IDEAS home Printed from https://ideas.repec.org/p/tor/tecipa/tecipa-510.html
   My bibliography  Save this paper

Multiplicity of Equilibria and Information Structures in Empirical Games: Challenges and Prospects

Author

Listed:
  • Ron N. Borkovsky
  • Paul B. Ellickson
  • Brett R. Gordon
  • Victor Aguirregabiria
  • Gardete Pedro

Abstract

Empirical models of strategic games are central to much analysis in marketing and economics. However, two challenges in applying these models to real world data are that such models often admit multiple equilibria and that they require strong informational assumptions. The first implies that the model does not make unique predictions about the data, and the second implies that results may be driven by strong a priori assumptions about the informational setup. This article summarizes recent work that seeks to address both issues and suggests some avenues for future research.

Suggested Citation

  • Ron N. Borkovsky & Paul B. Ellickson & Brett R. Gordon & Victor Aguirregabiria & Gardete Pedro, 2014. "Multiplicity of Equilibria and Information Structures in Empirical Games: Challenges and Prospects," Working Papers tecipa-510, University of Toronto, Department of Economics.
  • Handle: RePEc:tor:tecipa:tecipa-510
    as

    Download full text from publisher

    File URL: https://www.economics.utoronto.ca/public/workingPapers/tecipa-510.pdf
    File Function: Main Text
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Milgrom, Paul & Roberts, John, 1982. "Limit Pricing and Entry under Incomplete Information: An Equilibrium Analysis," Econometrica, Econometric Society, vol. 50(2), pages 443-459, March.
    2. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    3. Doraszelski, Ulrich & Pakes, Ariel, 2007. "A Framework for Applied Dynamic Analysis in IO," Handbook of Industrial Organization, in: Mark Armstrong & Robert Porter (ed.), Handbook of Industrial Organization, edition 1, volume 3, chapter 30, pages 1887-1966, Elsevier.
    4. Ulrich Doraszelski & Mark Satterthwaite, 2010. "Computable Markov‐perfect industry dynamics," RAND Journal of Economics, RAND Corporation, vol. 41(2), pages 215-243, June.
    5. Victor Aguirregabiria & Arvind Magesan, 2020. "Identification and Estimation of Dynamic Games When Players’ Beliefs Are Not in Equilibrium," Review of Economic Studies, Oxford University Press, vol. 87(2), pages 582-625.
    6. James Levinsohn & Steven Berry & Ariel Pakes, 1999. "Voluntary Export Restraints on Automobiles: Evaluating a Trade Policy," American Economic Review, American Economic Association, vol. 89(3), pages 400-430, June.
    7. Bajari, Patrick & Hong, Han & Krainer, John & Nekipelov, Denis, 2010. "Estimating Static Models of Strategic Interactions," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(4), pages 469-482.
    8. Richard Ericson & Ariel Pakes, 1995. "Markov-Perfect Industry Dynamics: A Framework for Empirical Work," Review of Economic Studies, Oxford University Press, vol. 62(1), pages 53-82.
    9. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
    10. Paul B. Ellickson & Sanjog Misra, 2011. "Structural Workshop Paper --Estimating Discrete Games," Marketing Science, INFORMS, vol. 30(6), pages 997-1010, November.
    11. Sridhar Narayanan, 2013. "Bayesian estimation of discrete games of complete information," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 39-81, March.
    12. Ariel Pakes & Paul McGuire, 1994. "Computing Markov-Perfect Nash Equilibria: Numerical Implications of a Dynamic Differentiated Product Model," RAND Journal of Economics, The RAND Corporation, vol. 25(4), pages 555-589, Winter.
    13. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    14. Lee, Robin S. & Pakes, Ariel, 2009. "Multiple equilibria and selection by learning in an applied setting," Economics Letters, Elsevier, vol. 104(1), pages 13-16, July.
    15. Elie Tamer, 2003. "Incomplete Simultaneous Discrete Response Model with Multiple Equilibria," Review of Economic Studies, Oxford University Press, vol. 70(1), pages 147-165.
    16. Federico Ciliberto & Elie Tamer, 2009. "Market Structure and Multiple Equilibria in Airline Markets," Econometrica, Econometric Society, vol. 77(6), pages 1791-1828, November.
    17. David Besanko & Ulrich Doraszelski & Yaroslav Kryukov & Mark Satterthwaite, 2010. "Learning-by-Doing, Organizational Forgetting, and Industry Dynamics," Econometrica, Econometric Society, vol. 78(2), pages 453-508, March.
    18. Ron Borkovsky & Ulrich Doraszelski & Yaroslav Kryukov, 2012. "A dynamic quality ladder model with entry and exit: Exploring the equilibrium correspondence using the homotopy method," Quantitative Marketing and Economics (QME), Springer, vol. 10(2), pages 197-229, June.
    19. Sanjog Misra, 2013. "Markov chain Monte Carlo for incomplete information discrete games," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 117-153, March.
    20. Andrew Sweeting, 2009. "The strategic timing incentives of commercial radio stations: An empirical analysis using multiple equilibria," RAND Journal of Economics, RAND Corporation, vol. 40(4), pages 710-742, December.
    21. David Besanko & Ulrich Doraszelski & Lauren Xiaoyuan Lu & Mark Satterthwaite, 2010. "Lumpy Capacity Investment and Disinvestment Dynamics," Operations Research, INFORMS, vol. 58(4-part-2), pages 1178-1193, August.
    22. Sridhar Narayanan, 2013. "Bayesian estimation of discrete games of complete information," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 39-81, March.
    23. Bresnahan, Timothy F. & Reiss, Peter C., 1991. "Empirical models of discrete games," Journal of Econometrics, Elsevier, vol. 48(1-2), pages 57-81.
    24. Kenneth L. Judd & Philipp Renner & Karl Schmedders, 2012. "Finding all pure‐strategy equilibria in games with continuous strategies," Quantitative Economics, Econometric Society, vol. 3(2), pages 289-331, July.
    25. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
    26. Paul L. E. Grieco, 2014. "Discrete games with flexible information structures: an application to local grocery markets," RAND Journal of Economics, RAND Corporation, vol. 45(2), pages 303-340, June.
    27. Chaim Fershtman & Ariel Pakes, 2012. "Dynamic Games with Asymmetric Information: A Framework for Empirical Work," The Quarterly Journal of Economics, Oxford University Press, vol. 127(4), pages 1611-1661.
    28. Federico Echenique & Ivana Komunjer, 2009. "Testing Models With Multiple Equilibria by Quantile Methods," Econometrica, Econometric Society, vol. 77(4), pages 1281-1297, July.
    29. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945.
    30. Besanko, David & Doraszelski, Ulrich & Lu, Lauren Xiaoyuan & Satterthwaite, Mark, 2010. "On the role of demand and strategic uncertainty in capacity investment and disinvestment dynamics," International Journal of Industrial Organization, Elsevier, vol. 28(4), pages 383-389, July.
    31. Camerer, Colin F. & Ho, Teck-Hua & Chong, Juin-Kuan, 2002. "Sophisticated Experience-Weighted Attraction Learning and Strategic Teaching in Repeated Games," Journal of Economic Theory, Elsevier, vol. 104(1), pages 137-188, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Tobias Salz & Emanuel Vespa, 2020. "Estimating dynamic games of oligopolistic competition: an experimental investigation," RAND Journal of Economics, RAND Corporation, vol. 51(2), pages 447-469, June.
    2. Victor Aguirregabiria, 2021. "Identification of firms’ beliefs in structural models of market competition," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(1), pages 5-33, February.
    3. Tobias Salz & Emanuel Vespa, 2020. "Estimating Dynamic Games of Oligopolistic Competition: An Experimental Investigation," NBER Working Papers 26765, National Bureau of Economic Research, Inc.
    4. Pavel Kireyev, 2016. "Markets for Ideas: Prize Structure, Entry Limits, and the Design of Ideation Contests," Harvard Business School Working Papers 16-129, Harvard Business School.
    5. Victor Aguirregabiria & Jihye Jeon, 2020. "Firms’ Beliefs and Learning: Models, Identification, and Empirical Evidence," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 56(2), pages 203-235, March.
    6. Yang, Chao & Lee, Lung-fei & Qu, Xi, 2018. "Tobit models with social interactions: Complete vs incomplete information," Regional Science and Urban Economics, Elsevier, vol. 73(C), pages 30-50.
    7. William Rand & Roland T. Rust & Min Kim, 2018. "Complex systems: marketing’s new frontier," AMS Review, Springer;Academy of Marketing Science, vol. 8(3), pages 111-127, December.
    8. Sanchez Villalba, Miguel, 2015. "Global inspection games," Journal of Public Economics, Elsevier, vol. 128(C), pages 59-72.
    9. Jos'-Antonio Esp'n-S'nchez & 'lvaro Parra & Yuzhou Wang, 2018. "Equilibrium Uniqueness in Entry Games with Private Information," Cowles Foundation Discussion Papers 2126R, Cowles Foundation for Research in Economics, Yale University, revised May 2021.
    10. Vélez-Velásquez, Juan Sebastián, 2019. "Merger effects with product complementarity: Evidence from Colombia’s telecommunications," Information Economics and Policy, Elsevier, vol. 49(C).

    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. Victor Aguirregabiria & Jihye Jeon, 2020. "Firms’ Beliefs and Learning: Models, Identification, and Empirical Evidence," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 56(2), pages 203-235, March.
    2. Victor Aguirregabiria, 2021. "Identification of firms’ beliefs in structural models of market competition," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 54(1), pages 5-33, February.
    3. Luo, Yao & Xiao, Ping & Xiao, Ruli, 2022. "Identification of dynamic games with unobserved heterogeneity and multiple equilibria," Journal of Econometrics, Elsevier, vol. 226(2), pages 343-367.
    4. Xie, Erhao, 2021. "Empirical properties and identification of adaptive learning models in behavioral game theory," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 798-821.
    5. Brett Hollenbeck, 2020. "Horizontal mergers and innovation in concentrated industries," Quantitative Marketing and Economics (QME), Springer, vol. 18(1), pages 1-37, March.
    6. Gabriel Y. Weintraub & C. Lanier Benkard & Benjamin Van Roy, 2010. "Computational Methods for Oblivious Equilibrium," Operations Research, INFORMS, vol. 58(4-part-2), pages 1247-1265, August.
    7. Jos'-Antonio Esp'n-S'nchez & 'lvaro Parra, 2018. "Entry Games under Private Information," Cowles Foundation Discussion Papers 2126, Cowles Foundation for Research in Economics, Yale University.
    8. Victor Aguirregabiria & Junichi Suzuki, 2015. "Empirical Games of Market Entry and Spatial Competition in Retail Industries," Working Papers tecipa-534, University of Toronto, Department of Economics.
    9. Pakes, Ariel, 2017. "Empirical tools and competition analysis: Past progress and current problems," International Journal of Industrial Organization, Elsevier, vol. 53(C), pages 241-266.
    10. Taisuke Otsu & Martin Pesendorfer, 2021. "Equilibrium multiplicity in dynamic games: testing and estimation," STICERD - Econometrics Paper Series 618, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    11. Todd Guilfoos & Andreas Duus Pape, 2020. "Estimating Case-Based Learning," Games, MDPI, vol. 11(3), pages 1-25, September.
    12. Linli Xu & Jorge M. Silva-Risso & Kenneth C. Wilbur, 2018. "Dynamic Quality Ladder Model Predictions in Nonrandom Holdout Samples," Management Science, INFORMS, vol. 64(7), pages 3187-3207, July.
    13. Liu, Nianqing & Vuong, Quang & Xu, Haiqing, 2017. "Rationalization and identification of binary games with correlated types," Journal of Econometrics, Elsevier, vol. 201(2), pages 249-268.
    14. Erhao Xie, 2018. "Inference in Games Without Nash Equilibrium: An Application to Restaurants, Competition in Opening Hours," Staff Working Papers 18-60, Bank of Canada.
    15. Ianni, A., 2002. "Reinforcement learning and the power law of practice: some analytical results," Discussion Paper Series In Economics And Econometrics 203, Economics Division, School of Social Sciences, University of Southampton.
    16. Ron N. Borkovsky & Ulrich Doraszelski & Yaroslav Kryukov, 2010. "A User's Guide to Solving Dynamic Stochastic Games Using the Homotopy Method," Operations Research, INFORMS, vol. 58(4-part-2), pages 1116-1132, August.
    17. Arifovic, Jasmina & Karaivanov, Alexander, 2010. "Learning by doing vs. learning from others in a principal-agent model," Journal of Economic Dynamics and Control, Elsevier, vol. 34(10), pages 1967-1992, October.
    18. Dürsch, Peter & Kolb, Albert & Oechssler, Jörg & Schipper, Burkhard C., 2005. "Rage Against the Machines: How Subjects Learn to Play Against Computers," Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 63, Free University of Berlin, Humboldt University of Berlin, University of Bonn, University of Mannheim, University of Munich.
    19. Victor Aguirregabiria & Allan Collard-Wexler & Stephen P. Ryan, 2021. "Dynamic Games in Empirical Industrial Organization," NBER Working Papers 29291, National Bureau of Economic Research, Inc.
    20. A. Orhun, 2013. "Spatial differentiation in the supermarket industry: The role of common information," Quantitative Marketing and Economics (QME), Springer, vol. 11(1), pages 3-37, March.

    More about this item

    Keywords

    Empirical games; Structural estimation; Multiple Equilibria; Biased Beliefs; Information structures; Learning in games; Identification;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C57 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Econometrics of Games and Auctions
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

    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:tor:tecipa:tecipa-510. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: .

    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: RePEc Maintainer (email available below). General contact details of provider: .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.