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Finite Mixture Analysis of Beauty-Contest Data from Multiple Samples

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Author Info

  • Antoni Bosch-Domenech
  • Jose G. Montalvo
  • Rosemarie Nagel
  • Albert Satorra

Abstract

This paper develops a finite mixture distribution analysis of Beauty-Contest data obtained from diverse groups of experiments. ML estimation using the EM approach provides estimates for the means and variances of the component distributions, which are common to all the groups, and estimates of the mixing proportions, which are specific to each group. This estimation is performed without imposing constraints on the parameters of the composing distributions. The statistical analysis indicates that many individuals follow a common pattern of reasoning described as iterated best reply (degenerate), and shows that the proportions of people thinking at different levels of depth vary across groups.

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Bibliographic Info

Paper provided by UCLA Department of Economics in its series Levine's Bibliography with number 122247000000000035.

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Date of creation: 17 Feb 2004
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Handle: RePEc:cla:levrem:122247000000000035

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  1. Hamparsum Bozdogan, 1987. "Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions," Psychometrika, Springer, vol. 52(3), pages 345-370, September.
  2. Arcidiacono, Peter & Jones, John B., 2000. "Finite Mixture Distribution, Sequential Likelihood, and the EM Algorithm," Working Papers 00-16, Duke University, Department of Economics.
  3. Nagel, Rosemarie, 1995. "Unraveling in Guessing Games: An Experimental Study," American Economic Review, American Economic Association, vol. 85(5), pages 1313-26, December.
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Cited by:
  1. Wengström, Erik, 2007. "Setting the Anchor: Price Competition, Level-n Theory and Communication," Working Papers 2007:6, Lund University, Department of Economics.

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