This paper provides evidence that a person's gender influences the way others interpret information about his or her ability and documents the implications for gender inequality in labor markets. Using data on physicians' referrals to surgical specialists, I find that referring physicians view patient outcomes differently depending on the performing surgeon's gender. Physicians become more pessimistic about a female surgeon's ability than a male's after a patient death, indicated by a sharper drop in referrals to the female surgeon. However, physicians become more optimistic about a male surgeon's ability after a good patient outcome, indicated by a larger increase in the number of referrals the male surgeon receives. Physicians also change their behavior toward other female surgeons after a bad experience with one female surgeon, becoming less likely to refer to new women in the same specialty. There are no such spillovers to other men after a bad experience with one male surgeon. Consistent with learning models, physicians' reactions to events are strongest when they have just begun to refer to a surgeon. However, the empirical patterns are consistent with Bayesian learning only if physicians do not have rational expectations about the true distribution of surgeon ability.
How is credit for group work allocated when individual contributions are not perfectly observed? Do demographic traits like gender influence the allocation of credit? Using data from academic economists' CVs, I test whether coauthored and solo-authored publications matter differently for tenure for men and women. Because coauthors are listed alphabetically in economics, coauthored papers do not provide specific information about each contributor's skills or ability. Solo-authored papers, on the other hand, provide a relatively clear signal of ability. I find that men are tenured at roughly the same rate regardless of whether they coauthor or solo-author. Women, however, become less likely to receive tenure the more they coauthor. The result is most pronounced for women coauthoring with men and less pronounced among women who coauthor with other women. I contrast economics with sociology, a discipline in which coauthors are listed in order of contribution, and find that when contributions are made clear, men and women receive equal credit for coauthored papers.
Does a confidence gap exist between men and women who made it to the very top of their careers? Using data from a select group of economists working in top U.S. universities, we find that women are still less confident than men along two margins. First, when asked about their level of agreement on survey questions about the economy, women are less likely to give “extreme” answers in which they strongly agree or disagree. Second, women are less confident in the accuracy of their answer. The results persist after controlling for the year the PhD was granted, the PhD awarding institution, the current institution, and the number of solo and co-authored publications up to the point of tenure. We provide suggestive evidence that the confidence gap is driven by women being less confident when asked questions that are outside their field of expertise.
How is credit for group work allocated when individual contributions are not observed? I use data on academics’ publication records to test whether demographic traits like gender influence how credit allocated under such uncertainty. While solo-authored papers send a clear signal about ability, coauthored papers are noisy, providing no specific information about each contributor’s skills. I find that men are tenured at roughly the same rate regardless of coauthoring choices. Women, however, are less likely to receive tenure the more they coauthor. The result is much less pronounced among women who coauthor with other women.
There is evidence that, in some contexts, income shocks cause conflict. The literature demonstrating this relationship uses rainfall shocks to instrument for income shocks, arguing that in agriculturally-dependent regions, negative rain shocks lower income which incites violence. This identification strategy relies on the assumption that rainfall shocks affect conflict only through their impacts on income. This paper evaluates this exclusion restriction in the context of religious conflict in India. Using data on dam construction, I identify districts that are downstream from irrigation dams and show that income in these areas is much less sensitive to rainfall fluctuations. However, rain shocks remain equally strong predictors of riot incidence in these districts. I explore other channels through which rainfall might affect conflict.