We take cohorts of entering freshmen at the United States Air Force Academy and assign half to peer groups designed to maximize the academic performance of the lowest ability students. Our assignment algorithm uses nonlinear peer effects estimates from the historical pre-treatment data, in which students were randomly assigned to peer groups. We find a negative and significant treatment effect for the students we intended to help. We provide evidence that within our “optimally” designed peer groups, students avoided the peers with whom we intended them to interact and instead formed more homogeneous subgroups. These results illustrate how policies that manipulate peer groups for a desired social outcome can be confounded by changes in the endogenous patterns of social interactions within the group.

We estimate peer effects in college achievement using a data set in which individuals are exogenously assigned to peer groups of about 30 students with whom they are required to spend the majority of their time interacting. This feature enables us to estimate peer effects that are more comparable to changing the entire cohort of peers. Using this broad peer group, we measure academic peer effects of much larger magnitude than found in previous studies. The effects persist at a diminished rate into follow-on years, and we find evidence of nonlinearities in the magnitude of the effects across student academic ability.

In primary and secondary education, measures of teacher quality are often based on contemporaneous student performance on standardized achievement tests. In the postsecondary environment, scores on student evaluations of professors are typically used to measure teaching quality. We possess unique data that allow us to measure relative student performance in mandatory follow‐on classes. We compare metrics that capture these three different notions of instructional quality and present evidence that professors who excel at promoting contemporaneous student achievement teach in ways that improve their student evaluations but harm the follow‐on achievement of their students in more advanced classes.

Why aren't there more women in science? This paper begins to shed light on this question by exploiting data from the U.S. Air Force Academy, where students are randomly assigned to professors for a wide variety of mandatory standardized courses.We focus on the role of professor gender. Our results suggest that although professor gender has little impact on male students, it has a powerful effect on female students' performance in math and science classes, and high-performing female students' likelihood of taking future math and science courses, and graduating with a STEM degree. The estimates are largest for students whose SAT math scores are in the top 5% of the national distribution. The gender gap in course grades and STEM majors is eradicated when high-performing female students are assigned to female professors in mandatory introductory math and science coursework.