A Structural Model of Segregation in Social Networks

65 Pages Posted: 19 Jul 2013

See all articles by Angelo Mele

Angelo Mele

Johns Hopkins University - Carey Business School

Multiple version iconThere are 2 versions of this paper

Date Written: July 16, 2013


The main challenges in estimating strategic network formation models are the presence of multiple equilibria, and the fact that the number of possible network configurations increases exponentially with the number of players. I propose a dynamic model of strategic network formation with heterogeneous players, which converges to a unique stationary equilibrium. Hence, the structural preference parameters can be estimated using a single network observation. In addition, the model provides the first equilibrium micro-foundation of exponential random graphs. Because of the curse of dimensionality, the likelihood is computationally intractable. Therefore, I propose a Bayesian estimation strategy that samples from the posterior, interleaving parameter and network simulations, without evaluating the likelihood. I prove that the proposed algorithm converges to the correct posterior distribution. A mean-field analysis shows that the algorithm converges fast for practical applications. Estimation is tested with artificial and Add Health data, confirming evidence of homophily in high schools.

Keywords: Social Networks, Bayesian Estimation, Markov Chain Monte Carlo

JEL Classification: D85, C15, C73

Suggested Citation

Mele, Angelo, A Structural Model of Segregation in Social Networks (July 16, 2013). Available at SSRN: https://ssrn.com/abstract=2294957 or http://dx.doi.org/10.2139/ssrn.2294957

Angelo Mele (Contact Author)

Johns Hopkins University - Carey Business School ( email )

100 International Drive
Baltimore, MD 21202
United States

HOME PAGE: http://www.meleangelo.com

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