Men are from Mars and Women Too: A Bayesian Meta-Analysis of Overconfidence Experiments

Oriana Bandiera, Nidhi Parekh, Barbara Petrongolo and Michelle Rao

No 16939, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: Gender differences in self-confidence could explain women’s under representation in high-income occupations and glass-ceiling effects. We draw lessons from the economic literature via a survey of experts and a Bayesian hierarchical model that aggregates experimental findings over the last twenty years. The experts’ survey indicates beliefs that men are overconfident and women under-confident. Yet, the literature reveals that both men and women are typically overconfident. Moreover, the model cannot reject the hypothesis that gender differences in self-confidence are equal to zero. In addition, the estimated pooling factor is low, implying that each study contains little information over a common phenomenon. The discordance can be reconciled if the experts overestimate the pooling factor or have priors that are biased and precise.

Date: 2022-01
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Related works:
Journal Article: Men are from Mars, and Women Too: A Bayesian Meta‐analysis of Overconfidence Experiments (2022)
Working Paper: Men Are from Mars, and Women Too: A Bayesian Meta-Analysis of Overconfidence Experiments (2022)
Working Paper: Men are from Mars, and women too: a Bayesian meta-analysis of overconfidence experiments (2021)
Working Paper: Men are from Mars, and women too: a Bayesian meta-analysis of overconfidence experiments (2021)
Working Paper: Men Are from Mars, and Women Too: A Bayesian Meta-Analysis of Overconfidence Experiments (2021)
Working Paper: Men are from Mars, and women too: a Bayesian meta-analysis of overconfidence experiments (2021)
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