Economic Dynamics with Learning: New Stability Results

George Evans and Seppo Honkapohja

The Review of Economic Studies, 1998, vol. 65, issue 1, 23-44

Abstract: Drawing upon recent contributions in the statistical literature, we present new results on the convergence of recursive, stochastic algorithms which can be applied to economic models with learning and which generalize previous results. The formal results provide probability bounds for convergence which can be used to describe the local stability under learning of rational expectations equilibria in stochastic models. Economic examples include local stability in a multivariate linear model with multiple equilibria and global convergence in a model with a unique equilibrium.

Date: 1998
References: Add references at CitEc
Citations: View citations in EconPapers (71)

Downloads: (external link)
http://hdl.handle.net/10.1111/1467-937X.00034 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Economic Dynamics with Learning: New Stability Results (1996)
Working Paper: Economic Dynamics with Learning: New Stability Results
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:oup:restud:v:65:y:1998:i:1:p:23-44.

Access Statistics for this article

The Review of Economic Studies is currently edited by Thomas Chaney, Xavier d’Haultfoeuille, Andrea Galeotti, Bård Harstad, Nir Jaimovich, Katrine Loken, Elias Papaioannou, Vincent Sterk and Noam Yuchtman

More articles in The Review of Economic Studies from Review of Economic Studies Ltd
Bibliographic data for series maintained by Oxford University Press ().