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Variance Estimation in a Random Coefficients Model

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Author Info

  • Schlicht, Ekkehart

    ()
    (University of Munich)

  • Ludsteck, Johannes

    ()
    (Institut für Arbeitsmarkt- und Berufsforschung)

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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Bibliographic Info

Paper provided by Institute for the Study of Labor (IZA) in its series IZA Discussion Papers with number 2031.

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Length: 33 pages
Date of creation: Mar 2006
Date of revision:
Handle: RePEc:iza:izadps:dp2031

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Related research

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

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References

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  1. Michael Athans, 1974. "The Importance of Kalman Filtering Methods for Economic Systems," NBER Chapters, National Bureau of Economic Research, Inc, in: Annals of Economic and Social Measurement, Volume 3, number 1, pages 49-64 National Bureau of Economic Research, Inc.
  2. Robert E. Lucas, Jr. & Thomas J. Sargent, 1979. "After Keynesian macroeconomics," Quarterly Review, Federal Reserve Bank of Minneapolis, Federal Reserve Bank of Minneapolis, issue Spr.
  3. 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, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(2), pages 364-71, June.
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Cited by:
  1. Baxa, Jaromír & Horváth, Roman & Vašíček, Bořek, 2013. "Time-varying monetary-policy rules and financial stress: Does financial instability matter for monetary policy?," Journal of Financial Stability, Elsevier, Elsevier, vol. 9(1), pages 117-138.
  2. Schlicht, Ekkehart, 2004. "Estimating the Smoothing Parameter in the So-Called Hodrick-Prescott Filter," IZA Discussion Papers 1054, Institute for the Study of Labor (IZA).
  3. Jaromir Baxa & Roman Horvath & Borek Vasicek, 2010. "How Does Monetary Policy Change? Evidence on Inflation Targeting Countries," Working Papers, Czech National Bank, Research Department 2010/02, Czech National Bank, Research Department.

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