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My Friend Far, Far Away: A Random Field Approach to Exponential Random Graph Models

51 Pages Posted: 4 Nov 2012 Last revised: 24 Apr 2017

Vincent Boucher

Laval University

Ismael Mourifie

University of Toronto - Department of Economics

Date Written: April 2017

Abstract

We explore the asymptotic properties of strategic models of network formation in very large populations. Specifically, we focus on (undirected) exponential random graph models (ERGMs). We want to recover a set of parameters from the individuals' utility functions using the observation of a single, but large, social network. We show that under some conditions, a simple logit estimator is coherent, consistent and asymptotically normally distributed under a weak version of homophily. The approach is compelling as the computing time is minimal and the estimator can be easily implemented using pre-programmed estimators available in most statistical packages. We provide an application of our method using the Add Health database.

Keywords: social network, pairwise stability, spatial econometrics

JEL Classification: C13, D85

Suggested Citation

Boucher, Vincent and Mourifie, Ismael, My Friend Far, Far Away: A Random Field Approach to Exponential Random Graph Models (April 2017). Available at SSRN: https://ssrn.com/abstract=2170803 or http://dx.doi.org/10.2139/ssrn.2170803

Vincent Boucher (Contact Author)

Laval University ( email )

2214 Pavillon J-A. DeSeve
Quebec, Quebec G1K 7P4
Canada

Ismael Mourifie

University of Toronto - Department of Economics ( email )

150 St. George Street
Toronto, Ontario M5S3G7
Canada

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