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Abstract This article studies estimation of social interactions in a large network game, where all observations come from one single equilibrium of a network game with asymmetric information. Simple assumptions about the structure are made to establish the existence and uniqueness of the equilibrium. I show that the equilibrium strategies satisfy a network decaying dependence condition requiring that dependence between two players' decisions decay with their network distance, which serves as the basis for my statistical inference. Moreover, I establish identification and propose a computationally feasible and efficient estimation method, which is illustrated by an empirical application of college attendance.
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