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Estimation of Constant Gain Learning Models

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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.

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File URL: http://webpages.ursinus.edu/egaus/Research/CGL_GR.pdf
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Bibliographic Info

Paper provided by Ursinus College, Department of Economics in its series Working Papers with number 12-01.

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Length: pages
Date of creation: 12 Aug 2012
Date of revision: 01 Apr 2014
Handle: RePEc:urs:urswps:12-01

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Postal: Ursinus College 601 East Main St. Collegeville, PA 19426
Web page: http://webpages.ursinus.edu/ecba/
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Related research

Keywords: Adaptive Learning; Rational Expectations; MCMC; Bayesian Econometrics;

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  1. Bruce Preston, 2005. "Learning about Monetary Policy Rules when Long-Horizon Expectations Matter," International Journal of Central Banking, International Journal of Central Banking, vol. 1(2), September.
  2. Slobodyan, Sergey & Wouters, Raf, 2012. "Learning in an estimated medium-scale DSGE model," Journal of Economic Dynamics and Control, Elsevier, vol. 36(1), pages 26-46.
  3. Chevillon, Guillaume & Massmann, Michael & Mavroeidis, Sophocles, 2010. "Inference in models with adaptive learning," Journal of Monetary Economics, Elsevier, vol. 57(3), pages 341-351, April.
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