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Homophily in preferences or meetings? Identifying and estimating an iterative network formation model

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  • Luis Alvarez
  • Cristine Pinto
  • Vladimir Ponczek

Abstract

Is homophily in social and economic networks driven by a taste for homogeneity (preferences) or by a higher probability of meeting individuals with similar attributes (opportunity)? This paper studies identification and estimation of an iterative network game that distinguishes between these two mechanisms. Our approach enables us to assess the counterfactual effects of changing the meeting protocol between agents. As an application, we study the role of preferences and meetings in shaping classroom friendship networks in Brazil. In a network structure in which homophily due to preferences is stronger than homophily due to meeting opportunities, tracking students may improve welfare. Still, the relative benefit of this policy diminishes over the school year.

Suggested Citation

  • Luis Alvarez & Cristine Pinto & Vladimir Ponczek, 2022. "Homophily in preferences or meetings? Identifying and estimating an iterative network formation model," Papers 2201.06694, arXiv.org, revised Mar 2024.
    • Handle: RePEc:arx:papers:2201.06694
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    References listed on IDEAS

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    1. Shuyang Sheng, 2020. "A Structural Econometric Analysis of Network Formation Games Through Subnetworks," Econometrica, Econometric Society, vol. 88(5), pages 1829-1858, September.
    2. Bramoullé, Yann & Currarini, Sergio & Jackson, Matthew O. & Pin, Paolo & Rogers, Brian W., 2012. "Homophily and long-run integration in social networks," Journal of Economic Theory, Elsevier, vol. 147(5), pages 1754-1786.
    3. Whitney K. Newey & Richard J. Smith, 2004. "Higher Order Properties of Gmm and Generalized Empirical Likelihood Estimators," Econometrica, Econometric Society, vol. 72(1), pages 219-255, January.
    4. Aguirregabiria, Victor & Mira, Pedro, 2010. "Dynamic discrete choice structural models: A survey," Journal of Econometrics, Elsevier, vol. 156(1), pages 38-67, May.
    5. Simon Barthelmé & Nicolas Chopin, 2014. "Expectation Propagation for Likelihood-Free Inference," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(505), pages 315-333, March.
    6. Angelo Mele, 2017. "A Structural Model of Dense Network Formation," Econometrica, Econometric Society, vol. 85, pages 825-850, May.
    7. à ureo de Paula & Seth Richards†Shubik & Elie Tamer, 2018. "Identifying Preferences in Networks With Bounded Degree," Econometrica, Econometric Society, vol. 86(1), pages 263-288, January.
    8. Paul Goldsmith-Pinkham & Guido W. Imbens, 2013. "Social Networks and the Identification of Peer Effects," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(3), pages 253-264, July.
    9. Patrick Bajari & Han Hong & Stephen P. Ryan, 2010. "Identification and Estimation of a Discrete Game of Complete Information," Econometrica, Econometric Society, vol. 78(5), pages 1529-1568, September.
    10. Sergio Currarini & Matthew O. Jackson & Paolo Pin, 2009. "An Economic Model of Friendship: Homophily, Minorities, and Segregation," Econometrica, Econometric Society, vol. 77(4), pages 1003-1045, July.
    11. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    12. Qi Li & Jeffrey Scott Racine, 2006. "Nonparametric Econometrics: Theory and Practice," Economics Books, Princeton University Press, edition 1, volume 1, number 8355.
    13. Qi Li & Jeffrey Scott Racine, 2006. "Density Estimation, from Nonparametric Econometrics: Theory and Practice," Introductory Chapters, in: Nonparametric Econometrics: Theory and Practice, Princeton University Press.
    14. Bryan S. Graham, 2017. "An Econometric Model of Network Formation With Degree Heterogeneity," Econometrica, Econometric Society, vol. 85, pages 1033-1063, July.
    15. Jackson, Matthew O. & Watts, Alison, 2002. "The Evolution of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 106(2), pages 265-295, October.
    16. D T Frazier & G M Martin & C P Robert & J Rousseau, 2018. "Asymptotic properties of approximate Bayesian computation," Biometrika, Biometrika Trust, vol. 105(3), pages 593-607.
    17. Wentao Li & Paul Fearnhead, 2018. "On the asymptotic efficiency of approximate Bayesian computation estimators," Biometrika, Biometrika Trust, vol. 105(2), pages 285-299.
    18. Blum, Michael G. B., 2010. "Approximate Bayesian Computation: A Nonparametric Perspective," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1178-1187.
    19. Bryan S. Graham, 2016. "Homophily and Transitivity in Dynamic Network Formation," NBER Working Papers 22186, National Bureau of Economic Research, Inc.
    20. Chih‐Sheng Hsieh & Lung Fei Lee, 2016. "A Social Interactions Model with Endogenous Friendship Formation and Selectivity," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(2), pages 301-319, March.
    21. Elie Tamer, 2003. "Incomplete Simultaneous Discrete Response Model with Multiple Equilibria," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(1), pages 147-165.
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