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On the Directionality Test of Peer Effects in Social Networks

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  • Weihua An

Abstract

One interesting idea in social network analysis is the directionality test that utilizes the directions of social ties to help identify peer effects. The null hypothesis of the test is that if contextual factors are the only force that affects peer outcomes, the estimated peer effects should not differ, if the directions of social ties are reversed. In this article, I statistically formalize this test and investigate its properties under various scenarios. In particular, I point out the validity of the test is contingent on the presence of peer selection, sampling error, and simultaneity bias. I also outline several methods that can help provide causal estimates of peer effects in social networks.

Suggested Citation

  • Weihua An, 2016. "On the Directionality Test of Peer Effects in Social Networks," Sociological Methods & Research, , vol. 45(4), pages 635-650, November.
  • Handle: RePEc:sae:somere:v:45:y:2016:i:4:p:635-650
    DOI: 10.1177/0049124115582271
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    References listed on IDEAS

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    1. Andreas Ammermueller & Jörn-Steffen Pischke, 2009. "Peer Effects in European Primary Schools: Evidence from the Progress in International Reading Literacy Study," Journal of Labor Economics, University of Chicago Press, vol. 27(3), pages 315-348, July.
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    3. Fowler, J.H. & Christakis, N.A., 2008. "Estimating peer effects on health in social networks: A response to Cohen-Cole and Fletcher; and Trogdon, Nonnemaker, and Pais," Journal of Health Economics, Elsevier, vol. 27(5), pages 1400-1405, September.
    4. Lyons Russell, 2011. "The Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis," Statistics, Politics and Policy, De Gruyter, vol. 2(1), pages 1-29, May.
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    Cited by:

    1. Jonathan Pratschke & Giovanni Abbiati, 2023. "“Like with like” or “do like?” Modeling peer effects in the classroom," Social Science Quarterly, Southwestern Social Science Association, vol. 104(3), pages 265-280, May.

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