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Dynamic Games with Asymmetric Information: A Framework for Empirical Work

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  • Chaim Fershtman
  • Ariel Pakes

Abstract

We develop a framework for the analysis of dynamic oligopolies with persistant sources of asymmetric information that enables applied analysis of situations of empirical importance that have been difficult to deal with. The framework generates policies that are "relatively" easy for agents to use while still being optimal in a meaningful sense, and is amenable to empirical research in that its equilibrium conditions can be tested and equilibrium policies are relatively easy to compute. We conclude with an example that endogenizes the maintenance decisions of electricity generators when the costs states of the generators are private information. Copyright 2012, Oxford University Press.

Suggested Citation

  • Chaim Fershtman & Ariel Pakes, 2012. "Dynamic Games with Asymmetric Information: A Framework for Empirical Work," The Quarterly Journal of Economics, Oxford University Press, vol. 127(4), pages 1611-1661.
  • Handle: RePEc:oup:qjecon:v:127:y:2012:i:4:p:1611-1661
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    File URL: http://hdl.handle.net/10.1093/qje/qjs025
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    Cited by:

    1. Pierpaolo Battigalli & Simone Cerreia-Vioglio & Fabio Maccheroni & Massimo Marinacci, 2015. "Self-Confirming Equilibrium and Model Uncertainty," American Economic Review, American Economic Association, vol. 105(2), pages 646-677, February.
    2. C. Lanier Benkard & Przemyslaw Jeziorski & Gabriel Y. Weintraub, 2013. "Oblivious Equilibrium for Concentrated Industries," NBER Working Papers 19307, National Bureau of Economic Research, Inc.
    3. John Asker & Chaim Fershtman & Jihye Jeon & Ariel Pakes, 2016. "The Competitive Effects of Information Sharing," NBER Working Papers 22836, National Bureau of Economic Research, Inc.
    4. repec:eee:indorg:v:53:y:2017:i:c:p:241-266 is not listed on IDEAS
    5. C. Lanier Benkard & Przemyslaw Jeziorski & Gabriel Y. Weintraub, 2015. "Oblivious equilibrium for concentrated industries," RAND Journal of Economics, RAND Corporation, vol. 46(4), pages 671-708, October.
    6. Ron Borkovsky & Paul Ellickson & Brett Gordon & Victor Aguirregabiria & Pedro Gardete & Paul Grieco & Todd Gureckis & Teck-Hua Ho & Laurent Mathevet & Andrew Sweeting, 2015. "Multiplicity of equilibria and information structures in empirical games: challenges and prospects," Marketing Letters, Springer, vol. 26(2), pages 115-125, June.
    7. Osborne, Matthew & Shapiro, Adam Hale, 2014. "A Dynamic Model of Price Signaling, Consumer Learning, and Price Adjustment," Working Paper Series 2014-27, Federal Reserve Bank of San Francisco.
    8. Jie Bai, 2016. "Melons as Lemons: Asymmetric Information, Consumer Learning and Seller Reputation," Natural Field Experiments 00540, The Field Experiments Website.
    9. Christopher Gedge & James W. Roberts & Andrew Sweeting, 2014. "A Model of Dynamic Limit Pricing with an Application to the Airline Industry," NBER Working Papers 20293, National Bureau of Economic Research, Inc.
    10. Martin Watzinger, 2016. "The Effect of a Credit Crunch on Equilibrium Market Structure," Computational Economics, Springer;Society for Computational Economics, vol. 48(1), pages 105-130, June.
    11. Zhou, Tingyu & Clapp, John M., 2015. "The location of new anchor stores within metropolitan areas," Regional Science and Urban Economics, Elsevier, vol. 50(C), pages 87-107.

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