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Variance Estimation in a Random Coefficients Model

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  • Schlicht, Ekkehart
  • Ludsteck, Johannes

Abstract

This papers describes an estimator for a standard state-space model with coefficients generated by a random walk that is statistically superior to the Kalman filter as applied to this particular class of models. Two closely related estimators for the variances are introduced: A maximum likelihood estimator and a moments estimator that builds on the idea that some moments are equalized to their expectations. These estimators perform quite similar in many cases. In some cases, however, the moments estimator is preferable both to the proposed likelihood estimator and the Kalman filter, as implemented in the program package Eviews.

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File URL: http://epub.ub.uni-muenchen.de/904/1/schlicht-ludsteck-vcfilter-munich.pdf
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Bibliographic Info

Paper provided by University of Munich, Department of Economics in its series Discussion Papers in Economics with number 904.

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Date of creation: Mar 2006
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Handle: RePEc:lmu:muenec:904

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Related research

Keywords: time-varying coefficients; adaptive estimation; random walk; Kalman filter; state-space model;

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References

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  1. Cooley, Thomas F & Prescott, Edward C, 1973. "An Adaptive Regression Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(2), pages 364-71, June.
  2. Michael Athans, 1974. "The Importance of Kalman Filtering Methods for Economic Systems," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 1, pages 49-64 National Bureau of Economic Research, Inc.
  3. Robert E. Lucas, Jr. & Thomas J. Sargent, 1979. "After Keynesian macroeconomics," Quarterly Review, Federal Reserve Bank of Minneapolis, issue Spr.
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Citations

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Cited by:
  1. Jaromír Baxa & Roman Horváth & Borek Vasícek, 2011. "Monetary Policy Rules and Financial Stress: Does Financial Instability Matter for Monetary," Working Papers wpdea1101, Department of Applied Economics at Universitat Autonoma of Barcelona.
  2. Jaromír Baxa & Roman Horváth & Bořek Vašíček, 2010. "How Does Monetary Policy Change? Evidence on Inflation Targeting Countries," Working Papers IES 2010/26, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Oct 2010.
  3. Schlicht, Ekkehart, 2004. "Estimating the Smoothing Parameter in the So-Called Hodrick-Prescott Filter," Discussion Papers in Economics 304, University of Munich, Department of Economics.

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