  This paper studies social interactions in a game theoretic model with players
in a large social network. We consider observations from one single equilibrium
of a large network game with asymmetric information, in which each player
chooses an action from a finite set and is subject to interactions with her
friends. Simple assumptions about the structure are made to establish the
existence and uniqueness of equilibrium. In particular, we show that the
equilibrium strategies satisfy a network decaying dependence (NDD) condition
requiring that dependence between any two players' decisions decays with their
network distance. The formulation of such an NDD property is novel and serves
as the basis for statistical inference. Further, we establish the
identification of the structural model and introduce a computationally feasible
and efficient estimation method. We illustrate the estimation method with an
actual application to college attendance, as well as in Monte Carlo
experiments.
