Segregation in social networks

Abstract

I develop a dynamic heterogeneous agents model of strategic network formation, where a matching technology and preferences for same-type individuals drive the dynamics of friendship. The model converges to a unique stationary distribution that is structurally estimated using Markov Chain Monte Carlo methods and stochastic approximation techniques. I use data from the restricted version of Add Health, a representative survey of US high schools containing detailed data on the actual friendship network of each student. Results show that the tendency to create links to individuals of the same racial group is pervasive. However, I find that a certain degree of heterogeneity in mutual and indirect friends increases utility of the agents. I use the model to simulate policies whose goal is to increase the degree of interracial contact. I re-assign some minority students to another school where there are only few minority students. The simulations show that these policies decrease students' welfare in the new stationary equilibrium.