Using Danish matched employer-employee data, I compare the relative pay of men and women to their relative productivity as measured by production function estimation. I find that the gender "productivity gap" is 8 percent, implying that almost two thirds of the residual gender wage gap is due to productivity differences between men and women. Motherhood plays an important role, yet it also reveals a puzzle: the pay gap for mothers is entirely explained by productivity, whereas the gap for non-mothers is not. In addition, the decoupling of pay and productivity for women without children happens during their prime-child bearing years. These estimates are robust to a variety of specifications for the impact of observables on productivity, and robust to accounting for endogenous sorting of women into less productive firms using a control-function approach. This paper also provides estimates of the productivity gap across industries and occupations, finding the same general patterns for mothers compared to women without children within these subgroups.

It is common for mentorship programs to use race, gender, and nationality to match mentors and mentees. Despite the popularity of these programs, there is little evidence on whether mentees value mentors with shared traits. Using novel administrative data from an online college mentoring platform connecting students and alumni, we document that female students indeed disproportionately reach out to female mentors. To disentangle whether this observed homophily is explained by taste-based or statistical discrimination, we implement a preference elicitation survey paired with an within-survey experiment. We find that homophily is entirely explained by a lack of information on mentor quality. We discuss the implications of these results for the design of initiatives that match on shared traits.

We document the declining gap between the average earnings of women and men in Denmark from 1980 to 2010. The decline in the earnings gap is driven by increases in hours worked by women as well as a decline in the gender wage gap. The data show a great deal of segregation across education tracks, occupations, and even workplaces, but this segregation has declined since 1980. These changes in segregation have been accompanied by a reduction in the role of observables in explaining the gender wage gap. The residual gender wage gap has been constant since 1980. The hours gap is not affected by changes in segregation at the occupation and education level: differences in these characteristics for women relative to men do not contribute to the hours gap in 2010 and they did not in 1980. However, a firm-worker fixed effects analysis suggests that 30 percent of the gender hours gap can be explained by the sorting of women into lower-hours workplaces. The hours gap is driven by mothers, the group for whom differences in employer, occupation, education, and experience also imply large differences in wages. The combined effect of hours and wages is a more than 20 percent gender earnings gap among well-attached (halftime-plus) workers between 25 and 60 years old, 10 percent of which cannot be explained by differences in hours, or in the readily observable characteristics of these workers.

Gender differences in professional networks have been shown to contribute to men’s and women’s disparate labor market outcomes. This gap could be due to differences in network access, differences in network usage, or both. Using novel administrative data from a student-alumni professional networking website, we study gender differences in student network usage, holding network access fixed. Focusing on messages sent by students to alumni, we document that male and female students network similarly, both in terms of the number of messages sent and the specific questions asked. Furthermore, there are only small gender differences in question tone.