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Price Dispersion: An Evolutionary Approach

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  • Ed Hopkins

Abstract

In many markets it is possible to find rival sellers charging different prices for the same good. Earlier research has explained this phenomenon by demon-strating the existence of dispersed price equilibria when consumers must make use of costly search to discover prices. Taking as a starting point the model of Burdett and Judd (Econometric, 1983), this paper, extending evolutionary techniques to a game with nonlinear payoffs and a continuum of strategies, reexamines the question of price dispersion from an evolutionary, disequilibrium perspective. That is, firms and consumers adjust behaviour adaptively in response to current market conditions. We find that dispersed price equilibria are unstable when consumers use a fixed sample size search rule but may be stable when a reservation price rule is used.
(This abstract was borrowed from another version of this item.)
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Ed Hopkins, "undated". "Price Dispersion: An Evolutionary Approach," Discussion Papers 1996-3, Edinburgh School of Economics, University of Edinburgh.
  • Handle: RePEc:edn:ediedp:1996-3
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    References listed on IDEAS

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    1. Rothschild, Michael, 1974. "Searching for the Lowest Price When the Distribution of Prices Is Unknown," Journal of Political Economy, University of Chicago Press, vol. 82(4), pages 689-711, July/Aug..
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    3. Rothschild, Michael, 1973. "Models of Market Organization with Imperfect Information: A Survey," Journal of Political Economy, University of Chicago Press, vol. 81(6), pages 1283-1308, Nov.-Dec..
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    7. Hopkins, Ed, 1999. "Learning, Matching, and Aggregation," Games and Economic Behavior, Elsevier, vol. 26(1), pages 79-110, January.
    8. Diamond, Peter A., 1971. "A model of price adjustment," Journal of Economic Theory, Elsevier, vol. 3(2), pages 156-168, June.
    9. Benabou Roland, 1993. "Search Market Equilibrium, Bilateral Heterogeneity, and Repeat Purchases," Journal of Economic Theory, Elsevier, vol. 60(1), pages 140-158, June.
    10. Kandori, Michihiro & Mailath, George J & Rob, Rafael, 1993. "Learning, Mutation, and Long Run Equilibria in Games," Econometrica, Econometric Society, vol. 61(1), pages 29-56, January.
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    13. Helmut Bester, 1988. "Bargaining, Search Costs and Equilibrium Price Distributions," Review of Economic Studies, Oxford University Press, vol. 55(2), pages 201-214.
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    18. Harrison, Glenn W & Morgan, Peter, 1990. "Search Intensity in Experiments," Economic Journal, Royal Economic Society, vol. 100(401), pages 478-486, June.
    19. Talmain, Gabriel, 1992. "Search from an unkown distribution an explicit solution," Journal of Economic Theory, Elsevier, vol. 57(1), pages 141-157.
    20. Nachbar, J H, 1990. ""Evolutionary" Selection Dynamics in Games: Convergence and Limit Properties," International Journal of Game Theory, Springer;Game Theory Society, vol. 19(1), pages 59-89.
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    22. Wilde, Louis L. & Schwartz, Alan., "undated". "Equilibrium Comparison Shopping," Working Papers 184, California Institute of Technology, Division of the Humanities and Social Sciences.
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    Cited by:

    1. Hopkins, Ed, 1999. "A Note on Best Response Dynamics," Games and Economic Behavior, Elsevier, vol. 29(1-2), pages 138-150, October.
    2. Kirman, Alan P. & Vriend, Nicolaas J., 2001. "Evolving market structure: An ACE model of price dispersion and loyalty," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 459-502, March.

    More about this item

    JEL classification:

    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C83 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Survey Methods; Sampling Methods

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