Replication data for: Identification of Social Interactions through Partially Overlapping Peer Groups

In this paper, we demonstrate that, in a context where peer groups do not overlap fully, it is possible to identify all the relevant parameters of the standard linear-in-means model of social interactions. We apply this novel identification structure to study peer effects in the choice of college major. Results show that one is more likely to choose a major when many of her peers make the same choice. We also show that peers can divert students from majors in which they have a relative ability advantage, with adverse consequences on academic performance, entry wages, and job satisfaction. (JEL I23, J24, J31, Z13)