IDEAS home Printed from https://ideas.repec.org/a/spr/jecrev/v67y2016i4d10.1111_jere.12108.html
   My bibliography  Save this article

Bayesian Estimation of Entry Games with Multiple Players and Multiple Equilibria

Author

Listed:
  • Yuko Onishi

    (University of Tokyo)

  • Yasuhiro Omori

    (University of Tokyo)

Abstract

Entry game models are often used to study the nature of firms’ profits and the nature of competition among firms in empirical studies. However, when there are multiple players in an oligopoly market, the resulting multiple equilibria have made it difficult in previous studies to estimate the payoff functions of players in complete information, static and discrete games without using unreasonable assumptions. To overcome this difficulty, the present paper proposes a practical estimation method for an entry game with three players using a Bayesian approach. Some mild assumptions are imposed on the payoff function, and the average competitive effect is used to capture the entry effect of the number of firms. Our proposed methodology is applied to Japanese airline data from the year 2000, when there were three major airline companies, ANA, JAL and JAS. The model comparison is conducted to investigate the nature of strategic interaction among these Japanese airline companies.

Suggested Citation

  • Yuko Onishi & Yasuhiro Omori, 2016. "Bayesian Estimation of Entry Games with Multiple Players and Multiple Equilibria," The Japanese Economic Review, Springer, vol. 67(4), pages 418-440, December.
    • Handle: RePEc:spr:jecrev:v:67:y:2016:i:4:d:10.1111_jere.12108
    DOI: 10.1111/jere.12108
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1111/jere.12108
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1111/jere.12108?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Chib, Siddhartha, 2001. "Markov chain Monte Carlo methods: computation and inference," Handbook of Econometrics, in: J.J. Heckman & E.E. Leamer (ed.), Handbook of Econometrics, edition 1, volume 5, chapter 57, pages 3569-3649, Elsevier.
    2. Berry, Steven T, 1992. "Estimation of a Model of Entry in the Airline Industry," Econometrica, Econometric Society, vol. 60(4), pages 889-917, July.
    3. Shinya Sugawara & Yasuhiro Omori, 2012. "Duopoly In The Japanese Airline Market: Bayesian Estimation For The Entry Game," The Japanese Economic Review, Japanese Economic Association, vol. 63(3), pages 310-332, September.
    4. Patrick Bajari & Han Hong & Stephen P. Ryan, 2010. "Identification and Estimation of a Discrete Game of Complete Information," Econometrica, Econometric Society, vol. 78(5), pages 1529-1568, September.
    5. Kooreman, Peter, 1994. "Estimation of Econometric Models of Some Discrete Games," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 9(3), pages 255-268, July-Sept.
    6. Elie Tamer, 2003. "Incomplete Simultaneous Discrete Response Model with Multiple Equilibria," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(1), pages 147-165.
    7. Federico Ciliberto & Elie Tamer, 2009. "Market Structure and Multiple Equilibria in Airline Markets," Econometrica, Econometric Society, vol. 77(6), pages 1791-1828, November.
    8. Bresnahan, Timothy F. & Reiss, Peter C., 1991. "Empirical models of discrete games," Journal of Econometrics, Elsevier, vol. 48(1-2), pages 57-81.
    9. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    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. Aradillas-Lopez, Andres, 2012. "Pairwise-difference estimation of incomplete information games," Journal of Econometrics, Elsevier, vol. 168(1), pages 120-140.
    2. Yuko Onishi & Yasuhiro Omori, 2014. "Bayesian Estimation of Entry Games with Multiple Players and Multiple Equilibria," CIRJE F-Series CIRJE-F-943, CIRJE, Faculty of Economics, University of Tokyo.
    3. 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.
    4. Larry G. Epstein & Hiroaki Kaido & Kyoungwon Seo, 2016. "Robust Confidence Regions for Incomplete Models," Econometrica, Econometric Society, vol. 84, pages 1799-1838, September.
    5. Jason R. Blevins, 2015. "Structural Estimation Of Sequential Games Of Complete Information," Economic Inquiry, Western Economic Association International, vol. 53(2), pages 791-811, April.
    6. Paul B. Ellickson & Sanjog Misra, 2011. "Structural Workshop Paper --Estimating Discrete Games," Marketing Science, INFORMS, vol. 30(6), pages 997-1010, November.
    7. Andrew Chesher & Adam Rosen, 2012. "Simultaneous equations for discrete outcomes: coherence, completeness, and identification," CeMMAP working papers CWP21/12, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    8. Dunker, Fabian & Hoderlein, Stefan & Kaido, Hiroaki & Sherman, Robert, 2018. "Nonparametric identification of the distribution of random coefficients in binary response static games of complete information," Journal of Econometrics, Elsevier, vol. 206(1), pages 83-102.
    9. Jeremy Fox & Natalia Lazzati, 2013. "Identification of discrete choice models for bundles and binary games," CeMMAP working papers 04/13, Institute for Fiscal Studies.
    10. Shiko Maruyama, 2009. "Estimating Sequential-move Games by a Recursive Conditioning Simulator," Discussion Papers 2009-01, School of Economics, The University of New South Wales.
    11. Shinya Sugawara & Yasuhiro Omori, 2017. "An Econometric Analysis of Insurance Markets with Separate Identification for Moral Hazard and Selection Problems," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 473-502, October.
    12. Hoshino, Tadao & Yanagi, Takahide, 2023. "Treatment effect models with strategic interaction in treatment decisions," Journal of Econometrics, Elsevier, vol. 236(2).
    13. Kline, Brendan & Tamer, Elie, 2012. "Bounds for best response functions in binary games," Journal of Econometrics, Elsevier, vol. 166(1), pages 92-105.
    14. 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.
    15. 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.
    16. Xiao, Ruli, 2018. "Identification and estimation of incomplete information games with multiple equilibria," Journal of Econometrics, Elsevier, vol. 203(2), pages 328-343.
    17. Jun, Sung Jae & Pinkse, Joris, 2020. "Counterfactual prediction in complete information games: Point prediction under partial identification," Journal of Econometrics, Elsevier, vol. 216(2), pages 394-429.
    18. Andrew Sweeting, 2005. "Coordination Games, Multiple Equilibria and the Timing of Radio Commercials," 2005 Meeting Papers 490, Society for Economic Dynamics.
    19. Philip G. Gayle & Zijun Luo, 2015. "Choosing between Order-of-Entry Assumptions in Empirical Entry Models: Evidence from Competition between Burger King and McDonald's Restaurant Outlets," Journal of Industrial Economics, Wiley Blackwell, vol. 63(1), pages 129-151, March.
    20. Christian Bontemps & Raquel Menezes Bezerra Sampaio, 2020. "Entry games for the airline industry," Post-Print hal-02137358, HAL.

    More about this item

    Keywords

    C11; L13; L93;
    All these keywords.

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets
    • L93 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Air Transportation

    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:spr:jecrev:v:67:y:2016:i:4:d:10.1111_jere.12108. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.