IDEAS home Printed from https://ideas.repec.org/p/tut/cremwp/2024-05.html
   My bibliography  Save this paper

Identification and estimation of asymmetries in peer effects for binary outcomes

Author

Listed:
  • Mathieu Lambotte

    (Univ Rennes, CNRS, CREM – UMR6211, F-35000 Rennes France)

Abstract

We introduce asymmetry in the analysis of peer effects stemming from a taste for conformity. Indeed, overdoing and underdoing relatively to the social norm might lead to asymmetric social costs of deviating from the norm. The magnitude and direction of this asymmetry depends on the behavior under scrutiny. We develop conditions under which this network game results in a unique Bayes-Nash equilibrium depending on rational expectations about peers’ behavior and propose an estimation strategy based on a nested fixed point maximum likelihood estimator. The model is applied to data on smoking and alcohol consumption of secondary school students in the United States. Using the estimated parameters, we estimate the subsidies a social planner should provide to restore players’ first-best strategies. Empirical evidence converges to indicate that assuming a symmetric social distance function in peer effects model might be misleading.

Suggested Citation

  • 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.
    • Handle: RePEc:tut:cremwp:2024-05
    as

    Download full text from publisher

    File URL: https://ged.univ-rennes1.fr/nuxeo/site/esupversions/2d657eeb-a1ca-421a-95b8-3bf8fd5c3c65
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Peter Kooreman & Adriaan R. Soetevent, 2007. "A discrete-choice model with social interactions: with an application to high school teen behavior," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(3), pages 599-624.
    2. Lung-fei Lee & Ji Li & Xu Lin, 2014. "Binary Choice Models with Social Network under Heterogeneous Rational Expectations," The Review of Economics and Statistics, MIT Press, vol. 96(3), pages 402-417, July.
    3. McKelvey Richard D. & Palfrey Thomas R., 1995. "Quantal Response Equilibria for Normal Form Games," Games and Economic Behavior, Elsevier, vol. 10(1), pages 6-38, July.
    4. Liu, Xiaodong & Patacchini, Eleonora & Zenou, Yves, 2014. "Endogenous peer effects: local aggregate or local average?," Journal of Economic Behavior & Organization, Elsevier, vol. 103(C), pages 39-59.
    5. Jackson, Matthew O. & Zenou, Yves, 2015. "Games on Networks," Handbook of Game Theory with Economic Applications,, Elsevier.
    6. 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.
    7. Liu, Xiaodong & Zhou, Jiannan, 2017. "A social interaction model with ordered choices," Economics Letters, Elsevier, vol. 161(C), pages 86-89.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Aristide Houndetoungan, 2024. "Count Data Models with Heterogeneous Peer Effects under Rational Expectations," Papers 2405.17290, arXiv.org.
    2. Yann Bramoullé & Habiba Djebbari & Bernard Fortin, 2020. "Peer Effects in Networks: A Survey," Annual Review of Economics, Annual Reviews, vol. 12(1), pages 603-629, August.
    3. 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.
    4. Yann Bramoullé & Rachel Kranton, 2015. "Games Played on Networks," AMSE Working Papers 1530, Aix-Marseille School of Economics, France.
    5. 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.
    6. Emerson Melo, 2022. "On the uniqueness of quantal response equilibria and its application to network games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 74(3), pages 681-725, October.
    7. Steven N. Durlauf & Yannis M. Ioannides, 2010. "Social Interactions," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 451-478, September.
    8. Kojevnikov, Denis & Song, Kyungchul, 2023. "Econometric inference on a large Bayesian game with heterogeneous beliefs," Journal of Econometrics, Elsevier, vol. 237(1).
    9. Mauleon, Ana & Nanumyan, Mariam & Vannetelbosch, Vincent, 2024. "Ideal efforts and consensus in a multi-layer network game," LIDAM Discussion Papers CORE 2024023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Yann Algan & Quoc-Anh Do & Nicolò Dalvit & Alexis Le Chapelain & Yves Zenou, 2015. "How Social Networks Shape Our Beliefs: A Natural Experiment among Future French Politicians," Working Papers hal-03459820, HAL.
    11. repec:spo:wpmain:info:hdl:2441/78vacv4udu92eq3fec89svm9uv is not listed on IDEAS
    12. Gibbons, Steve & Overman, Henry G. & Patacchini, Eleonora, 2015. "Spatial Methods," 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 115-168, Elsevier.
    13. Chih‐Sheng Hsieh & Lung‐Fei Lee & Vincent Boucher, 2020. "Specification and estimation of network formation and network interaction models with the exponential probability distribution," Quantitative Economics, Econometric Society, vol. 11(4), pages 1349-1390, November.
    14. Golub, Benjamin & Hsieh, Yu-Chi & Sadler, Evan, 2024. "On the difficulty of characterizing network formation with endogenous behavior," Mathematical Social Sciences, Elsevier, vol. 129(C), pages 107-110.
    15. Ana Balsa & Carlos D az, 2018. "Social interactions in health behaviors and conditions," Documentos de Trabajo/Working Papers 1802, Facultad de Ciencias Empresariales y Economia. Universidad de Montevideo..
    16. Vincent Boucher & Carlo L. Del Bello & Fabrizio Panebianco & Thierry Verdier & Yves Zenou, 2023. "Education Transmission and Network Formation," Journal of Labor Economics, University of Chicago Press, vol. 41(1), pages 129-173.
    17. repec:hal:spmain:info:hdl:2441/78vacv4udu92eq3fec89svm9uv is not listed on IDEAS
    18. Áureo de Paula, 2015. "Econometrics of network models," CeMMAP working papers CWP52/15, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. Zhang, Yang & Du, Xiaomin, 2017. "Network effects on strategic interactions: A laboratory approach," Journal of Economic Behavior & Organization, Elsevier, vol. 143(C), pages 133-146.
    20. Lin, Xu, 2014. "Peer effects in adolescents' delinquent behaviors: Evidence from a binary choice network model," Regional Science and Urban Economics, Elsevier, vol. 46(C), pages 73-92.
    21. Hahn, Youjin & Islam, Asadul & Patacchini, Eleonora & Zenou, Yves, 2015. "Network Structure and Education Outcomes: Evidence from a Field Experiment in Bangladesh," IZA Discussion Papers 8872, Institute of Labor Economics (IZA).
    22. Cohen-Cole, Ethan & Patacchini, Eleonora & Zenou, Yves, 2015. "Static and dynamic networks in interbank markets," Network Science, Cambridge University Press, vol. 3(1), pages 98-123, March.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • 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
    • C57 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Econometrics of Games and Auctions
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tut:cremwp:2024-05. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: GERMAIN Lucie (email available below). General contact details of provider: https://edirc.repec.org/data/crmrefr.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.