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Markov Perfect Industry Dynamics with Many Firms

  • Weintraub, Gabriel Y.

    (Columbia U)

  • Benkard, C. Lanier

    (Stanford U)

  • Van Roy, Benjamin
Registered author(s):

    We propose an approximation method for analyzing Ericson and Pakes (1995)-style dynamic models of imperfect competition. We develop a simple algorithm for computing an "oblivious equilibrium," in which each firm is assumed to make decisions based only on its own state and knowledge of the long run average industry state, but where firms ignore current information about competitors' states. We prove that, as the market becomes large, if the equilibrium distribution of firm states obeys a certain "lighttail" condition, then oblivious equilibria closely approximate Markov perfect equilibria. We develop bounds that can be computed to assess the accuracy of the approximation for any given applied problem. Through computational experiments, we find that the method often generates useful approximations for industries with hundreds of firms and in some cases even tens of firms.

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    File URL: http://gsbapps.stanford.edu/researchpapers/library/RP1919R.pdf
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    Paper provided by Stanford University, Graduate School of Business in its series Research Papers with number 1919r.

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    Date of creation: Feb 2007
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    Handle: RePEc:ecl:stabus:1919r
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