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Finite Mixture Analysis of Beauty-Contest Data Using Generalised Beta Distributions

Author

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  • Antoni Bosch-Domènech
  • José García-Montalvo
  • Rosemarie Nagel
  • Albert Satorra

Abstract

This paper introduces a mixture model based on the beta distribution, without preestablished means and variances, to analyze a large set of Beauty-Contest data obtained from diverse groups of experiments (Bosch-Dom`enech et al. 2002). This model gives a better fit of the experimental data, and more precision to the hypothesis that a large proportion of individuals follow a common pattern of reasoning, described as iterated best reply (degenerate), than mixture models based on the normal distribution. The analysis shows that the means of the distributions across the groups of experiments are pretty stable, while the proportions of choices at different levels of reasoning vary across groups.

Suggested Citation

  • Antoni Bosch-Domènech & José García-Montalvo & Rosemarie Nagel & Albert Satorra, 2010. "Finite Mixture Analysis of Beauty-Contest Data Using Generalised Beta Distributions," Working Papers 455, Barcelona Graduate School of Economics.
  • Handle: RePEc:bge:wpaper:455
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    References listed on IDEAS

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    1. Glenn W. Harrison & John A. List, 2004. "Field Experiments," Journal of Economic Literature, American Economic Association, vol. 42(4), pages 1009-1055, December.
    2. McDonald, James B. & Xu, Yexiao J., 1995. "A generalization of the beta distribution with applications," Journal of Econometrics, Elsevier, vol. 66(1-2), pages 133-152.
    3. Antoni Bosch-Domènech & José G. Montalvo & Rosemarie Nagel & Albert Satorra, 2002. "One, Two, (Three), Infinity, ...: Newspaper and Lab Beauty-Contest Experiments," American Economic Review, American Economic Association, vol. 92(5), pages 1687-1701, December.
    4. Peter Arcidiacono & John Bailey Jones, 2003. "Finite Mixture Distributions, Sequential Likelihood and the EM Algorithm," Econometrica, Econometric Society, vol. 71(3), pages 933-946, May.
    5. Andersen, Steffen & Harrison, Glenn W. & Hole, Arne Risa & Rutström, Elisabet E., 2009. "Non-Linear Mixed Logit and the Characterization of Individual Heterogeneity," Working Papers 06-2009, Copenhagen Business School, Department of Economics.
    6. Stahl, Dale O., 1998. "Is step-j thinking an arbitrary modelling restriction or a fact of human nature?," Journal of Economic Behavior & Organization, Elsevier, vol. 37(1), pages 33-51, September.
    7. Nagel, Rosemarie, 1995. "Unraveling in Guessing Games: An Experimental Study," American Economic Review, American Economic Association, vol. 85(5), pages 1313-1326, December.
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    Citations

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    Cited by:

    1. Nagel, Rosemarie & Bühren, Christoph & Frank, Björn, 2017. "Inspired and inspiring: Hervé Moulin and the discovery of the beauty contest game," Mathematical Social Sciences, Elsevier, vol. 90(C), pages 191-207.
    2. Wengström, Erik, 2007. "Setting the Anchor: Price Competition, Level-n Theory and Communication," Working Papers 2007:6, Lund University, Department of Economics.
    3. Mariano Runco, 2015. "Bounded Rationality in a Cournot Duopoly Game," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(2), pages 79-94, November.
    4. Chen, Xiaohong & Ponomareva, Maria & Tamer, Elie, 2014. "Likelihood inference in some finite mixture models," Journal of Econometrics, Elsevier, vol. 182(1), pages 87-99.
    5. Leder, Johannes & Häusser, Jan Alexander & Mojzisch, Andreas, 2015. "Exploring the underpinnings of impaired strategic decision-making under stress," Journal of Economic Psychology, Elsevier, vol. 49(C), pages 133-140.

    More about this item

    Keywords

    Beauty-Contest experiments; decision theory; reasoning hierarchy; finite mixture distribution; beta distribution; EM algorithm;

    JEL classification:

    • C24 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Truncated and Censored Models; Switching Regression Models; Threshold Regression Models
    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior

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