Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
In labour markets, women are often underrepresented relative to men. This underrepresentation may be due to inaccurate beliefs about ability across genders. Inaccurate beliefs might cause a sampling problem: to have accurate beliefs about a group, one must first collect information about it. However, employers may not wish to shortlist individuals from a group that is perceived to exhibit lower quality. Inaccurate beliefs may also persist due to biased belief updating. We run a stylised hiring experiment to disentangle these two effects. We ask participants to create shortlists from a male and a female pool of workers and give them feedback on the skill of those they shortlist. Based on that information, participants hire workers, and provide us with their beliefs about the distribution of skills in the male and female pots. We study how employers update their beliefs as a function of their past shortlisting behaviour, and how they shortlist given their beliefs. Participants were more likely to sample from the pool with the higher subjective mean quality (on average men) and lower subjective variance. Participants were not Bayesian updaters but there were no gender-specific biases in updating. Sampling more from a pool and spending more time sampling yield more accurate beliefs.