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 20 years. The experts’ survey indicates beliefs that men are overconfident and women underconfident. 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.