Multi-Dimensional Skills and Gender Differences in STEM Majors
利用纵向数据估计广义Roy模型，研究大学前技能如何影响STEM专业选择与毕业，发现高数学能力女性自我效能感低，导致辍学，而针对性干预可改善其毕业率和劳动力市场结果。
Abstract This paper studies the relationship between pre-college skills and gender differences in STEM majors. I use longitudinal data to estimate a generalised Roy model of initial major choices and subsequent graduation outcomes. I recover students’ latent math ability, non-cognitive skills and math self-efficacy. High–math-ability women have lower math self-efficacy than men. Mathematical ability and self-efficacy shape the likelihood of STEM enrolment. A lack of math self-efficacy drives women’s drop out from STEM majors. I find large returns to STEM enrolment for high–math-ability women. Well-focused math self-efficacy interventions could improve women’s STEM graduation rates and labour market outcomes.