ESTIMATION OF PEER EFFECTS IN ENDOGENOUS SOCIAL NETWORKS: CONTROL FUNCTION APPROACH

We propose methods of estimating the linear-in-means model of peer effects in which the peer group, defined by a social network, is endogenous in the outcome equation for peer effects. Endogeneity is due to unobservable individual characteristics that influence both link formation in the network and the outcome of interest. We propose two estimators of the peer effect equation that control for the endogeneity of the social connections using a control function approach. We leave the functional form of the control function unspecified, estimate the model using a sieve semiparametric approach and establish asymptotics of the semiparametric estimator.

Automated summary

This paper proposes two methods to estimate the linear-in-means model of peer effects, controlling for the endogeneity of social connections using a control function approach. The authors leave the functional form of the control function unspecified and establish asymptotics of the semiparametric estimator.