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Estimation of social‐influence‐dependent peer pressure in a large network game

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  • Zhongjian Lin
  • Haiqing Xu

Abstract

Research on peer effects in sociology has long been focused on social interactions and the associated social influence process. In this paper, we extend a large‐network‐based game model to a model that allows for the dependence of social interactions on social‐influence status. In particular, we use the Katz–Bonacich centrality to measure individuals' social influences, which are obtained directly from the observation of a social network. To solve the computational burden when the data come from the equilibrium of a large network, we extend a nested pseudo‐likelihood estimation approach to our large‐network‐based game model. Using the National Longitudinal Study of Adolescent Health (Add Health) dataset, we investigate the peer effects of dangerous behaviour among high‐school students. Our results show that the peer effects are statistically significant and positive. Moreover, students benefit more (statistically significant at the 5% level) from conformity or, equivalently, pay more for disobedience, in terms of peer pressure, if their friends have a higher status of social influence.

Suggested Citation

  • Zhongjian Lin & Haiqing Xu, 2017. "Estimation of social‐influence‐dependent peer pressure in a large network game," Econometrics Journal, Royal Economic Society, vol. 20(3), pages 86-102, October.
  • Handle: RePEc:wly:emjrnl:v:20:y:2017:i:3:p:s86-s102
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    File URL: http://hdl.handle.net/10.1111/ectj.12102
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    Cited by:

    1. Yingyao Hu & Zhongjian Lin, 2018. "Misclassification and the hidden silent rivalry," CeMMAP working papers CWP12/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    2. Victor Aguirregabiria & Mathieu Marcoux, 2019. "Imposing equilibrium restrictions in the estimation of dynamic discrete games," Working Papers tecipa-646, University of Toronto, Department of Economics.
    3. Chomsisengphet, Souphala & Kiefer, Hua & Liu, Xiaodong, 2018. "Spillover effects in home mortgage defaults: Identifying the power neighbor," Regional Science and Urban Economics, Elsevier, vol. 73(C), pages 68-82.

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