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

Author

Listed:
  • Ida Johnsson

    (University of Southern California)

  • Hyungsik Roger Moon

    (University of Southern California and Yonsei University)

Abstract

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.

Suggested Citation

  • Ida Johnsson & Hyungsik Roger Moon, 2021. "Estimation of Peer Effects in Endogenous Social Networks: Control Function Approach," The Review of Economics and Statistics, MIT Press, vol. 103(2), pages 328-345, May.
    • Handle: RePEc:tpr:restat:v:103:y:2021:i:2:p:328-345
    DOI: 10.1162/rest_a_00870
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    Citations

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    Cited by:

    1. Eric Auerbach, 2022. "Identification and Estimation of a Partially Linear Regression Model Using Network Data," Econometrica, Econometric Society, vol. 90(1), pages 347-365, January.
    2. Hahn, Jinyong & Liao, Zhipeng & Ridder, Geert & Shi, Ruoyao, 2023. "The influence function of semiparametric two-step estimators with estimated control variables," Economics Letters, Elsevier, vol. 231(C).
    3. Hoshino, Tadao & Yanagi, Takahide, 2023. "Treatment effect models with strategic interaction in treatment decisions," Journal of Econometrics, Elsevier, vol. 236(2).
    4. Gao, Wayne Yuan & Li, Ming & Xu, Sheng, 2023. "Logical differencing in dyadic network formation models with nontransferable utilities," Journal of Econometrics, Elsevier, vol. 235(1), pages 302-324.
    5. Xiaoxu Zhang & Xinyu Du, 2023. "Industry and Regional Peer Effects in Corporate Digital Transformation: The Moderating Effects of TMT Characteristics," Sustainability, MDPI, vol. 15(7), pages 1-22, March.
    6. Shuyang Sheng & Xiaoting Sun, 2023. "Social Interactions with Endogenous Group Formation," Papers 2306.01544, arXiv.org.
    7. Jochmans, Koen, 2023. "Peer effects and endogenous social interactions," Journal of Econometrics, Elsevier, vol. 235(2), pages 1203-1214.
    8. Diemer, Andreas, 2022. "Endogenous peer effects in diverse friendship networks: Evidence from Swedish classrooms," Economics of Education Review, Elsevier, vol. 89(C).
    9. Brice Romuald Gueyap Kounga, 2023. "Identification and Estimation of a Semiparametric Logit Model using Network Data," Papers 2310.07151, arXiv.org.
    10. Tadao Hoshino, 2023. "Causal Interpretation of Linear Social Interaction Models with Endogenous Networks," Papers 2308.04276, arXiv.org, revised Oct 2023.
    11. Margherita Comola & Rokhaya Dieye & Bernard Fortin, 2022. "Heterogeneous peer effects and gender-based interventions for teenage obesity," CIRANO Working Papers 2022s-25, CIRANO.
    12. Alejandro Sanchez-Becerra, 2022. "The Network Propensity Score: Spillovers, Homophily, and Selection into Treatment," Papers 2209.14391, arXiv.org.

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