GMM Identication and Estimation of Peer E¤ects in a System of Simultaneous Equations
نویسنده
چکیده
This paper considers the identi cation and estimation of network models with agents interacting in multiple activities. We establish the model identi cation using both linear and quadratic moment conditions. The quadratic moment conditions exploit the covariance structure of individualschoices in the same and related activities, and facilitate the identi cation of peer e¤ects when exclusion restrictions based on intransitivity of network connections or variation in network sizes are not available. Combining linear and quadratic moment conditions, we propose a general GMM framework for the estimation of simultaneous equations network models. The GMM estimator improves the estimation e¢ ciency of the existing IV-based linear estimators in the literature. Simulation experiments show that the GMM estimator performs well in nite samples. JEL classi cation: C31, C36
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