IDEAS home Printed from https://ideas.repec.org/a/wly/iecrev/v59y2018i1p257-284.html
   My bibliography  Save this article

Social Interactions In Large Networks: A Game Theoretic Approach

Author

Listed:
  • Haiqing Xu

Abstract

This article studies estimation of social interactions in a large network game, where all observations come from one single equilibrium of a network game with asymmetric information. Simple assumptions about the structure are made to establish the existence and uniqueness of the equilibrium. I show that the equilibrium strategies satisfy a network decaying dependence condition requiring that dependence between two players' decisions decay with their network distance, which serves as the basis for my statistical inference. Moreover, I establish identification and propose a computationally feasible and efficient estimation method, which is illustrated by an empirical application of college attendance.

Suggested Citation

  • Haiqing Xu, 2018. "Social Interactions In Large Networks: A Game Theoretic Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(1), pages 257-284, February.
    • Handle: RePEc:wly:iecrev:v:59:y:2018:i:1:p:257-284
    DOI: 10.1111/iere.12269
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/iere.12269
    Download Restriction: no
    File URL: https://libkey.io/10.1111/iere.12269?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. González, Felipe, 2020. "Collective action in networks: Evidence from the Chilean student movement," Journal of Public Economics, Elsevier, vol. 188(C).
    2. Aristide Houndetoungan, 2024. "Count Data Models with Heterogeneous Peer Effects under Rational Expectations," Papers 2405.17290, arXiv.org.
    3. Daiqiang Zhang, 2021. "Testing Passive Versus Symmetric Beliefs In Contracting With Externalities," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 62(2), pages 723-767, May.
    4. Bora Kim, 2020. "Analysis of Randomized Experiments with Network Interference and Noncompliance," Papers 2012.13710, arXiv.org.
    5. John Higgins & Tarun Sabarwal, 2023. "Control and spread of contagion in networks with global effects," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 25(6), pages 1149-1187, December.
    6. Emerson Melo, 2022. "On the uniqueness of quantal response equilibria and its application to network games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 74(3), pages 681-725, October.
    7. Michael P. Leung, 2020. "Equilibrium computation in discrete network games," Quantitative Economics, Econometric Society, vol. 11(4), pages 1325-1347, November.
    8. Michael P. Leung, 2024. "Identifying Treatment and Spillover Effects Using Exposure Contrasts," Papers 2403.08183, arXiv.org, revised Dec 2024.
    9. Balbus, Lukasz & Dziewulski, Pawel & Reffett, Kevin & Wozny, Lukasz, 2022. "Markov distributional equilibrium dynamics in games with complementarities and no aggregate risk," Theoretical Economics, Econometric Society, vol. 17(2), May.
    10. Michael P. Leung, 2019. "Inference in Models of Discrete Choice with Social Interactions Using Network Data," Papers 1911.07106, arXiv.org.
    11. Chen, Liang & Luo, Yao, 2023. "Empirical analysis of network effects in nonlinear pricing data," International Journal of Industrial Organization, Elsevier, vol. 91(C).
    12. Andrey Leonidov, 2024. "Potts game on graphs: static equilibria," Computational Management Science, Springer, vol. 21(1), pages 1-10, June.
    13. Kojevnikov, Denis & Song, Kyungchul, 2023. "Econometric inference on a large Bayesian game with heterogeneous beliefs," Journal of Econometrics, Elsevier, vol. 237(1).
    14. Zhongjian Lin & Francis Vella, 2024. "Endogenous Treatment Models with Social Interactions: An Application to the Impact of Exercise on Self-Esteem," Papers 2408.13971, arXiv.org.
    15. John Higgins & Tarun Sabarwal, 2021. "Control and Spread of Contagion in Networks," WORKING PAPERS SERIES IN THEORETICAL AND APPLIED ECONOMICS 202111, University of Kansas, Department of Economics.
    16. Lin, Zhongjian & Tang, Xun & Yu, Ning Neil, 2021. "Uncovering heterogeneous social effects in binary choices," Journal of Econometrics, Elsevier, vol. 222(2), pages 959-973.
    17. Lin, Zhongjian & Vella, Francis, 2021. "Selection and Endogenous Treatment Models with Social Interactions: An Application to the Impact of Exercise on Self-Esteem," IZA Discussion Papers 14167, Institute of Labor Economics (IZA).
    18. Liang Chen & Yao Luo, 2023. "Empirical Analysis of Network Effects in Nonlinear Pricing Data," Working Papers tecipa-758, University of Toronto, Department of Economics.
    19. Kojevnikov, Denis & Song, Kyungchul, 2023. "Econometric inference on a large bayesian game with heterogeneous beliefs," Other publications TiSEM aca0631e-4f8a-45c7-af3a-4, Tilburg University, School of Economics and Management.
    20. Lin, Zhongjian & Hu, Yingyao, 2024. "Binary choice with misclassification and social interactions, with an application to peer effects in attitude," Journal of Econometrics, Elsevier, vol. 238(1).
    21. Leung, Michael P., 2019. "A weak law for moments of pairwise stable networks," Journal of Econometrics, Elsevier, vol. 210(2), pages 310-326.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:iecrev:v:59:y:2018:i:1:p:257-284. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/deupaus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.