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netivreg: Estimation of peer effects in endogenous social networks

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  • Juan Estrada

    (Emory University)

Abstract

I present the netivreg command, which implements the generalized three-stage least-squares (G3SLS) estimator for the endogenous linear-in-means model developed in Estrada et al. (2020, “On the Identification and Estimation of Endogenous Peer Effects in Multiplex Networks"). The G3SLS procedure utilizes full observability of a two-layered multiplex network data structure using Stata 16's new multiframes capabilities and Python integration. Implementations of the command utilizing simulated data as well as three years' worth of data on peer-reviewed articles published in top general-interest journals in economics in Estrada et al. (2020) are also included.

Suggested Citation

  • Juan Estrada, 2021. "netivreg: Estimation of peer effects in endogenous social networks," 2021 Stata Conference 16, Stata Users Group.
    • Handle: RePEc:boc:scon21:16
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