  This paper studies the identification and estimation of a semiparametric
binary network model in which the unobserved social characteristic is
endogenous, that is, the unobserved individual characteristic influences both
the binary outcome of interest and how links are formed within the network. The
exact functional form of the latent social characteristic is not known. The
proposed estimators are obtained based on matching pairs of agents whose
network formation distributions are the same. The consistency and the
asymptotic distribution of the estimators are proposed. The finite sample
properties of the proposed estimators in a Monte-Carlo simulation are assessed.
We conclude this study with an empirical application.
