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Harmonic Regression Models: A Comparative Review with Applications

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Author Info
Michael Artis
José G. Clavel
Mathias Hoffmann
Dilip Nachane

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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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Publisher Info
Paper provided by Institute for Empirical Research in Economics - IEW in its series IEW - Working Papers with number iewwp333.

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Date of creation: Sep 2007
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Handle: RePEc:zur:iewwpx:333

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

Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation and Testing
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications

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This page was last updated on 2009-11-26.


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