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The Empirical Content of Models with Multiple Equilibria in Economies with Social Interactions

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  • Alberto Bisin
  • Andrea Moro
  • Giorgio Topa

Abstract

We study a general class of models with social interactions that might display multiple equilibria. We propose an estimation procedure for these models and evaluate its efficiency and computational feasibility relative to different approaches taken to the curse of dimensionality implied by the multiplicity. Using data on smoking among teenagers, we implement the proposed estimation procedure to understand how group interactions affect health-related choices. We find that interaction effects are strong both at the school level and at the smaller friends-network level. Multiplicity of equilibria is pervasive at the estimated parameter values, and equilibrium selection accounts for about 15 percent of the observed smoking behavior. Counterfactuals show that student interactions, surprisingly, reduce smoking by approximately 70 percent with respect to the equilibrium smoking that would occur without interactions.

Suggested Citation

  • Alberto Bisin & Andrea Moro & Giorgio Topa, 2011. "The Empirical Content of Models with Multiple Equilibria in Economies with Social Interactions," NBER Working Papers 17196, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:17196
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    3. Vincent BOUCHER & Ismael MOURIFIÉ, 2013. "My Friend Far Far Away: Asymptotic Properties of Pairwise Stable Networks," Working Papers tecipa-499, University of Toronto, Department of Economics.
    4. Topa, Giorgio & Zenou, Yves, 2015. "Neighborhood and Network Effects," Handbook of Regional and Urban Economics, in: Gilles Duranton & J. V. Henderson & William C. Strange (ed.), Handbook of Regional and Urban Economics, edition 1, volume 5, chapter 0, pages 561-624, Elsevier.
    5. Balbus, Lukasz & Dziewulski, Pawel & Reffett, Kevin & Wozny, Lukasz, 2022. "Markov distributional equilibrium dynamics in games with complementarities and no aggregate risk," Theoretical Economics, Econometric Society, vol. 17(2), May.
    6. Áureo de Paula, 2015. "Econometrics of network models," CeMMAP working papers 52/15, Institute for Fiscal Studies.
    7. Leung, Michael P., 2015. "Two-step estimation of network-formation models with incomplete information," Journal of Econometrics, Elsevier, vol. 188(1), pages 182-195.
    8. ÖZGÜR, Onur & BISIN, Alberto, 2011. "Dynamic Linear Economies with Social Interactions," Cahiers de recherche 04-2011, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    9. Kojevnikov, Denis & Song, Kyungchul, 2023. "Econometric inference on a large Bayesian game with heterogeneous beliefs," Journal of Econometrics, Elsevier, vol. 237(1).
    10. Giacomo De Giorgi & Michele Pellizzari, 2014. "Understanding Social Interactions: Evidence from the Classroom," Economic Journal, Royal Economic Society, vol. 124(579), pages 917-953, September.
    11. Ronak Jain & Vatsal Khandelwal, 2024. "Silent networks: The role of inaccurate beliefs in reducing useful social interactions," CSAE Working Paper Series 2024-06, Centre for the Study of African Economies, University of Oxford.
    12. Áureo de Paula, 2013. "Econometric Analysis of Games with Multiple Equilibria," Annual Review of Economics, Annual Reviews, vol. 5(1), pages 107-131, May.
    13. Arun Advani & Bansi Malde, 2018. "Methods to identify linear network models: a review," Swiss Journal of Economics and Statistics, Springer;Swiss Society of Economics and Statistics, vol. 154(1), pages 1-16, December.
    14. Jose-Alberto Guerra & Myra Mohnen, 2022. "Multinomial Choice with Social Interactions: Occupations in Victorian London," The Review of Economics and Statistics, MIT Press, vol. 104(4), pages 736-747, October.
    15. Mathieu Lambotte, 2024. "Identification and estimation of asymmetries in peer effects for binary outcomes," Economics Working Paper Archive (University of Rennes & University of Caen) 2024-05, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
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    17. 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.

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    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • I1 - Health, Education, and Welfare - - Health

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