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Cycle Extraction: A Comparison of the Phase-Average Trend Method, the Hodrick-Prescott and Christiano-Fitzgerald Filters

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  • Ronny Nilsson
  • Gyorgy Gyomai

Abstract

This paper reports on revision properties of different de-trending and smoothing methods (cycle estimation methods), including PAT with MCD smoothing, a double Hodrick-Prescott (HP) filter and the Christiano-Fitzgerald (CF) filter. The different cycle estimation methods are rated on their revision performance in a simulated real time experiment. Our goal is to find a robust method that gives early turning point signals and steady turning point signals. The revision performance of the methods has been evaluated according to bias, overall revision size and signal stability measures. In a second phase, we investigate if revision performance is improved using stabilizing forecasts or by changing the cycle estimation window from the baseline 6 and 96 months (i.e. filtering out high frequency noise with a cycle length shorter than 6 months and removing trend components with cycle length longer than 96 months) to 12 and 120 months. The results show that, for all tested time series, the PAT de-trending method is outperformed by both the HP or CF filter. In addition, the results indicate that the HP filter outperforms the CF filter in turning point signal stability but has a weaker performance in absolute numerical precision. Short horizon stabilizing forecasts tend to improve revision characteristics of both methods and the changed filter window also delivers more robust turning point estimates. Ce document présente l’impact des révisions dû à différentes méthodes de lissage et de correction de la tendance (méthodes d'estimation du cycle), comme la méthode PAT avec lissage en utilisant le mois de dominance cyclique (MCD), le double filtre de Hodrick-Prescott (HP) et le filtre Christiano-Fitzgerald (CF). Les différentes méthodes d'estimation du cycle sont évaluées sur leur performance de révision faite à partir d’une simulation en temps réel. Notre objectif est de trouver une méthode robuste qui donne des signaux de point de retournement tôt et stable á la fois. La performance de révisions de ces méthodes a été évaluée en fonction du biais, de la grandeur de la révision et de la stabilité du signal. Nous examinerons ensuite si la performance de la révision peut être améliorée en utilisant des prévisions de stabilisation ou en changeant la fenêtre d'estimation du cycle de base de 6 et 96 mois à une fenêtre de 12 et 120 mois. La fenêtre d’estimation de base correspond à un filtre pour éliminer le bruit (hautes fréquences) avec une longueur de cycle de moins de 6 mois et supprimer la tendance avec une longueur de cycle supérieure à 96 mois. Les résultats montrent que, pour toutes les séries testées, la méthode PAT est moins performante que les deux filtres HP ou CF. En outre, les résultats indiquent que le filtre HP surpasse le filtre CF du point de vue de la stabilité du signal du point de retournement mais sa performance est plus faible quant à la précision numérique absolue. Des prévisions à court terme ont la tendance à améliorer les caractéristiques des révisions des deux méthodes et la modification de la fenêtre de base offre aussi des estimations plus robustes des points de retournement.

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Bibliographic Info

Paper provided by OECD Publishing in its series OECD Statistics Working Papers with number 2011/4.

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Date of creation: 27 May 2011
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Handle: RePEc:oec:stdaaa:2011/4-en

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Cited by:
  1. Saša Obradović & Vladimir Mihajlović, 2013. "Synchronization of Business Cycles in the Selected European Countries," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 60(6), pages 759-773, December.

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