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Homophily and transitivity in dynamic network formation

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  • Bryan S. Graham

Abstract

In social and economic networks linked agents often share additional links in common. There are two competing explanations for this phenomenon. First, agents may have a structural taste for transitive links – the returns to linking may be higher if two agents share links in common. Second, agents may assortatively match on unobserved attributes, a process called homophily. I study parameter identifiability in a simple model of dynamic network formation with both effects. Agents form, maintain, and sever links over time in order to maximize utility. The return to linking may be higher if agents share friends in common. A pair-specific utility component allows for arbitrary homophily on time-invariant agent attributes. I derive conditions under which it is possible to detect the presence of a taste for transitivity in the presence of assortative matching on unobservables. I leave the joint distribution of the initial network and the pair-specific utility component, a very high dimensional object, unrestricted. The analysis is of the 'fixed effects' type. The identification result is constructive, suggesting an analog estimator, whose single large network properties I characterize.

Suggested Citation

  • Bryan S. Graham, 2016. "Homophily and transitivity in dynamic network formation," CeMMAP working papers 16/16, Institute for Fiscal Studies.
  • Handle: RePEc:azt:cemmap:16/16
    DOI: 10.1920/wp.ifs.2016.1607
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    Cited by:

    1. Bryan S. Graham & Andrin Pelican, 2023. "Scenario Sampling for Large Supermodular Games," Papers 2307.11857, arXiv.org.
    2. Chernozhukov, Victor & Fernández-Val, Iván & Weidner, Martin, 2024. "Network and panel quantile effects via distribution regression," Journal of Econometrics, Elsevier, vol. 240(2).
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    4. Kevin Dano, 2023. "Transition Probabilities and Moment Restrictions in Dynamic Fixed Effects Logit Models," Papers 2303.00083, arXiv.org, revised Dec 2023.
    5. Braun, Martin & Verdier, Valentin, 2023. "Estimation of spillover effects with matched data or longitudinal network data," Journal of Econometrics, Elsevier, vol. 233(2), pages 689-714.
    6. 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).
    7. Bryan S. Graham & Andrin Pelican, 2023. "Scenario sampling for large supermodular games," CeMMAP working papers 15/23, Institute for Fiscal Studies.
    8. Zuckerman, David, 2024. "Multidimensional homophily," Journal of Economic Behavior & Organization, Elsevier, vol. 218(C), pages 486-513.
    9. 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.
    10. Fan Zhou & Kunpeng Zhang & Bangying Wu & Yi Yang & Harry Jiannan Wang, 2021. "Unifying Online and Offline Preference for Social Link Prediction," INFORMS Journal on Computing, INFORMS, vol. 33(4), pages 1400-1418, October.

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