Men Are from Mars, and Women Too: A Bayesian Meta-Analysis of Overconfidence Experiments - Oriana Bandiera; Nidhi Parekh; Barbara Petrongolo; Michelle Rao (Center for Economic Studies and ifo Institute (CESifo), 2022)
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.
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