Market Failure Caused by Quality Uncertainty

  • Segismundo S. Izquierdo
  • Luis R. Izquierdo
  • José M. Galán
  • Cesáreo Hernández
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 564)

Summary

The classical argument used to explain why markets can fail when there is product quality variability (e.g. the used car market) relies heavily on the presence of asymmetric information —i.e. there must exist some reliable quality indicators that can be observed by sellers, but not by buyers. Using computer simulation, this paper illustrates how such market failures can occur even in the absence of asymmetric information. The mere assumption that buyers estimate the quality of the product they buy using their past experience in previous purchases is enough to observe prices drop, market efficiency losses, and systematic underestimation of actual product quality. This alternative explanation is shown to be valid for a very wide range of learning rules and in various market contexts.

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References

  1. Akerlof G A (1970) The Market for Lemons: Quality Uncertainty and the Market Mechanism. Quarterly Journal of Economics 84: 488–500CrossRefGoogle Scholar
  2. Axelrod R (1997) The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration. Princeton: Princeton University Press.Google Scholar
  3. Bergstrom T (2003) Vernon Smith’s Insomnia and the Dawn of Economics as Experimental Science. Scandinavian Journal of Economics 105: 181–205CrossRefGoogle Scholar
  4. Cliff D, Bruten J (1997) Minimal-intelligence agents for bargaining behaviours in market environments. Hewlett-Packard Laboratories Technical Report HPL-97-91Google Scholar
  5. Das R, Hanson JE, Kephart JO, Tesauro G (2001) Agent-Human Interactions in the Continuous Double Auction. Proceedings of the International Joint Conferences on Artificial Intelligence (IJCAI-O1)Google Scholar
  6. Duffy J (2005) Agent-Based Models and Human Subject Experiments. To appear in: Handbook of Computational Economics, vol 2. Elsevier, AmsterdamGoogle Scholar
  7. Duffy J, Unver MU (2006, forthcoming) Asset Price Bubbles and Crashes With Near Zero-Intelligence Traders. Economic Theory 27: 537–563CrossRefGoogle Scholar
  8. Gode D K, Sunder S (1993) Allocative Efficiency of Markets with Zero-Intelligence Traders: Markets as a Partial Substitute for Individual Rationality. Journal of Political Economy 101: 119–137CrossRefGoogle Scholar
  9. The Royal Swedish Academy of Sciences (2001) Advanced information on the 2001 Bank of Sweden Prize in Economic Sciences in Memory of Alfred Nobel. Available at http://nobelprize.org/economics/laureates/2001/ecoadv.pdf on May 20th 2005.Google Scholar
  10. Smith V L (1962) An Experimental Study of Competitive Market behavior. Journal of Political Economy 70: 111–137CrossRefGoogle Scholar
  11. Vriend N (2000) An Illustration of the Essential Difference Between Individual and Social Learning, and its Consequence for Computational Analyses. Journal of Economic Dynamics and Control 24: 1–19MATHMathSciNetCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Segismundo S. Izquierdo
    • 1
  • Luis R. Izquierdo
    • 2
  • José M. Galán
    • 3
  • Cesáreo Hernández
    • 1
  1. 1.University of ValladolidSpain
  2. 2.The Macaulay InstituteAberdeenUK
  3. 3.University of BurgosSpain

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