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 which is now the largest country in the world.
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 academically and report lower STEM-related anxiety, with the largest gains among those with lower prior achievement, confidence, or belonging. Exposure to female faculty also shifts beliefs away from stereotypes about women’s ability in STEM, especially among men. These effects are not explained by differences in teaching practices or grading but are consistent with the influence of female role models in reducing psychological barriers. Our findings show that exposure to female faculty improves outcomes for women and promotes more inclusive norms in STEM fields.
I investigate whether returns to different levels of cognitive skills systematically vary for locations where the Indian Information-Technology (IT) Services Industry is intensely concentrated. Using data from Census of India (2001 and 2011), I classify Indian districts into ‘IT-Clusters’ and ‘non-clusters.’ Furthermore, I use a triple-differences framework with wage data from India’s National Sample Survey’s Employment and Unemployment Data. I find evidence that the skill premium in wages (i.e, the difference in wages between high-skilled and low-skilled workers) is higher in IT-clusters relative to non-clusters. Furthermore, there is mixed evidence to suggest the possibility of positive spillovers in wages for low-skilled workers associated with being located in IT-Clusters. There is no evidence to suggest that the difference in skill premium between IT-Clusters and non-clusters is increasing between 2004-05 and 2011-122