Advanced Search
MyIDEAS: Login to save this paper or follow this series

Harmonic Regression Models: A Comparative Review with Applications

Contents:

Author Info

  • Michael Artis
  • José G. Clavel
  • Mathias Hoffmann
  • Dilip Nachane

Abstract

Strongly periodic series occur frequently in many disciplines. This paper reviews one specific approach to analyzing such series viz. the harmonic regression approach. In this paper the five major methods suggested under this approach are critically reviewed and compared, and their empirical potential highlighted via two applications. The out-of-sample forecast comparisons are made using the Superior Predictive Ability test, which specifically guards against the perils of data snooping. Certain tentative conclusions are drawn regarding the relative forecasting ability of the different methods.

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://www.iew.uzh.ch/wp/iewwp333.pdf
Download Restriction: no

Bibliographic Info

Paper provided by Institute for Empirical Research in Economics - University of Zurich in its series IEW - Working Papers with number 333.

as in new window
Length:
Date of creation: Sep 2007
Date of revision:
Handle: RePEc:zur:iewwpx:333

Contact details of provider:
Postal: Blümlisalpstrasse 10, CH-8006 Zürich
Phone: +41-1-634 22 05
Fax: +41-1-634 49 07
Email:
Web page: http://www.econ.uzh.ch/
More information through EDIRC

Related research

Keywords: Mixed spectrum; autoregressive methods; eigenvalue methods; dynamic harmonic regression; data snooping: multiple forecast comparisons;

Find related papers by JEL classification:

This paper has been announced in the following NEP Reports:

References

No references listed on IDEAS
You can help add them by filling out this form.

Citations

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:zur:iewwpx:333. 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: (Marita Kieser).

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.