McKelvey, Richard D. and Page, Talbot (1990) Public and private information: An experimental study of information pooling. Econometrica, 58 (6). pp. 1321-1339. ISSN 0012-9682. https://resolver.caltech.edu/CaltechAUTHORS:20171109-141025874
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Abstract
This paper reports on an experimental study of the way in which individuals make inferences from publicly available information. We compare the predictions of a theoretical model of a common knowledge inference process with actual behavior. In the theoretical model, "perfect Bayesians," starting with private information, take actions; an aggregate statistic is made publicly available; the individuals do optimal Bayesian updating and take new actions; and the process continues until there is a common knowledge equilibrium with complete information pooling. We find that the theoretical model roughly predicts the observed behavior, but the actual inference process is clearly less efficient than the standard of the theoretical model, and while there is some pooling, it is incomplete.
Item Type: | Article | |||||||||
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Additional Information: | © 1990 The Econometric Society. We acknowledge support of NSF Grant No. IST 85-13679 to the California Institute of Technology. We thank Jim Snyder for help with the experiments and data analysis, and Colin Camerer and a referee for useful comments on an earlier draft. The data from the experiments reported here are available on request from the authors. Formerly SSWP 696. | |||||||||
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Subject Keywords: | Information pooling, common knowledge, Bayesian learning | |||||||||
Issue or Number: | 6 | |||||||||
Record Number: | CaltechAUTHORS:20171109-141025874 | |||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20171109-141025874 | |||||||||
Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | |||||||||
ID Code: | 83110 | |||||||||
Collection: | CaltechAUTHORS | |||||||||
Deposited By: | Jacquelyn Bussone | |||||||||
Deposited On: | 16 Nov 2017 23:45 | |||||||||
Last Modified: | 03 Oct 2019 19:02 |
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