Incentives to learn calibration : a gender-dependent impact
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 a 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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- Cesarini, David & Sandewall, Örjan & Johannesson, Magnus, 2003.
"Confidence Interval Estimation Tasks and the Economics of Overconfidence,"
SSE/EFI Working Paper Series in Economics and Finance
535, Stockholm School of Economics.
- Cesarini, David & Sandewall, Orjan & Johannesson, Magnus, 2006. "Confidence interval estimation tasks and the economics of overconfidence," Journal of Economic Behavior & Organization, Elsevier, vol. 61(3), pages 453-470, November.
- Biais, Bruno & Hilton, Denis & Mazurier, Karine & Pouget, Sébastien, 2004.
"Judgmental Overconfidence, Self-Monitoring and Trading Performance in an Experimental Financial Market,"
IDEI Working Papers
259, Institut d'Économie Industrielle (IDEI), Toulouse.
- Bruno Biais & Denis Hilton & Karine Mazurier & Sébastien Pouget, 2005. "Judgemental Overconfidence, Self-Monitoring, and Trading Performance in an Experimental Financial Market," Review of Economic Studies, Oxford University Press, vol. 72(2), pages 287-312.
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