Reducing the Excess Variability of the Hodrick-Prescott Filter by Flexible Penalization
The Hodrick-Prescott filter is the probably most popular tool for trend estimation in economics. Compared to other frequently used methods like the Baxter-King filter it allows to estimate the trend for the most recent periods of a time series. However, the Hodrick- Prescott filter suffers from an increasing excess variability at the margins of the series inducing a too flexible trend function at the margins compared to the middle. This paper will tackle this problem using spectral analysis and a flexible penalization. It will show that the excess variability can be reduced immensely by a flexible penalization, while the gain function for the middle of the time series is used as a measure to determine the degree of the flexible penalization.
|Date of creation:||Jan 2014|
|Date of revision:|
|Contact details of provider:|| Postal: Ludwigstr. 28, 80539 Munich, Germany|
Web page: http://www.vwl.uni-muenchen.de
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Gebhard Flaig, 2015.
"Why We Should Use High Values for the Smoothing Parameter of the Hodrick-Prescott Filter,"
Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik),
Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 235(6), pages 518-538, November.
- Gebhard Flaig, 2012. "Why We Should Use High Values for the Smoothing Parameter of the Hodrick-Prescott Filter," CESifo Working Paper Series 3816, CESifo Group Munich.
- McElroy, Tucker, 2008. "Matrix Formulas For Nonstationary Arima Signal Extraction," Econometric Theory, Cambridge University Press, vol. 24(04), pages 988-1009, August.
- Marianne Baxter & Robert G. King, 1995.
"Measuring Business Cycles Approximate Band-Pass Filters for Economic Time Series,"
NBER Working Papers
5022, National Bureau of Economic Research, Inc.
- Marianne Baxter & Robert G. King, 1999. "Measuring Business Cycles: Approximate Band-Pass Filters For Economic Time Series," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 575-593, November.
- Danthine, Jean-Pierre & Girardin, Michel, 1989. "Business cycles in Switzerland : A comparative study," European Economic Review, Elsevier, vol. 33(1), pages 31-50, January.
- Stamfort, Stefan, 2005. "Berechnung trendbereinigter Indikatoren für Deutschland mit Hilfe von Filterverfahren," Discussion Paper Series 1: Economic Studies 2005,19, Deutsche Bundesbank, Research Centre.
- Proietti, Tommaso, 2007. "Signal extraction and filtering by linear semiparametric methods," Computational Statistics & Data Analysis, Elsevier, vol. 52(2), pages 935-958, October.
When requesting a correction, please mention this item's handle: RePEc:lmu:muenec:17940. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Tamilla Benkelberg)
If references are entirely missing, you can add them using this form.