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Bayesian Economist... Bayesian agents: An alternative approach to optimal learning

El-Gamal, Mahmoud A. and Sundaram, Rangarajan K. (1993) Bayesian Economist... Bayesian agents: An alternative approach to optimal learning. Journal of Economic Dynamics and Control, 17 . pp. 355-383. ISSN 0165-1889. https://resolver.caltech.edu/CaltechAUTHORS:20171109-135228581

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Abstract

We generalize the results on Bayesian learning based on the martingale convergence theorem to the sequential framework. We show that the variability in the sequential framework is sufficient under mild conditions to circumvent the incomplete learning results that characterize the optimal learning literature. We then give an alternative approach whereby the economist is Bayesian with a prior on the space of agent priors. We illustrate the usefulness of our approach by applying it to two popular economic examples: a monopolist who does not know the demand curve he faces, and the stochastic single-sector growth model with an unknown production function.


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https://doi.org/10.1016/0165-1889(93)90002-ADOIArticle
http://www.sciencedirect.com/science/article/pii/016518899390002APublisherArticle
http://resolver.caltech.edu/CaltechAUTHORS:20170901-161946053Related ItemWorking Paper
Additional Information:© 1993--Elsevier Science Publishers B.V. Received August 1989, final version received February 1992. We wish to thank Larry Blutne, David Easley, Mark Feldman, Nick Kiefer, and participants in the theory workshops of Caltech, the University of Rochester, and Penn State, the fifth conference on the foundations of utility, risk, and uncertainty in Duke, April 1990, and the decision sciences conference in UC Irvin, August 1990, for valuable discussions. The paper also benefited substantially from a referee's suggestions and comments. All remaining errors are of course our own. Formerly SSWP 705.
Record Number:CaltechAUTHORS:20171109-135228581
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Deposited By: Jacquelyn Bussone
Deposited On:16 Nov 2017 23:51
Last Modified:03 Oct 2019 19:02

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