Estimation of Constant Gain Learning Models

Eric Gaus and Srikanth Ramamurthy

Working Papers from Ursinus College, Department of Economics

Abstract: This paper provides a concise primer on the estimation of constant gain learning models. One practical concern in the estimation procedure is the initialization of the learning parameters. The popular approach in the literature relies on a training sample to estimate these quantities. We also consider the alternative, that of estimating these alongside the other model parameters. As we show with the aid of both simulated data and real data examples, the estimates are comparable using either approach.

Keywords: Adaptive Learning; Rational Expectations; MCMC; Bayesian Econometrics (search for similar items in EconPapers)
JEL-codes: D83 E52 (search for similar items in EconPapers)
Pages: pages
Date: 2012-08-12, Revised 2014-04-01
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://webpages.ursinus.edu/egaus/Research/CGL_GR.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 500 Can't connect to webpages.ursinus.edu:80 (No such host is known. )

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:urs:urswps:12-01

Access Statistics for this paper

More papers in Working Papers from Ursinus College, Department of Economics Ursinus College 601 East Main St. Collegeville, PA 19426. Contact information at EDIRC.
Bibliographic data for series maintained by Eric Gaus ( this e-mail address is bad, please contact ).