Working Paper
Working Paper. “Life-cycle Returns to Math and Social Skills: The Roles of Gender, Sorting and Employer Learning”.Abstract

This paper documents gender differences in life-cycle returns to social skills and math skills in the labor market. Using the National Longitudinal Survey of Youth 1979 data, I test for whether women and men sort into occupations that match with their pre-market skills, and whether there are increasing returns to skills as employers learn about workers' abilities over time. Workers with higher social skills choose occupations that put higher emphasis on job interactions, but this sorting effect is stronger for men than for women and the gap is widening over the life-cycle. Math skills are also positively correlated with social characteristics of an occupation such as leadership activities, and there is a significant gender gap in sorting by math skills. I then follow the employer learning literature to estimate the returns to each skill and the growth of returns with experience. Returns to social skills and math skills grow at a faster rate for men than for women, suggesting differential speed of employer learning. However, the initial of return to a female worker’s math skills is significantly higher such that on average women enjoy higher returns to math skills in the first 10-15 years of their career. These findings reflect gender differences in both workers’ occupational sorting and employers’ belief updating process, and suggest a higher return to investing in skills that counter beliefs about gender stereotypes.

Forthcoming. “Gender Bias in Rumors Among Professionals: An Identity-based Interpretation.” Review of Economics and Statistics.Abstract

This paper measures gender bias in what people say about women versus men in an anonymous online professional forum. I study the content of posts that refer to each gender, and the transitions in the topics of discussion that occur between consecutive posts in a thread once attention turns to one gender or the other. I find that discussions about women tend to highlight their personal characteristics (such as physical appearance or family circumstances) rather than their professional accomplishments. Posts about women are also more likely to lead to deviations from professional topics than posts about men. I interpret these findings through a model that highlights posters’ incentives to boost their own identities relative to the underrepresented out-group in a profession.

5/2018. “Gendered Language on the Economics Job Market Rumors Forum.” AEA Papers and Proceedings, 108, Pp. 175-179. Data & Code Paper Appendix