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Computable Markov-Perfect Industry Dynamics: Existence, Purification, and Multiplicity

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  • Doraszelski, Ulrich
  • Satterthwaite, Mark
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    Abstract

    We provide a general model of dynamic competition in an oligopolistic industry with investment, entry, and exit. To ensure that there exists a computationally tractable Markov perfect equilibrium, we introduce firm heterogeneity in the form of randomly drawn, privately known scrap values and setup costs into the model. Our game of incomplete information always has an equilibrium in cutoff entry/exit strategies. In contrast, the existence of an equilibrium in the Ericson & Pakes (1995) model of industry dynamics requires admissibility of mixed entry/exit strategies, contrary to the assertion in their paper, that existing algorithms cannot cope with. In addition, we provide a condition on the model's primitives that ensures that the equilibrium is in pure investment strategies. Building on this basic existence result, we first show that a symmetric equilibrium exists under appropriate assumptions on the model's primitives. Second, we show that, as the distribution of the random scrap values/setup costs becomes degenerate, equilibria in cutoff entry/exit strategies converge to equilibria in mixed entry/exit strategies of the game of complete information. Finally, we provide the first example of multiple symmetric equilibria in this literature.

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    Bibliographic Info

    Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 6212.

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    Date of creation: Mar 2007
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    Handle: RePEc:cpr:ceprdp:6212

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    Keywords: dynamic oligopoly; industry dynamics; Markov perfect equilibrium;

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    Cited by:
    1. Victor Aguirregabiria & Pedro mira, 2007. "Dynamic Discrete Choice Structural Models: A Survey," Working Papers tecipa-297, University of Toronto, Department of Economics.
    2. Patrick Bajari & C. Lanier Benkard & Jonathan Levin, 2007. "Estimating Dynamic Models of Imperfect Competition," Econometrica, Econometric Society, Econometric Society, vol. 75(5), pages 1331-1370, 09.
    3. Duggan, John & Kalandrakis, Tasos, 2012. "Dynamic legislative policy making," Journal of Economic Theory, Elsevier, vol. 147(5), pages 1653-1688.
    4. Victor Aguirregabiria & Chun-Yu Ho, 2008. "A Dynamic Oligopoly Game of the US Airline Industry: Estimation and Policy Experiments," Working Papers tecipa-337, University of Toronto, Department of Economics.
    5. Markovich, Sarit, 2008. "Snowball: A dynamic oligopoly model with indirect network effects," Journal of Economic Dynamics and Control, Elsevier, Elsevier, vol. 32(3), pages 909-938, March.
    6. Wilson, Nathan E., 2012. "Uncertain regulatory timing and market dynamics," International Journal of Industrial Organization, Elsevier, Elsevier, vol. 30(1), pages 102-115.
    7. Hall, Joshua & Laincz, Christopher, 2012. "Optimal R&D Subsidies with Heterogeneous Firms in a Dynamic Setting," School of Economics Working Paper Series 2012-13, LeBow College of Business, Drexel University.

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