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Industry dynamics: Foundations for models with an infinite number of firms

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  • Weintraub, Gabriel Y.
  • Benkard, C. Lanier
  • Van Roy, Benjamin

Abstract

This paper explores the connection between three important threads of economic research offering different approaches to studying the dynamics of an industry with heterogeneous firms. Finite models of the form pioneered by Ericson and Pakes (1995) capture the dynamics of a finite number of heterogeneous firms as they compete in an industry, and are typically analyzed using the concept of Markov perfect equilibrium (MPE). Infinite models of the form pioneered by Hopenhayn (1992), on the other hand, consider an infinite number of infinitesimal firms, and are typically analyzed using the concept of stationary equilibrium (SE). A third approach uses oblivious equilibrium (OE), which maintains the simplifying benefits of an infinite model but within the more realistic setting of a finite model. The paper relates these three approaches. The main result of the paper provides conditions under which SE of infinite models approximate MPE of finite models arbitrarily well in asymptotically large markets. Our conditions require that the distribution of firm states in SE obeys a certain âlight-tailâ condition. In a second set of results, we show that the set of OE of a finite model approaches the set of SE of the infinite model in large markets under a similar light-tail condition.

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  • Weintraub, Gabriel Y. & Benkard, C. Lanier & Van Roy, Benjamin, 2011. "Industry dynamics: Foundations for models with an infinite number of firms," Journal of Economic Theory, Elsevier, vol. 146(5), pages 1965-1994, September.
  • Handle: RePEc:eee:jetheo:v:146:y:2011:i:5:p:1965-1994
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    References listed on IDEAS

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    4. Régis Chenavaz & Corina Paraschiv & Gabriel Turinici, 2021. "Dynamic Pricing of New Products in Competitive Markets: A Mean-Field Game Approach," Dynamic Games and Applications, Springer, vol. 11(3), pages 463-490, September.
    5. Kikuchi, Tomoo & Nishimura, Kazuo & Stachurski, John, 2018. "Span of control, transaction costs and the structure of production chains," Theoretical Economics, Econometric Society, vol. 13(2), May.
    6. Krishnamurthy Iyer & Ramesh Johari & Mukund Sundararajan, 2014. "Mean Field Equilibria of Dynamic Auctions with Learning," Management Science, INFORMS, vol. 60(12), pages 2949-2970, December.
    7. Piotr Więcek & Eitan Altman, 2015. "Stationary Anonymous Sequential Games with Undiscounted Rewards," Journal of Optimization Theory and Applications, Springer, vol. 166(2), pages 686-710, August.
    8. Jian Yang, 2021. "Analysis of Markovian Competitive Situations Using Nonatomic Games," Dynamic Games and Applications, Springer, vol. 11(1), pages 184-216, March.
    9. Ren'e Aid & Matteo Basei & Giorgio Ferrari, 2023. "A Stationary Mean-Field Equilibrium Model of Irreversible Investment in a Two-Regime Economy," Papers 2305.00541, arXiv.org.
    10. Cao, Haoyang & Dianetti, Jodi & Ferrari, Giorgio, 2021. "Stationary Discounted and Ergodic Mean Field Games of Singular Control," Center for Mathematical Economics Working Papers 650, Center for Mathematical Economics, Bielefeld University.
    11. Sachin Adlakha & Ramesh Johari, 2013. "Mean Field Equilibrium in Dynamic Games with Strategic Complementarities," Operations Research, INFORMS, vol. 61(4), pages 971-989, August.
    12. Jian Yang, 2017. "A link between sequential semi-anonymous nonatomic games and their large finite counterparts," International Journal of Game Theory, Springer;Game Theory Society, vol. 46(2), pages 383-433, May.
    13. Jian Yang, 2015. "A Link between Sequential Semi-anonymous Nonatomic Games and their Large Finite Counterparts," Papers 1510.06809, arXiv.org, revised Jun 2016.
    14. Jian Yang, 2015. "Analysis of Markovian Competitive Situations using Nonatomic Games," Papers 1510.06813, arXiv.org, revised Apr 2017.

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