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

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

JEL Classification: C91, J16