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Uncovering Time-Varying Parameters with the Kalman-Filter and the Flexible Least Squares: a Monte Carlo Study

  • Zsolt Darvas
  • Balázs Varga

    ()

    (OTP Fund Management and Corvinus University of Budapest)

Using Monte Carlo methods, we compare the ability of the Kalman-filter, the Kalman-smoother and the flexible least squares (FLS) to uncover the parameters of an autoregression. We find that the ordinary least squares (OLS) estimator performs much better that the time-varying coefficient methods when the parameters are in fact constant, but the OLS does very poorly when parameters change. Neither the FLS, nor the Kalman-filter and Kalman-smoother can uncover sudden changes in parameters. But when parameter changes are smoother, such as linear, sinusoid or even random walk changes in the parameters, the FLS with a weight parameter 100 works reasonably well and typically outperforms even the Kalman-smoother, which is in turn performed better than the Kalman-filter.

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File URL: http://web.uni-corvinus.hu/matkg/working_papers/wp_2012_4_darvas_varga.pdf
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Paper provided by Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest in its series Working Papers with number 1204.

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Length: 17 pages
Date of creation: Dec 2012
Date of revision:
Handle: RePEc:mkg:wpaper:1204
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  1. Kalaba, Robert E. & Tesfatsion, Leigh S., 1990. "Flexible Least Squares for Approximately Linear Systems," Staff General Research Papers 11190, Iowa State University, Department of Economics.
  2. Kalaba, Robert E. & Tesfatsion, Leigh S., 1989. "Time-Varying Linear Regression Via Flexible Least Squares," Staff General Research Papers 11196, Iowa State University, Department of Economics.
  3. Kalaba, Robert & Rasakhoo, Nima & Tesfatsion, Leigh, 1989. "A FORTRAN program for time-varying linear regression via flexible least squares," Computational Statistics & Data Analysis, Elsevier, vol. 7(3), pages 291-309, February.
  4. Kalaba, Robert E. & Tesfatsion, Leigh S., 1988. "The Flexible Least Squares Approach to Time-Varying Linear Regression," Staff General Research Papers 11198, Iowa State University, Department of Economics.
  5. Robert Kalaba & Leigh Tesfatsion, 1995. "A Multicriteria Approach to Model Specification and Estimation," Econometrics 9501001, EconWPA.
  6. Giovanni Montana & Kostas Triantafyllopoulos & Theodoros Tsagaris, 2007. "Flexible least squares for temporal data mining and statistical arbitrage," Papers 0709.3884, arXiv.org.
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