Finite mixture analysis of beauty-contest data using generalised beta distributions
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-Domenech et al. 2002). This model gives a better t 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 di erent levels of reasoning vary across groups.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- Rosemarie Nagel & Antoni Bosch-Domènech & Albert Satorra & José García Montalvo, 1999. "One, two, (three), infinity: Newspaper and lab beauty-contest experiments," Economics Working Papers 438, Department of Economics and Business, Universitat Pompeu Fabra.
- Antoni Bosch-Domenech & Jose Garcia-Montalvo & Rosemarie Nagel & Albert Satorra, 2002. "One, two, (three), infinity: Newspaper and lab beauty-contest experiments," Artefactual Field Experiments 00011, The Field Experiments Website.
- Peter Arcidiacono & John Bailey Jones, 2003. "Finite Mixture Distributions, Sequential Likelihood and the EM Algorithm," Econometrica, Econometric Society, vol. 71(3), pages 933-946, 05.
- Arcidiacono, Peter & Jones, John B., 2000. "Finite Mixture Distribution, Sequential Likelihood, and the EM Algorithm," Working Papers 00-16, Duke University, Department of Economics.
- Glenn W. Harrison & John A. List, 2004. "Field Experiments," Journal of Economic Literature, American Economic Association, vol. 42(4), pages 1009-1055, December.
- Glenn Harrison & John List, 2004. "Field experiments," Artefactual Field Experiments 00058, The Field Experiments Website.
- John List & David Reiley, 2008. "Field experiments," Artefactual Field Experiments 00091, The Field Experiments Website.
- Nagel, Rosemarie, 1995. "Unraveling in Guessing Games: An Experimental Study," American Economic Review, American Economic Association, vol. 85(5), pages 1313-1326, December.
- McDonald, James B. & Xu, Yexiao J., 1995. "A generalization of the beta distribution with applications," Journal of Econometrics, Elsevier, vol. 69(2), pages 427-428, October.
- 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.
- 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.
- 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. Full references (including those not matched with items on IDEAS)