The underrepresentation of women in science, technology, engineering, and mathematics (STEM) fields can begin as early as grade school and intensify at each successive career step so that men greatly outnumber women as scientists and engineers at senior levels. This underrepresentation of women in STEM is a topic of great interest in economics and public policy today. Yet, factors affecting persistence in these fields are not well understood and understanding the nature of the situation especially is limited at the graduate education level. A step in the direction of learning more is represented by a paper released by the National Bureau of Economic Research (NBER) last month. It describes an investigation of peer gender composition in the training process of STEM doctoral degrees.
Using year-to-year variation within doctoral programs in the fraction of each cohort that is female, researchers found that women in cohorts with no female peers are less likely to graduate within six years of initial enrollment than men, but an increase in the share of female peers in a cohort increases the probability of on-time graduation for women as compared to their male counterparts. This effect largely is driven by students in typically male programs (less than 38.5% female students in the average cohort) and by dropout behavior in the first year of enrollment. Peer gender composition has a small effect on first term GPA and no effect on the probability of obtaining research funding. The small/null findings for these two channels suggest that the results largely cannot be explained by women learning or competing more successfully in cohorts with more female peers. The findings are consistent, however, with a climate mechanism, through which more female peers create a female friendly environment that encourages women to persist in doctoral programs, despite having no significant effect on learning or financial support. Taken together, the findings indicate that peer gender composition can be a useful proxy for climate and that yearly variations in this measure can provide a useful identification strategy for investigating gender gaps in outcomes.
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