The Pipeline Problem: Quantitative Models to Estimate the Effects Of Gender and Education on the Stem Workforce

摘要

Although women obtain degrees in the fields of Science, Technology, Engineering, and Mathematics (STEM) at lower rates than their male counterparts, this difference does not alone account for the similarly large disparity of men and women working in STEM jobs. Using data from the American Community Survey for 2015, I run a survey of models, including linear and logistic regressions as well as propensity matching, to investigate the extent to which women are underrepresented, even after accounting for education. The results show that for women, the benefit of a STEM degree on STEM job placement rates is significantly lower than it is for their male counterparts; in some estimates, the effect is halved. The models diverge somewhat on the extent to which this is correlated with a lower baseline of women without STEM degrees working STEM jobs (compared to similar men), but all provide grounds to reject the notion that workforce disparity is attributable solely or even primarily to education.