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

Oriana Bandiera, Nidhi Parekh (), Barbara Petrongolo and Michelle Rao ()
Additional contact information
Nidhi Parekh: J-PAL Africa
Michelle Rao: London School of Economics

No 14950, IZA Discussion Papers from Institute of Labor Economics (IZA)

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.

Keywords: Bayesian meta-analysis; over-confidence; gender gaps (search for similar items in EconPapers)
JEL-codes: C91 J16 (search for similar items in EconPapers)
Pages: 49 pages
Date: 2021-12
New Economics Papers: this item is included in nep-evo, nep-exp, nep-lab and nep-neu
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published - published in: Economica, 2022, 89 (S1), 38 - 70

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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 (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)
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