Changing Decision Rules

Uncovering Behavioral Strategies Using Estimation/Classification (EC)
  • Mahmoud A. El-Gamal
  • David M. Grether
Chapter
Part of the Theory and Decision Library book series (TDLB, volume 40)

Abstract

We use the Estimation Classification (EC) estimator first introduced and utilised in El-Gamal and Grether (1995) to study the extent to which individual decision making under uncertainty is shaped by the simplicity of application of various heuristics. In particular, we consider the representativeness heuristic, which figured prominently in earlier empirical results. We study two sets of data from two experiments conducted recently at the University of Wisconsin at Madison, where we employed two designs. One of the designs was used in our previous research and makes the representativeness heuristic readily available to the subjects, whereas the other design does not. In one experimental session, we started with the first design and switched to the second, and in the other session the order of the designs was reversed. We find strong evidence that the ease with which subjects can use the representativeness heuristic influences their tendency to use it. This is evidence for a long-held view in the bounded rationality literature that — other things constant — individuals tend to use heuristics which are more readily available to them.

Keywords

Experimental Session Penalty Function Search Routine Prior Odds Limited Dependent Variable 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Baltagi, B. Econometric Analysis of Panel Data. New York: Wiley. 1995.Google Scholar
  2. Edwards, W. “Conservatism in Human Information Processing”. In Kahneman, D., P. Slovic, and A. Tversky (eds.). Judgement Under Uncertainty: Heuristics and Biases. Cambridge: Cambridge University Press. 1982.Google Scholar
  3. El-Gamal, M. and D. Grether. “Are People Bayesian? Uncovering Behavioral strategies ”. Journal of the American Statistical Association. 1995:90(432).Google Scholar
  4. El-Gamal, M. and D. Grether. “Unknown Heterogeneity, the EC-EM Algorithm, and Large T Approximation”. SSRI working paper #9622, University of Wisconsin at Madison. 1996.Google Scholar
  5. El-Gamal, M. and D. Grether. “A Monte Carlo Study of EC-Estimation in Panel Data Models with Limited Dependent Variables and Heterogeneity”. In Hsiao, C., L-F Lee, K. Lahiri and M. H. Pesaran (eds.). Analysis of Panels and Limited Dependent Variable Models. Cambridge: Cambridge University Press. 1998a.Google Scholar
  6. El-Gamal, M. and D. Grether. “Uncovering Heterogeneity in Behavioral Strategies”. In Ritschard, G., F. Berchtold and D. Zighed (eds.). Apprentissage des Principes Naturels aux Modèles Artificiels. Paris: Hermes. 1998b, 61–72.Google Scholar
  7. Hisao, C. Analysis of Panel Data. Econometric Society Monographs, No. 11. Cambridge: Cambridge University Press. 1986.Google Scholar
  8. Kahneman, D. and A. Tversky. “Subjective Probability: A Judgement of Representativeness”. Cognitive Psychology. 1972: 51.Google Scholar
  9. Tversky, Amos and Daniel Kahnemann. “Rational choice and the framing of decisions”. Journal of Business. 1986: 59.Google Scholar
  10. Wagenaar, W. A., G. Keren and S. Lichtenstein. “Islanders and hostages: Deep and surface structure of decision problems”. Acta Psychologica. 1988: 67.Google Scholar

Copyright information

© Springer Science+Business Media New York 1999

Authors and Affiliations

  • Mahmoud A. El-Gamal
    • 1
  • David M. Grether
    • 2
  1. 1.Rice UniversityUSA
  2. 2.CaltechUSA

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