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Inference in a synchronization game with social interactions


  • de Paula, Áureo


This paper studies inference in a continuous time game where an agent's decision to quit an activity depends on the participation of other players. In equilibrium, similar actions can be explained not only by direct influences but also by correlated factors. Our model can be seen as a simultaneous duration model with multiple decision makers and interdependent durations. We study the problem of determining the existence and uniqueness of equilibrium stopping strategies in this setting. This paper provides results and conditions for the detection of these endogenous effects. First, we show that the presence of such effects is a necessary and sufficient condition for simultaneous exits. This allows us to set up a nonparametric test for the presence of such influences, which is robust to multiple equilibria. Second, we provide conditions under which parameters in the game are identified. Finally, we apply the model to data on desertion in the Union Army during the American Civil War, and find evidence of endogenous influences.

Suggested Citation

  • de Paula, Áureo, 2009. "Inference in a synchronization game with social interactions," Journal of Econometrics, Elsevier, vol. 148(1), pages 56-71, January.
  • Handle: RePEc:eee:econom:v:148:y:2009:i:1:p:56-71

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    References listed on IDEAS

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    2. Jing-Zhi Huang & Marti G. Subrahmanyam & G. George Yu, 1999. "Pricing And Hedging American Options: A Recursive Integration Method," World Scientific Book Chapters, in: Marco Avellaneda (ed.), Quantitative Analysis In Financial Markets Collected Papers of the New York University Mathematical Finance Seminar, chapter 8, pages 219-239, World Scientific Publishing Co. Pte. Ltd..
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    Cited by:

    1. Seth Richards‐Shubik, 2015. "Peer effects in sexual initiation: Separating demand and supply mechanisms," Quantitative Economics, Econometric Society, vol. 6(3), pages 663-702, November.
    2. Steven N. Durlauf & Yannis M. Ioannides, 2010. "Social Interactions," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 451-478, September.
    3. Landsman, Vardit & Nitzan, Irit, 2020. "Cross-decision social effects in product adoption and defection decisions," International Journal of Research in Marketing, Elsevier, vol. 37(2), pages 213-235.
    4. Ruixuan Liu, 2020. "A competing risks model with time‐varying heterogeneity and simultaneous failure," Quantitative Economics, Econometric Society, vol. 11(2), pages 535-577, May.
    5. Franco Peracchi & Claudio Rossetti, 2013. "The heterogeneous thresholds ordered response model: identification and inference," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(3), pages 703-722, June.
    6. Bo Honoré & Áureo de Paula, 2011. "Interdependent Durations in Joint Retirement," Working Papers, Center for Retirement Research at Boston College wp2011-5, Center for Retirement Research, revised Feb 2011.
    7. Áureo de Paula, 2015. "Econometrics of network models," CeMMAP working papers 52/15, Institute for Fiscal Studies.
    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. Bo E. Honoré & Aureo de Paula, 2009. ""Interdependent Durations" Third Version," PIER Working Paper Archive 09-039, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Feb 2008.
    10. Pinheiro, Marcelo, 2008. "Loyalty, peer group effects, and 401(k)," The Quarterly Review of Economics and Finance, Elsevier, vol. 48(1), pages 94-122, February.
    11. Ethan Cohen-Cole & Andrei Kirilenko & Eleonora Patacchini, 2010. "Are Networks Priced? Network Topology and Order Trading Strategies in High Liquidity Markets," EIEF Working Papers Series 1011, Einaudi Institute for Economics and Finance (EIEF), revised Apr 2010.
    12. Bo E. Honore & Aureo de Paula, 2007. "Interdependent Durations, Second Version," PIER Working Paper Archive 08-044, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania, revised 01 Nov 2008.
    13. Áureo de Paula, 2013. "Econometric Analysis of Games with Multiple Equilibria," Annual Review of Economics, Annual Reviews, vol. 5(1), pages 107-131, May.
    14. Kline, Brendan, 2015. "Identification of complete information games," Journal of Econometrics, Elsevier, vol. 189(1), pages 117-131.
    15. William A. Brock & Steven N. Durlauf, 2010. "Adoption Curves and Social Interactions," Journal of the European Economic Association, MIT Press, vol. 8(1), pages 232-251, March.
    16. Bo E. Honoré & Áureo de Paula, 2016. "A new model for interdependent durations with an application to joint retirement," CeMMAP working papers CWP07/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    17. ÖZGÜR, Onur, 2010. "Local Interactions," Cahiers de recherche 2010-06, Universite de Montreal, Departement de sciences economiques.
    18. Bo E. Honor & Áureo De Paula, 2010. "Interdependent Durations," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 77(3), pages 1138-1163.
    19. Haenlein, Michael, 2013. "Social interactions in customer churn decisions: The impact of relationship directionality," International Journal of Research in Marketing, Elsevier, vol. 30(3), pages 236-248.
    20. Bhatia, Tulikaa & Wang, Lei, 2011. "Identifying physician peer-to-peer effects using patient movement data," International Journal of Research in Marketing, Elsevier, vol. 28(1), pages 51-61.

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    More about this item


    Duration Optimal stopping Game estimation Coordination;

    JEL classification:

    • C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General


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