Harmonic Regression Models: A Comparative Review with Applications
AbstractStrongly 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 InfoPaper provided by Institute for Empirical Research in Economics - University of Zurich in its series IEW - Working Papers with number 333.
Date of creation: Sep 2007
Date of revision:
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; Dynamic Treatment Effect Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-02-09 (All new papers)
- NEP-ECM-2008-02-09 (Econometrics)
- NEP-FOR-2008-02-09 (Forecasting)
- NEP-ORE-2008-02-09 (Operations Research)
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