The Long-Term Effects of Teachers' Gender Bias

This paper studies the effects of teachers' gender biases on students' long-term outcomes, including high school completion, college attendance, and formal sector employment. I measure teacher bias using differences in gender gaps between teacher-assigned and blindly-graded tests, and validate the assessment-based measure with novel data on teachers' attitudes, as captured by the Implicit Association Test (IAT). I develop a large-scale online portal available to teachers and students in Peruvian public schools to collect IAT scores nationwide. This analysis provides evidence that math teachers who strongly associate males with scientific disciplines give higher scores to male students, when compared to blindly-graded test scores, while language arts teachers who strongly associate females with humanities-based disciplines award higher grades to female students. Next, using graduation, college enrollment, and matched employer-employee data on 1.7 million public high school students who were expected to graduate between 2015 and 2019, I find that female students who are assigned to more biased teachers are less likely to complete high school and apply to college than male students. Moreover, female students assigned to more biased teachers in high school are less likely to hold a job in the formal sector after graduation and have fewer paid working hours relative to their male classmates. Exposure to gender-biased teachers also leads to monthly earnings losses for women, further exacerbating the gender pay gap.