Learning Within Rational-Expectations Equilibrium
Models of macroeconomic learning are populated by agents who possess a great deal of knowledge of the "true" structure of the economy, and yet ignore the impact of their own learning on that structure; they may learn about an equilibrium, but they do not learn within it.� An alternative learning model is presented where agents' decisions are informed by hypotheses they hold regarding the economy.� They periodically test these hypotheses against observed data, and replace them if they fail.� It is shown that agents who learn in this way spend almost all of the time approximating rational-expectations equilibria.
|Date of creation:||01 Jan 2012|
|Date of revision:|
|Contact details of provider:|| Postal: |
Web page: http://www.economics.ox.ac.uk/
More information through EDIRC
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.:
- Evans, George W. & Honkapohja, Seppo, 1999. "Learning dynamics," Handbook of Macroeconomics, in: J. B. Taylor & M. Woodford (ed.), Handbook of Macroeconomics, edition 1, volume 1, chapter 7, pages 449-542 Elsevier.
- Blume, Lawrence E. & Easley, David, 1982. "Learning to be rational," Journal of Economic Theory, Elsevier, vol. 26(2), pages 340-351, April.
- Sergiu Hart & Andreu Mas-Colell, 2002. "Uncoupled dynamics cannot lead to Nash equilibrium," Discussion Paper Series dp299, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
- John H. Nachbar, 1997.
"Prediction, Optimization, and Learning in Repeated Games,"
Econometric Society, vol. 65(2), pages 275-310, March.
- John H. Nachbar, 1995. "Prediction, Optimization, and Learning in Repeated Games," Game Theory and Information 9504001, EconWPA, revised 14 Feb 1996.
- John Nachbar, 2010. "Prediction, Optimization and Learning in Repeated Games," Levine's Working Paper Archive 576, David K. Levine.
When requesting a correction, please mention this item's handle: RePEc:oxf:wpaper:591. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Caroline Wise)
If references are entirely missing, you can add them using this form.