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Estimation of Peer Effects in Endogenous Social Networks: Control Function Approach

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  • Ida Johnsson
  • Hyungsik Roger Moon

Abstract

We propose a method 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 and treat it as unknown. To estimate the model, we use a sieve semiparametric approach, and we establish asymptotics of the semiparametric estimator.

Suggested Citation

  • Ida Johnsson & Hyungsik Roger Moon, 2017. "Estimation of Peer Effects in Endogenous Social Networks: Control Function Approach," Papers 1709.10024, arXiv.org.
  • Handle: RePEc:arx:papers:1709.10024
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    References listed on IDEAS

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    Cited by:

    1. Wayne Yuan Gao, 2017. "Nonparametric Identification in Index Models of Link Formation," Papers 1710.11230, arXiv.org, revised May 2018.

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