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Peer Effects Heterogeneity and Social Networks in Education

Author

Listed:
  • Livia Shkoza

    (University of Konstanz, GSDS)

  • Derya Uysal

    (University of Munich, CESifo)

  • Winfried Pohlmeier

    (University of Konstanz, CASCB, ICEA)

Abstract

This study focuses on the role of heterogeneity in network peer effects by accounting for network-specific factors and different driving mechanisms of peer behavior. We propose a novel Multivariate Instrumental Variable (MVIV) estimator which is consistent for a large number of networks keeping the individual network size bounded. We apply this approach to estimate peer effects on school achievement exploiting the network structure of friendships within classrooms. The empirical evidence presented is based on a unique network dataset from German upper secondary schools. We show that accounting for heterogeneity is not only crucial from a statistical perspective, but also yields new structural insights into how class size and gender composition affect school achievement through peer behavior.

Suggested Citation

  • Livia Shkoza & Derya Uysal & Winfried Pohlmeier, 2023. "Peer Effects Heterogeneity and Social Networks in Education," Rationality and Competition Discussion Paper Series 423, CRC TRR 190 Rationality and Competition.
    • Handle: RePEc:rco:dpaper:423
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    References listed on IDEAS

    as
    1. Victor Lavy & Analia Schlosser, 2011. "Mechanisms and Impacts of Gender Peer Effects at School," American Economic Journal: Applied Economics, American Economic Association, vol. 3(2), pages 1-33, April.
    2. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves, 2014. "Endogenous peer effects: local aggregate or local average?," Journal of Economic Behavior & Organization, Elsevier, vol. 103(C), pages 39-59.
    3. Simone Dobbelsteen & Jesse Levin & Hessel Oosterbeek, 2002. "The causal effect of class size on scholastic achievement: distinguishing the pure class size effect from the effect of changes in class composition," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(1), pages 17-38, February.
    4. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
    5. Kelejian, Harry H & Prucha, Ingmar R, 1999. "A Generalized Moments Estimator for the Autoregressive Parameter in a Spatial Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 40(2), pages 509-533, May.
    6. Caroline M. Hoxby, 2000. "The Effects of Class Size on Student Achievement: New Evidence from Population Variation," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 115(4), pages 1239-1285.
    7. Victor Lavy & Analia Schlosser, 2011. "Mechanisms and Impacts of Gender Peer Effects at School," American Economic Journal: Applied Economics, American Economic Association, vol. 3(2), pages 1-33, April.
    Full references (including those not matched with items on IDEAS)

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    Keywords

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    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • I21 - Health, Education, and Welfare - - Education - - - Analysis of Education
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C36 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Instrumental Variables (IV) Estimation

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