Estimation of Constant Gain Learning Models
AbstractThis 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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Bibliographic InfoPaper provided by Ursinus College, Department of Economics in its series Working Papers with number 12-01.
Date of creation: 12 Aug 2012
Date of revision:
Adaptive Learning; Rational Expectations; MCMC; Bayesian Econometrics;
Find related papers by JEL classification:
- E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
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- Bruce Preston, 2005.
"Learning about Monetary Policy Rules when Long-Horizon Expectations Matter,"
International Journal of Central Banking,
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- Bruce Preston, 2003. "Learning about monetary policy rules when long-horizon expectations matter," Working Paper 2003-18, Federal Reserve Bank of Atlanta.
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- 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.
- Sergey Slobodyan & Raf Wouters, 2009.
"Learning in an Estimated Medium-Scale DSGE Model,"
CERGE-EI Working Papers
wp396, The Center for Economic Research and Graduate Education - Economic Institute, Prague.
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