Analyzing Strongly Periodic Series in the Frequency Domain: A Comparison of Alternative Approaches with Applications

38 Pages Posted: 5 Jun 2008

See all articles by Michael J. Artis

Michael J. Artis

University of Manchester - Institute for Political & Economic Governance (IPEG)

José G. Clavel

University of Murcia

Mathias Hoffmann

University of Zurich - Department of Economics; CESifo (Center for Economic Studies and Ifo Institute)

Dilip Madhukar Nachane

Indira Gandhi Institute of Development Research (IGIDR)

Date Written: October 2007

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.

Keywords: autoregressive methods, data snooping, dynamic harmonic regression, eigenvalue methods, mixed spectrum, multiple forecast comparisons

JEL Classification: C22, C53

Suggested Citation

Artis, Michael J. and Clavel, José G. and Hoffmann, Mathias and Nachane, Dilip Madhukar, Analyzing Strongly Periodic Series in the Frequency Domain: A Comparison of Alternative Approaches with Applications (October 2007). CEPR Discussion Paper No. DP6517, Available at SSRN: https://ssrn.com/abstract=1140044

Michael J. Artis (Contact Author)

University of Manchester - Institute for Political & Economic Governance (IPEG) ( email )

Oxford Road
Manchester, M13 9PL
United Kingdom

José G. Clavel

University of Murcia ( email )

Avda Teniente Flomesta, 5
Murcia, Murcia 30100
Spain

Mathias Hoffmann

University of Zurich - Department of Economics ( email )

Zuerich, 8006
Switzerland

CESifo (Center for Economic Studies and Ifo Institute)

Poschinger Str. 5
Munich, DE-81679
Germany

Dilip Madhukar Nachane

Indira Gandhi Institute of Development Research (IGIDR) ( email )

Gen A.K. Vaidya Marg Santoshnagar
Goregaon (East)
Mumbai, Maharashtra 400065
India

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