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Structural Homophily

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  • Vincent Boucher

    (CIREQ - Centre interuniversitaire de recherche en économie quantitative)

Abstract

Homophily, or the fact that similar individuals tend to interact with each other, is a prominent feature of economic and social networks. Most existing theories of homophily are based on a descriptive approach and abstract away from equilibrium considerations. I show that the equilibrium structure of homophily has empirical power, as it can be used to recover underlying preference parameters. I build a non-cooperative model of network formation, which produces a unique, empirically realistic equilibrium network. Individuals have homophilic preferences and face capacity constraints on the number of links. I develop a novel empirical method, based on the shape of the equilibrium network, which allows for the identification and estimation of the underlying homophilic preferences. I apply this new methodology to race-based choices regarding friendship decisions among American teenagers.

Suggested Citation

  • Vincent Boucher, 2012. "Structural Homophily," Working Papers hal-00720825, HAL.
    • Handle: RePEc:hal:wpaper:hal-00720825
    Note: View the original document on HAL open archive server: https://hal.science/hal-00720825
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    References listed on IDEAS

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    Cited by:

    1. Simon Clark, 2020. ""You're Just My Type!" Matching and Payoffs When Like Attracts Like," Edinburgh School of Economics Discussion Paper Series 295, Edinburgh School of Economics, University of Edinburgh.
    2. Schulz, Jan & Mayerhoffer, Daniel M., 2021. "A network approach to consumption," BERG Working Paper Series 173, Bamberg University, Bamberg Economic Research Group.
    3. 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.
    4. Jiménez-Martínez, Antonio & Melguizo-López, Isabel, 2022. "Making friends: The role of assortative interests and capacity constraints," Journal of Economic Behavior & Organization, Elsevier, vol. 203(C), pages 431-465.
    5. Boucher, Vincent & Fortin, Bernard, 2015. "Some Challenges in the Empirics of the Effects of Networks," IZA Discussion Papers 8896, Institute of Labor Economics (IZA).
    6. Zenou, Yves & Boucher, Vincent & Tumen, Semih & Vlassopoulos, Michael & Wahba, Jackline, 2020. "Ethnic Mixing in Early Childhood: Evidence from a Randomized Field Experiment and a Structural Model," CEPR Discussion Papers 15528, C.E.P.R. Discussion Papers.
    7. Alan Griffith, 2022. "A continuous model of strong and weak ties," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 24(6), pages 1519-1563, December.
    8. Saeed Badri & Bernd Heidergott & Ines Lindner, 2022. "Na?ve Learning in Social Networks with Fake News: Bots as a Singularity," Tinbergen Institute Discussion Papers 22-097/II, Tinbergen Institute.
    9. Norma Olaizola & Federico Valenciano, 2023. "A connections model with decreasing returns link-formation technology," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 14(1), pages 31-61, March.
    10. Michael Foley & Rory Smead & Patrick Forber & Christoph Riedl, 2021. "Avoiding the bullies: The resilience of cooperation among unequals," PLOS Computational Biology, Public Library of Science, vol. 17(4), pages 1-18, April.
    11. Bolletta, Ugo, 2021. "A model of peer effects in school," Mathematical Social Sciences, Elsevier, vol. 114(C), pages 1-10.

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