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Parametric and Semiparametric IV Estimation of Network Models with Selectivity

Author

Listed:
  • 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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    References listed on IDEAS

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    1. repec:spr:sjecst:v:154:y:2018:i:1:d:10.1186_s41937-017-0011-x is not listed on IDEAS
    2. Lopera, Maria Adelaida & Marchand, Steeve, 2018. "Peer effects and risk-taking among entrepreneurs: Lab-in-the-field evidence," Journal of Economic Behavior & Organization, Elsevier, vol. 150(C), pages 182-201.
    3. Eric Auerbach, 2019. "Identification and Estimation of a Partially Linear Regression Model using Network Data," Papers 1903.09679, arXiv.org.
    4. repec:bla:jecsur:v:32:y:2018:i:4:p:1016-1044 is not listed on IDEAS
    5. Wayne Yuan Gao, 2017. "Nonparametric Identification in Index Models of Link Formation," Papers 1710.11230, arXiv.org, revised May 2018.
    6. 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.

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