Zusammenfassung:
Part-time work is a popular way to reconcile work and family obligations. This study uses large-scale observational data from an online recruitment platform and an online job board to examine how easy it is to get a part-time job and whether this depends on the gender of a jobseeker. First, I relate the number of hours stated on job advertisements to the gender preferences of firms indicated in a confidential online form. Second, I analyze hiring decisions of recruiters who navigate through jobseeker profiles. I estimate contact penalties for male and female jobseekers looking for part-time jobs by applying supervised machine learning to control for all relevant jobseeker characteristics visible to recruiters and by exploiting within jobseeker changes of hours preferences over time. I find that recruiters prefer full-time over part-time workers and that the part-time penalty is much more pronounced for men than for women, even when comparing applicants for the same position. Hence, the gender differences cannot be explained by differences in job or workplace characteristics. Instead, the preponderance of evidence points towards bias coming from gender stereotypes.