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Social Interaction Methods

Author

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  • Patacchini, Eleonora
  • Hsieh, Chih-Sheng
  • Lin, Xu

Abstract

This paper is concerned with methods for analyzing social interaction effects. The attention is focused on how to estimate endogenous effects, where an individual's choice may depend on those of his/her contacts about the same activity. The analysis is guided by the data structure that is available to measure social interactions, an intuitive aspect that allows empirical researchers to understand whether and how they could study social interaction effects in their own data. First, the case where the information on social interaction patterns is limited to membership to a given group is considered, then the discussion moves to the case where the data contain information on specific relationships among pairs of individuals within each group, and the availability of data on the co-evolution of social structures and outcomes. This paper also discusses some basic methods to deal with online social network data, and the novel literature estimating social interaction effects relying only on outcome data. For each data structure, the challenges and the main methods proposed in the literature to tackle them are reviewed.

Suggested Citation

  • Patacchini, Eleonora & Hsieh, Chih-Sheng & Lin, Xu, 2019. "Social Interaction Methods," CEPR Discussion Papers 14141, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:14141
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    Cited by:

    1. Lawrence E. Blume & William A. Brock & Steven N. Durlauf & Rajshri Jayaraman, 2015. "Linear Social Interactions Models," Journal of Political Economy, University of Chicago Press, vol. 123(2), pages 444-496.
    2. Kim, Min Jae & Kim, Tong Seop & Flores, Robert J. & Brouwer, Jack, 2020. "Neural-network-based optimization for economic dispatch of combined heat and power systems," Applied Energy, Elsevier, vol. 265(C).
    3. Steve Berry & Ahmed Khwaja & Vineet Kumar & Andres Musalem & Kenneth Wilbur & Greg Allenby & Bharat Anand & Pradeep Chintagunta & W. Hanemann & Przemek Jeziorski & Angelo Mele, 2014. "Structural models of complementary choices," Marketing Letters, Springer, vol. 25(3), pages 245-256, September.
    4. Hsieh, Chih-Sheng & Lin, Xu, 2017. "Gender and racial peer effects with endogenous network formation," Regional Science and Urban Economics, Elsevier, vol. 67(C), pages 135-147.

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