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Linear Social Interactions Models

Author

Listed:
  • Blume, Lawrence E.

    (Department of Economics, Cornell University, Ithaca, USA, and Santa Fe Institute and IHS Vienna)

  • Brock, William A.

    (Economics Department, University of Wisconsin-Madison, USA and University of Missouri, Columbia)

  • Durlauf, Steven N.

    (Department of Economics, University of Wisconsin-Madison, USA)

  • Jayaraman, Rajshri

    (European School of Management and Technology, Berlin, Germany)

Abstract

This paper provides a systematic analysis of identification in linear social interactions models. This is both a theoretical and an econometric exercise as the analysis is linked to a rigorously delineated model of interdependent decisions. We develop an incomplete information game that describes individual choices in the presence of social interactions. The equilibrium strategy profiles are linear. Standard models in the empirical social interactions literature are shown to be exact or approximate special cases of our general framework, which in turn provides a basis for understanding the microeconomic foundations of those models. We consider identification of both endogenous (peer) and contextual social effects under alternative assumptions on a priori information about network structure available to an analyst, and contrast the informational content of individual-level and aggregated data. Finally, we discuss potential ramifications for identification of endogenous group selection and differences between the information sets of analysts and agents.

Suggested Citation

  • Blume, Lawrence E. & Brock, William A. & Durlauf, Steven N. & Jayaraman, Rajshri, 2013. "Linear Social Interactions Models," Economics Series 298, Institute for Advanced Studies.
  • Handle: RePEc:ihs:ihsesp:298
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    File URL: http://www.ihs.ac.at/publications/eco/es-298.pdf
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Fortin, Bernard & Yazbeck, Myra, 2015. "Peer effects, fast food consumption and adolescent weight gain," Journal of Health Economics, Elsevier, vol. 42(C), pages 125-138.
    2. Julie Beugnot & Bernard Fortin & Guy Lacroix & Marie Claire Villeval, 2017. "Gender and Peer Effects on Performance in Social Networks," Working Papers halshs-00855047, HAL.
    3. Firmin Doko Tchatoka & Robert Garrard & Virginie Masson, 2017. "Testing for Stochastic Dominance in Social Networks," School of Economics Working Papers 2017-02, University of Adelaide, School of Economics.
    4. Rokhaya Dieye & Bernard Fortin, 2017. "Gender Peer Effects Heterogeneity in Obesity," Cahiers de recherche 1702, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    5. Beugnot, Julie & Fortin, Bernard & Lacroix, Guy & Villeval, Marie Claire, 2017. "Gender and Peer Effects in Social Networks," IZA Discussion Papers 10588, Institute for the Study of Labor (IZA).
    6. George Judge, 2016. "Econometric Information Recovery in Behavioral Networks," Econometrics, MDPI, Open Access Journal, vol. 4(3), pages 1-11, September.
    7. Battaglini, Marco & Patacchini, Eleonora, 2016. "Influencing Connected Legislators," CEPR Discussion Papers 11571, C.E.P.R. Discussion Papers.
    8. De Paula, Áureo & Rasul, Imran & Souza, Pedro, 2018. "Recovering Social Networks from Panel Data: Identification, Simulations and an Application," CEPR Discussion Papers 12792, C.E.P.R. Discussion Papers.
    9. Arun Advani & Bansi Malde, 2014. "Empirical methods for networks data: social effects, network formation and measurement error," IFS Working Papers W14/34, Institute for Fiscal Studies.
    10. Boucher, Vincent, 2016. "Conformism and self-selection in social networks," Journal of Public Economics, Elsevier, vol. 136(C), pages 30-44.
    11. de Martí, Joan & Zenou, Yves, 2015. "Network games with incomplete information," Journal of Mathematical Economics, Elsevier, vol. 61(C), pages 221-240.
    12. Yang, Chao & Lee, Lung-fei, 2017. "Social interactions under incomplete information with heterogeneous expectations," Journal of Econometrics, Elsevier, vol. 198(1), pages 65-83.
    13. Boucher, Vincent & Fortin, Bernard, 2015. "Some Challenges in the Empirics of the Effects of Networks," IZA Discussion Papers 8896, Institute for the Study of Labor (IZA).
    14. Ui, Takashi, 2016. "Bayesian Nash equilibrium and variational inequalities," Journal of Mathematical Economics, Elsevier, vol. 63(C), pages 139-146.
    15. repec:spr:sjecst:v:154:y:2018:i:1:d:10.1186_s41937-017-0011-x is not listed on IDEAS
    16. UI, Takashi, 2015. "Bayesian Nash Equilibrium and Variational Inequalities," Discussion Papers 2015-08, Graduate School of Economics, Hitotsubashi University.
    17. repec:eee:jcecon:v:45:y:2017:i:2:p:271-286 is not listed on IDEAS
    18. Ida Johnsson & Hyungsik Roger Moon, 2017. "Estimation of Peer Effects in Endogenous Social Networks: Control Function Approach," Papers 1709.10024, arXiv.org.

    More about this item

    Keywords

    Social interactions; identification; incomplete information games;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • Z13 - Other Special Topics - - Cultural Economics - - - Economic Sociology; Economic Anthropology; Language; Social and Economic Stratification

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