Finite Mixture Analysis of Beauty-Contest Data from Multiple Samples
AbstractThis 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by UCLA Department of Economics in its series Levine's Bibliography with number 122247000000000035.
Date of creation: 17 Feb 2004
Date of revision:
Contact details of provider:
Web page: http://www.dklevine.com/
Other versions of this item:
- Antoni Bosch-Dom?nech & Jose Garcia-Montalvo & Rosemarie Nagel & Albert Satorra, 2004. "Finite mixture analysis of beauty-contest data from multiple samples," Artefactual Field Experiments 00013, The Field Experiments Website.
- NEP-ALL-2004-02-23 (All new papers)
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.:
- 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.
- Peter Arcidiacono & John Bailey Jones, 2003.
"Finite Mixture Distributions, Sequential Likelihood and the EM Algorithm,"
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.
- Nagel, Rosemarie, 1995. "Unraveling in Guessing Games: An Experimental Study," American Economic Review, American Economic Association, vol. 85(5), pages 1313-26, December.
- Wengström, Erik, 2007. "Setting the Anchor: Price Competition, Level-n Theory and Communication," Working Papers 2007:6, Lund University, Department of Economics.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (David K. Levine).
If references are entirely missing, you can add them using this form.