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Dynamic Games in Empirical Industrial Organization

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  • Victor Aguirregabiria
  • Allan Collard-Wexler
  • Stephen P. Ryan

Abstract

This survey is organized around three main topics: models, econometrics, and empirical applications. Section 2 presents the theoretical framework, introduces the concept of Markov Perfect Nash Equilibrium, discusses existence and multiplicity, and describes the representation of this equilibrium in terms of conditional choice probabilities. We also discuss extensions of the basic framework, including models in continuous time, the concepts of oblivious equilibrium and experience-based equilibrium, and dynamic games where firms have non-equilibrium beliefs. In section 3, we first provide an overview of the types of data used in this literature, before turning to a discussion of identification issues and results, and estimation methods. We review different methods to deal with multiple equilibria and large state spaces. We also describe recent developments for estimating games in continuous time and incorporating serially correlated unobservables, and discuss the use of machine learning methods to solving and estimating dynamic games. Section 4 discusses empirical applications of dynamic games in IO. We start describing the first empirical applications in this literature during the early 2000s. Then, we review recent applications dealing with innovation, antitrust and mergers, dynamic pricing, regulation, product repositioning, advertising, uncertainty and investment, airline network competition, dynamic matching, and natural resources. We conclude with our view of the progress made in this literature and the remaining challenges.

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  • Victor Aguirregabiria & Allan Collard-Wexler & Stephen P. Ryan, 2021. "Dynamic Games in Empirical Industrial Organization," Papers 2109.01725, arXiv.org, revised Sep 2021.
  • Handle: RePEc:arx:papers:2109.01725
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    1. Takuma Matsuda & Suguru Otani, 2022. "Unified Container Shipping Industry Data From 1966: Freight Rate, Shipping Quantity, Newbuilding, Secondhand, and Scrap Price," Papers 2211.16292, arXiv.org, revised Apr 2023.
    2. 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.
    3. Taisuke Otsu & Martin Pesendorfer, 2023. "Equilibrium multiplicity in dynamic games: Testing and estimation," The Econometrics Journal, Royal Economic Society, vol. 26(1), pages 26-42.
    4. Victor Aguirregabiria & Alessandro Iaria & Senay Sokullu, 2023. "Identification and Estimation of Demand Models with Endogenous Product Entry and Exit," Working Papers tecipa-755, University of Toronto, Department of Economics.
    5. Paul S. Koh, 2022. "Estimating Dynamic Games with Unknown Information Structure," Papers 2205.03706, arXiv.org, revised May 2022.
    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.

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    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • L0 - Industrial Organization - - General

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