Automation and Gender: Implications for Occupational Segregation and the Gender Skill Gap
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Department of Economics
Occupational segregation by gender, although still sizable, has decreased significantly over the last few decades. Women have also made marked gains in education relative to men, with the gender gap in college education reversing in favor of women since the early 1990s. In this paper, we examine the contribution of automation to both these phenomena. Specifically, we analyze the effects of automation on the occupational structure of men and women and overall occupational segregation as well as gender differences in skill investments. We start by documenting two facts: (1) in 1980, women were much more likely than men to be in occupations with a high risk of automation, and (2) the cross-occupational relationship between risk of automation in 1980 and the change in worker share between 1980 and 2017, though negative for both genders, is much steeper for women. Taken together, these two facts suggest that women were more likely to be displaced by automation.
Exploiting cross-commuting zone variation in the share of workers in occupations that face a high risk of automation, we show that women, for a given shock in the risk of automation, were much more likely than men to transition out of routine task intensive occupations to occupations requiring higher levels of skill. The net effect is that local labor markets that were more affected by automation experienced greater occupational integration by gender. We examine potential channels such as the growing demand for social skills that favor women and their greater ability to upskill. Consistent with these channels, we find that local labor markets that were more susceptible to automation saw larger increases in the share of young women completing college relative to men and a greater movement of women to occupations with high math and high social skill requirements.