Expectations Of Learning Agents And Stability Of Perfect Foresight Equilibria In Discrete Time Dynamic Economic Models
AbstractWe study the global dynamic properties of stationary equilibria in discrete time deterministic models under bounded rationality. We assume agents' ability to learn from the past performance of their expectations formation mechanism, so that such mechanism itself is made endogenous. We determine sufficient conditions under which this type of error learning behaviour enhances the stability properties of the economic system and rules out non-perfect foresight cycles. This outcome, while partly at odds with some existing results in the economic literature, seems plausible from the point of view of economic intuition.
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2000 with number 218.
Date of creation: 05 Jul 2000
Date of revision:
Contact details of provider:
Postal: CEF 2000, Departament d'Economia i Empresa, Universitat Pompeu Fabra, Ramon Trias Fargas, 25,27, 08005, Barcelona, Spain
Fax: +34 93 542 17 46
Web page: http://enginy.upf.es/SCE/
More information through EDIRC
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Orlando Gomes, 2010. "Ordinary Least Squares Learning And Nonlinearities In Macroeconomics," Journal of Economic Surveys, Wiley Blackwell, vol. 24(1), pages 52-84, 02.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
If references are entirely missing, you can add them using this form.