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Parametric and Semiparametric IV Estimation of Network Models with Selectivity

Author

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  • Tiziano Arduini

    (Sapienza University of Rome)

  • Eleonora Patacchini

    (Cornell University, Sapienza University of Rome, EIEF, IZA and CEPR)

  • Edoardo Rainone

    (Bank of Italy)

Abstract

We propose parametric and semiparametric IV estimators for spatial autoregressive models with network data where the network structure is endogenous. We embed a dyadic network formation process in the control function approach as in Heckman and Robb (1985). In the semiparametric case, we use power series to approximate the correction terms. We establish the consistency and asymptotic normality for both parametric and semiparametric cases. We also investigate their finite sample properties via Monte Carlo simulation.

Suggested Citation

  • Tiziano Arduini & Eleonora Patacchini & Edoardo Rainone, 2015. "Parametric and Semiparametric IV Estimation of Network Models with Selectivity," EIEF Working Papers Series 1509, Einaudi Institute for Economics and Finance (EIEF), revised Oct 2015.
    • Handle: RePEc:eie:wpaper:1509
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    2. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 603-629, August.
    3. Jochmans, Koen, 2023. "Peer effects and endogenous social interactions," Journal of Econometrics, Elsevier, vol. 235(2), pages 1203-1214.
    4. Guido M. Kuersteiner & Ingmar R. Prucha, 2020. "Dynamic Spatial Panel Models: Networks, Common Shocks, and Sequential Exogeneity," Econometrica, Econometric Society, vol. 88(5), pages 2109-2146, September.
    5. Brice Romuald Gueyap Kounga, 2023. "Identification and Estimation of a Semiparametric Logit Model using Network Data," Papers 2310.07151, arXiv.org, revised Jun 2024.
    6. 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.
    7. Eric Auerbach, 2021. "Identification and Estimation of a Partially Linear Regression Model using Network Data: Inference and an Application to Network Peer Effects," Papers 2105.10002, arXiv.org.
    8. Ida Johnsson & Hyungsik Roger Moon, 2017. "Estimation of Peer Effects in Endogenous Social Networks: Control Function Approach," Papers 1709.10024, arXiv.org, revised Jul 2019.
    9. Arun Advani & Bansi Malde, 2018. "Credibly Identifying Social Effects: Accounting For Network Formation And Measurement Error," Journal of Economic Surveys, Wiley Blackwell, vol. 32(4), pages 1016-1044, September.
    10. Wayne Yuan Gao, 2017. "Nonparametric Identification in Index Models of Link Formation," Papers 1710.11230, arXiv.org, revised May 2018.
    11. Arun Advani & Bansi Malde, 2018. "Methods to identify linear network models: a review," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-16, December.
    12. 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.
    13. Rainone, Edoardo, 2020. "The network nature of over-the-counter interest rates," Journal of Financial Markets, Elsevier, vol. 47(C).
    14. Diemer, Andreas, 2022. "Endogenous peer effects in diverse friendship networks: Evidence from Swedish classrooms," Economics of Education Review, Elsevier, vol. 89(C).
    15. Gao, Wayne Yuan, 2020. "Nonparametric identification in index models of link formation," Journal of Econometrics, Elsevier, vol. 215(2), pages 399-413.
    16. Eric Auerbach, 2019. "Identification and Estimation of a Partially Linear Regression Model using Network Data," Papers 1903.09679, arXiv.org, revised Jun 2021.

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