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Social Networks with Unobserved Links

Author

Listed:
  • Arthur Lewbel
  • Xi Qu
  • Xun Tang

Abstract

We point-identify and estimate linear social network models without observing any network links. The required data consist of many small networks of individuals, such as classrooms or villages, with individuals who are each observed only once. We apply our estimator to data from Tennessee’s Project STAR (Student-Teacher Achievement Ratio). Without observing the latent network in each classroom, we identify and estimate peer and contextual effects on students’ performance in mathematics. We find that peer effects tend to be larger in bigger classes and that increasing peer effects would significantly improve students’ average test scores in some classes.

Suggested Citation

  • Arthur Lewbel & Xi Qu & Xun Tang, 2023. "Social Networks with Unobserved Links," Journal of Political Economy, University of Chicago Press, vol. 131(4), pages 898-946.
    • Handle: RePEc:ucp:jpolec:doi:10.1086/722090
    DOI: 10.1086/722090
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    Cited by:

    1. de Paula, Aureo & Rasul, Imran & Souza, Pedro, 2018. "Identifying Network Ties from Panel Data: Theory and an Application to Tax Competition," CEPR Discussion Papers 12792, C.E.P.R. Discussion Papers.
    2. Federico Martellosio, 2020. "Non-Identifiability in Network Autoregressions," Papers 2011.11084, arXiv.org, revised Jun 2022.
    3. Yi Cao & Tao Zhou & Jian Gao, 2024. "Heterogeneous peer effects of college roommates on academic performance," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    4. Arthur Lewbel & Xi Qu & Xun Tang, 2024. "Ignoring measurement errors in social networks," The Econometrics Journal, Royal Economic Society, vol. 27(2), pages 171-187.
    5. Promit K. Chaudhuri & Matthew O. Jackson & Sudipta Sarangi & Hector Tzavellas, 2023. "Games Under Network Uncertainty," Papers 2305.03124, arXiv.org, revised Dec 2024.

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    More about this item

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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