Examining the Fallout: Who is Hurt by Educational Gender Biases?

Educational biases have been extensively studied, but less attention has been given to how these biases affect individuals within each gender group. We show how to identify average gender bias across the skill distribution of students using a correctly timed blind exam. The results are simple to implement and can be applied to sub-groups based both on students' skills and socioeconomic characteristics. We find that gender bias is highly heterogeneous and is strongest for students with low-skill and low-socioeconomic background. These biases have significant effects on students later life outcomes, such as attending higher-education and labor market performance.