Gender gaps in academic achievement vary across subjects and assessment types: girls outperform boys on teacher-assigned course grades and on standardized reading tests, while gaps in math test scores favor boys in early grades but reverse by middle school. I investigate how teachers' impacts on these outcomes differ for boys and girls, and what explains the heterogeneity. Using longitudinal administrative data from North Carolina, I estimate value-added measures for fifth-grade teachers separately for test scores and course grades, and find that they have systematically different impacts by student gender: teachers with high test-score value-added disproportionately benefit girls' test scores and course grades, while teachers with high course-grade value-added disproportionately benefit boys' test scores and course grades. I develop a two-factor model wherein unobserved cognitive and non-cognitive skills combine in different proportions to produce observed test scores and course grades, with test scores placing a higher weight on cognitive skills than grades. Under this framework, observed gender gaps imply that boys have a relative proficiency in cognitive skills and girls have a relative proficiency in non-cognitive skills. A teacher's effectiveness for a given skill dimension has larger impacts (a) on outcomes that use that skill more intensively, and (b) for students with a relative deficiency in that skill. In addition to predicting the gender-differentiated impacts, the framework predicts that teachers should have heterogeneous impacts connected to students' relative skill standing -- independent of gender -- a prediction consistent with a student-level test. The effects of course-grade value-added extend to high school: fifth-grade teachers with high course-grade value-added increase boys' likelihood of graduating high school, with no measurable effect for girls. These findings link multidimensional teacher effectiveness with multidimensional gender gaps in student achievement, suggesting that teacher effectiveness is not a single attribute and that its multidimensionality matters for which students benefit.
Affirmative action programs are often criticized because of concerns that they result in lower worker productivity and efficiency losses. We study the relative productivity of workers benefiting from an aggressive affirmative action policy in a setting where hiring constraints are especially likely to bind. In India, colleges are required to reserve approximately 50 percent of faculty hires for individuals from disadvantaged caste and social class groups. We collect and analyze data from a nationally representative sample of 50 engineering and technology colleges in India, some of which randomly assign students to classrooms. We find that reservation category faculty have lower levels of education, lower professorial ranks and fewer years of experience in academia than general category faculty who are not hired through reservations. Yet, even with lower qualifications, we find no evidence that reservation category faculty provide lower quality instruction across a wide range of measures that include course grades, follow-on course grades, standardized test scores, dropout, attendance, graduate school plans, and graduation. In fact, we find that, at least for immediate effects on course grades, students taught by reservation category faculty perform slightly better than students taught by general category faculty. We find no evidence of positive "teacher-like-me" effects of reservation category faculty on the relative course performance and longer-term outcomes of reservation category students. Furthermore, even in the face of potential discrimination and resentment against faculty hiring quotas, general category students perform slightly better in classrooms taught by reservation category faculty than general category faculty. The findings have implications for the heated debates over affirmative action programs found in many countries around the world and in India.
Despite rising college enrollment among women, gender disparities persist in STEM fields. We leverage a large-scale setting in which STEM undergraduates are randomly assigned to instructors---a feature rarely feasible in higher education---to provide causal evidence on the effects of exposure to female faculty. Female students assigned to female faculty perform better on externally graded course exams and score higher on standardized tests administered two years later, indicating effects of female faculty that persist beyond the immediate classroom context. Gains are largest among female students who report higher uncertainty about belonging in STEM. Female students also report lower anxiety about mathematics and science. We show that these effects are unlikely to be driven by differences in teaching or grading practices, and are instead consistent with exposure to identity-relevant cues that reduce female students’ anxiety about STEM. Exposure to female faculty also shifts beliefs away from stereotypes about women’s ability in mathematics and science, especially among male students. These findings suggest that repeated exposure to female faculty improves performance among female students and fosters more inclusive beliefs about women in STEM fields.
(Under review. Draft Available Upon Request)
We study whether local schooling markets in India exhibit tipping-point dynamics in student caste composition. Using near-universal administrative panel data on schools, we define villages as local schooling markets and estimate village-level composition thresholds from the relationship between baseline caste shares and subsequent enrollment flows, adapting the Card et al. (2008) fixed-point procedure to multi-school markets. We study two caste contrasts: upper-caste versus all disadvantaged groups combined, and intermediate-caste versus the most marginalized. Estimated thresholds differ sharply across contrasts and concentrate at very different baseline shares, indicating that tipping is boundary-specific rather than a generic feature of composition change. Around these thresholds, within-village school segregation rises discontinuously by 12% for the upper-caste comparison and 42% for the within-disadvantaged caste comparison. These are driven by resorting across schools within the local market rather than shifts in village composition. School inputs and public grant flows exhibit parallel discrete changes at the same thresholds, with per-student grants jumping by about 30%. Threshold locations are lower where caste identity is more salient and higher where schooling markets are thicker, though both gradients largely reflect state-level heterogeneity. Together, these findings show that institutional responses to composition amplify household sorting, generating a supply-side response that affects school quality.