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Adaptative Learning Models of Consumer Behaviour (first version)

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Author Info
Ed Hopkins ()

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Abstract

This paper applies recent advances in the theory of learning to the analysis of consumer behaviour, in the context of a market with a dominant firm and a competitive fringe. Dynamically optimal pricing for the dominant firm is characterised when consumers learn adaptively about the relative quality of the product. A parallel is drawn between search goods and experience goods and between full and partial information in the context of adaptive learning. In the latter case, if consumers fail to take into account that information is only partial, they can be locked in the habit of purchasing inferior goods. Surprinsingly, however, the dominant firm's price is lower in the search good case. The firm has an incentive to offer lower prices to induce consumers to become locked in. Even if consumers adopt learning rule that leads asymptotically to correct quality of experience goods, if consumers' initial estimate of the dominant firm's quality is high (low), the firm has an incentive to charge above (below) the myopic monopoly price in order to slow (speed up) learning.

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Publisher Info
Paper provided by Edinburgh School of Economics, University of Edinburgh in its series ESE Discussion Papers with number 80.

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Length: 19
Date of creation: Mar 2004
Date of revision:
Handle: RePEc:edn:esedps:80

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  1. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May. [Downloadable!] (restricted)
  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. [Downloadable!] (restricted)
  3. Joel L. Schrag, 1999. "First Impressions Matter: A Model Of Confirmatory Bias," The Quarterly Journal of Economics, MIT Press, vol. 114(1), pages 37-82, February. [Downloadable!] (restricted)
  4. Fernando Vega-Redondo, 1997. "The Evolution of Walrasian Behavior," Econometrica, Econometric Society, vol. 65(2), pages 375-384, March.
  5. Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-81, September. [Downloadable!] (restricted)
  6. Ed Hopkins & Robert M. Seymour, 2002. "The Stability of Price Dispersion under Seller and Consumer Learning," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 43(4), pages 1157-1190, November. [Downloadable!] (restricted)
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  7. Bergemann, Dirk & Valimaki, Juuso, 1996. "Learning and Strategic Pricing," Econometrica, Econometric Society, vol. 64(5), pages 1125-49, September. [Downloadable!] (restricted)
    Other versions:
  8. Arthur, W Brian, 1993. "On Designing Economic Agents That Behave Like Human Agents," Journal of Evolutionary Economics, Springer, vol. 3(1), pages 1-22, February.
  9. Cooper, David J & Garvin, Susan & Kagel, John H, 1997. "Adaptive Learning vs. Equilibrium Refinements in an Entry Limit Pricing Game," Economic Journal, Royal Economic Society, vol. 107(442), pages 553-75, May. [Downloadable!] (restricted)
  10. Tilman Börgers & Rajiv Sarin, . "Naive Reinforcement Learning With Endogenous Aspiration," ELSE working papers 037, ESRC Centre on Economics Learning and Social Evolution. [Downloadable!]
  11. Bagwell, Kyle & Riordan, Michael H, 1991. "High and Declining Prices Signal Product Quality," American Economic Review, American Economic Association, vol. 81(1), pages 224-39, March. [Downloadable!] (restricted)
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  12. Ed Hopkins, 2002. "Two Competing Models of How People Learn in Games," Econometrica, Econometric Society, vol. 70(6), pages 2141-2166, November. [Downloadable!] (restricted)
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  13. Joseph E. Harrington, Jr. & Myong-Hun Chang, 2002. "Co-Evolution of Firms and Consumers and the Implications for Market Dominance," Computing in Economics and Finance 2002 234, Society for Computational Economics.
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  14. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
  15. Sarin, Rajiv & Vahid, Farshid, 1999. "Payoff Assessments without Probabilities: A Simple Dynamic Model of Choice," Games and Economic Behavior, Elsevier, vol. 28(2), pages 294-309, August. [Downloadable!] (restricted)
  16. Borgers, Tilman & Sarin, Rajiv, 2000. "Naive Reinforcement Learning with Endogenous Aspirations," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 41(4), pages 921-50, November.
  17. Schmalensee, Richard, 1992. "Sunk Costs and Market Structure: A Review Article," Journal of Industrial Economics, Blackwell Publishing, vol. 40(2), pages 125-34, June. [Downloadable!] (restricted)
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