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netivreg: Estimation of peer effects in endogenous social networks

Author

Listed:
  • Pablo Estrada

    (Emory University)

  • Juan Estrada

    (Analysis Group Economic Consulting)

  • Kim P. Huynh

    (Bank of Canada)

  • David Jacho-Chávez

    (Emory University)

  • Leonardo Sánchez-Aragón

    (ESPOL University)

Abstract

The command netivreg implements the generalized three-stage least- squares estimator developed in Estrada (2022, Causal inference in multilayered networks, PhD thesis) and the generalized method of moments estimator in Chan et al. (2024, Journal of Econometric Methods 13: 205–224) for the endogenous linear-in-means model. The two procedures use full observability of a two-layered multiplex network data structure using Stata’s new multiframes capabilities and Python integration (version 16 and above). Applications of the command include simulated data and three years’ worth of data on peer-reviewed articles published in top general-interest journals in economics.

Suggested Citation

  • Pablo Estrada & Juan Estrada & Kim P. Huynh & David Jacho-Chávez & Leonardo Sánchez-Aragón, 2025. "netivreg: Estimation of peer effects in endogenous social networks," Stata Journal, StataCorp LLC, vol. 25(2), pages 344-373, June.
    • Handle: RePEc:tsj:stataj:v:25:y:2025:i:2:p:344-373
    DOI: 10.1177/1536867X251341145
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