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Discussion Paper Details

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

Author(s): Michael J Artis, Jose Garcia Clavel, Mathias Hoffmann and Dilip M Nachane

Publication Date: October 2007

Keyword(s): autoregressive methods, data snooping, dynamic harmonic regression, eigenvalue methods, mixed spectrum and multiple forecast comparisons

Programme Area(s): International Macroeconomics

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.

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Bibliographic Reference

Artis, M, Clavel, J, Hoffmann, M and Nachane, D. 2007. 'Analyzing Strongly Periodic Series in the Frequency Domain: A Comparison of Alternative Approaches with Applications'. London, Centre for Economic Policy Research. https://cepr.org/active/publications/discussion_papers/dp.php?dpno=6517