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Social Networks with Unobserved Links

Author

Listed:
  • Arthur Lewbel

    (Boston College)

  • Xi Qu

    (Shanghai Jiao Tong University)

  • Xun Tang

    (Rice University)

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 that are each only observed once. We apply our estimator to data from Tennessee's Student/Teacher Achievement Ratio (STAR) Project. 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.

Suggested Citation

  • Arthur Lewbel & Xi Qu & Xun Tang, 2019. "Social Networks with Unobserved Links," Boston College Working Papers in Economics 1004, Boston College Department of Economics, revised 01 Feb 2021.
  • Handle: RePEc:boc:bocoec:1004
    Note: previously circulated as "Social Networks with Misclassified or Unobserved Links"
    as

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    File URL: http://fmwww.bc.edu/EC-P/wp1004.pdf
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    References listed on IDEAS

    as
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    Cited by:

    1. Federico Martellosio, 2020. "Non-Identifiability in Network Autoregressions," Papers 2011.11084, arXiv.org.

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    More about this item

    Keywords

    Social networks; Peer effects; Unobserved network; Classroom performance;
    All these keywords.

    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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