Escape Dynamics in Learning Models

Noah Williams

The Review of Economic Studies, 2019, vol. 86, issue 2, 882-912

Abstract: This article illustrates and characterizes how adaptive learning can lead to recurrent large fluctuations. Learning models have typically focused on the convergence of beliefs towards an equilibrium. However in stochastic environments, there may be rare but recurrent episodes where shocks cause beliefs to escape from the equilibrium, generating large movements in observed outcomes. I characterize the escape dynamics by drawing on the theory of large deviations, developing new results which make this theory directly applicable in a class of learning models. The likelihood, frequency, and most likely direction of escapes are all characterized by a deterministic control problem. I illustrate my results with two simple examples.

Keywords: Learning; Dynamics; Fluctuations (search for similar items in EconPapers)
JEL-codes: C62 D83 D84 (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
http://hdl.handle.net/10.1093/restud/rdy033 (application/pdf)
Access to full text is restricted to subscribers.

Related works:
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:86:y:2019:i:2:p:882-912.

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 ().