Incentives to learn calibration: a gender-dependent impact
AbstractMiscalibration 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.
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Bibliographic InfoArticle provided by AccessEcon in its journal Economics Bulletin.
Volume (Year): 29 (2009)
Issue (Month): 3 ()
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miscalibration; overconfidence; incentives; gender effect;
Other versions of this item:
- Marie-Pierre Dargnies & Guillaume Hollard, 2008. "Incentives to Learn Calibration : a Gender-Dependent Impact," UniversitÃ© Paris1 PanthÃ©on-Sorbonne (Post-Print and Working Papers) halshs-00348826, HAL.
- Marie-Pierre Dargnies & Guillaume Hollard, 2008. "Incentives to learn calibration : a gender-dependent impact," Documents de travail du Centre d'Economie de la Sorbonne v08088, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
- C9 - Mathematical and Quantitative Methods - - Design of Experiments
- D8 - Microeconomics - - Information, Knowledge, and Uncertainty
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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