wasmer, Malgorzata, 2013. "Intergenerational attitudes towards strategic uncertainty and competition: A field experiment in a Swiss bank," European Economic Review, Elsevier, vol. 61(C), pages 153-168.
    2. Michał Krawczyk, 2011. "Overconfident for real? Proper scoring for confidence intervals," Working Papers 2011-15, Faculty of Economic Sciences, University of Warsaw.

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    Keywords

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    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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