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A Framework for Dynamic Oligopoly in Concentrated Industries

Author

Listed:
  • Bar Ifrach
  • Gabriel Y. Weintraub

Abstract

In this article we introduce a new computationally tractable framework for Ericson and Pakes-style dynamic oligopoly models that overcomes the computational complexity involved in computing Markov perfect equilibrium (MPE). First, we define a new equilibrium concept that we call moment-based Markov equilibrium (MME), in which firms keep track of their own state, the detailed state of dominant firms, and few moments of the distribution of fringe firms’ states. Second, we provide guidelines to use MME in applied work and illustrate with an application how it can endogenize the market structure in a dynamic industry model even with hundreds of firms. Third, we develop a series of results that provide support for using MME as an approximation. We present numerical experiments showing that MME approximates MPE for important classes of models. Then, we introduce novel unilateral deviation error bounds that can be used to test the accuracy of MME as an approximation in large-scale settings. Overall, our new framework opens the door to study new issues in industry dynamics.

Suggested Citation

  • Bar Ifrach & Gabriel Y. Weintraub, 2017. "A Framework for Dynamic Oligopoly in Concentrated Industries," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 84(3), pages 1106-1150.
  • Handle: RePEc:oup:restud:v:84:y:2017:i:3:p:1106-1150.
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    File URL: http://hdl.handle.net/10.1093/restud/rdw047
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    Citations

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    Cited by:

    1. Takeshi Fukasawa, 2023. "The Use of Symmetry for Models with Variable-size Variables," Papers 2311.08650, arXiv.org, revised Dec 2023.
    2. Light, Bar & Weintraub, Gabriel, 2018. "Mean Field Equilibrium: Uniqueness, Existence, and Comparative Statics," Research Papers 3731, Stanford University, Graduate School of Business.
    3. Matthew Grennan & Robert J. Town, 2020. "Regulating Innovation with Uncertain Quality: Information, Risk, and Access in Medical Devices," American Economic Review, American Economic Association, vol. 110(1), pages 120-161, January.
    4. Victor Aguirregabiria & Allan Collard-Wexler & Stephen P. Ryan, 2021. "Dynamic Games in Empirical Industrial Organization," Papers 2109.01725, arXiv.org, revised Sep 2021.
    5. El Hadi Caoui, 2019. "Estimating the Costs of Standardization: Evidence from the Movie Industry," CESifo Working Paper Series 8040, CESifo.
    6. Takeshi Fukasawa, 2022. "Firm's Static Behavior under Dynamic Demand," Discussion Paper Series DP2022-19, Research Institute for Economics & Business Administration, Kobe University, revised Sep 2022.
    7. Jihye Jeon, 2022. "Learning and investment under demand uncertainty in container shipping," RAND Journal of Economics, RAND Corporation, vol. 53(1), pages 226-259, March.
    8. Dean Corbae & Pablo D'Erasmo, 2014. "Capital requirements in a quantitative model of banking industry dynamics," Working Papers 14-13, Federal Reserve Bank of Philadelphia.
    9. Dean Corbae & Pablo D'Erasmo, 2021. "Capital Buffers in a Quantitative Model of Banking Industry Dynamics," Econometrica, Econometric Society, vol. 89(6), pages 2975-3023, November.
    10. Dean Corbae & Pablo D'Erasmo, 2021. "Capital Buffers in a Quantitative Model of Banking Industry Dynamics," Working Papers 21-24, Federal Reserve Bank of Philadelphia.
    11. Sears, Louis S. & Lawell, C.Y. Cynthia Lin & Torres, Gerald & Walter, M. Todd, 2022. "Moment-based Markov Equilibrium Estimation of High-Dimension Dynamic Games: An Application to Groundwater Management in California," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322187, Agricultural and Applied Economics Association.
    12. Doraszelski, Ulrich & Escobar, Juan F., 2019. "Protocol invariance and the timing of decisions in dynamic games," Theoretical Economics, Econometric Society, vol. 14(2), May.

    More about this item

    Keywords

    Dynamic oligopoly; Industry dynamics; Computation;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets

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