The convergence of least squares learning in stochastic temporary equilibrium models
Publication Type
Journal Article
Publication Date
11-2002
Abstract
This paper provides conditions for the almost sure convergence of the least squares learning rule in a stochastic temporary equilibrium model, where regressions are performed on the past values of the endogenous state variable. In contrast to earlier studies, (Evans and Honkapohja, 1998; Marcent and Sargent, 1989), which were local analyses, the dynamics are studied from a global viewpoint, which allows one to obtain an almost sure convergence result without employing projection facilities.
Keywords
least squares learning, almost sure convergence
Discipline
Economic Theory
Research Areas
Economic Theory
Publication
Economic Theory
Volume
20
Issue
4
First Page
837
Last Page
847
ISSN
0938-2259
Identifier
10.1007/s00199-001-0237-8
Publisher
Springer Verlag (Germany)
Citation
CHATTERJI, Shurojit.
The convergence of least squares learning in stochastic temporary equilibrium models. (2002). Economic Theory. 20, (4), 837-847.
Available at: https://ink.library.smu.edu.sg/soe_research/1882
Additional URL
https://doi.org/10.1007/s00199-001-0237-8