Advanced Search
MyIDEAS: Login

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

Contents:

Author Info

  • Zsolt Darvas
  • Balázs Varga

    ()
    (OTP Fund Management and Corvinus University of Budapest)

Abstract

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.

Download Info

If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
File URL: http://web.uni-corvinus.hu/matkg/working_papers/wp_2012_4_darvas_varga.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest in its series Working Papers with number 1204.

as in new window
Length: 17 pages
Date of creation: Dec 2012
Date of revision:
Handle: RePEc:mkg:wpaper:1204

Contact details of provider:
Postal: 1093 Budapest, Fővám tér 8
Phone: +36 1 482-5155
Fax: +36 1 482-5029
Email:
Web page: http://web.uni-corvinus.hu/matkg/
More information through EDIRC

Related research

Keywords: flexible least squares; Kalman-filter; time-varying coefficient models;

Find related papers by JEL classification:

References

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
as in new window
  1. Giovanni Montana & Kostas Triantafyllopoulos & Theodoros Tsagaris, 2007. "Flexible least squares for temporal data mining and statistical arbitrage," Papers 0709.3884, arXiv.org.
  2. 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.
  3. 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.
  4. Robert Kalaba & Leigh Tesfatsion, 1995. "A Multicriteria Approach to Model Specification and Estimation," Econometrics 9501001, EconWPA.
  5. 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.
  6. Kalaba, R. & Rasakhoo, N. & Tesfatsion, L., 1988. "A Fortran Program For Time-Varying Linear Regression Via Flexible Least Squares," Papers m8730, Southern California - Department of Economics.
Full references (including those not matched with items on IDEAS)

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as in new window

Cited by:
  1. Zsuzsanna Zsibók & Balázs Varga, 2012. "Inflation Persistence in Hungary: a Spatial Analysis," Working Papers 1203, Department of Mathematical Economics and Economic Analysis, Corvinus University of Budapest.

Lists

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

Statistics

Access and download statistics

Corrections

When requesting a correction, please mention this item's handle: RePEc:mkg:wpaper:1204. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Balazs Varga).

If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

If references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.

If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.

Please note that corrections may take a couple of weeks to filter through the various RePEc services.