Signal extraction and the formulation of unobserved components models
This paper looks at unobserved components models and examines the implied weighting patterns for signal extraction. There are four main themes. The first concerns the implications of correlated disturbances driving the components, especially those cases in which the correlation is perfect. The second is about the way in which ARIMA-based methods for trend extraction relate to those based on unobserved components. The third explores the impact of heteroscedasticity and irregular spacing and shows how setting up models with t -distributed disturbances leads to weighting patterns which are robust to outliers and breaks. Finally, a comparison is made between implied weighting patterns with kernels used in non-parametric trend estimation and equivalent kernels used in spline smoothing. It is demonstrated that with irregularly spaced data, the weighting used by conventional spline smoothing techniques is not the same as that obtained from the time series model based approach.
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Volume (Year): 3 (2000)
Issue (Month): 1 ()
|Contact details of provider:|| Postal: Office of the Secretary-General, Rm E35, The Bute Building, Westburn Lane, St Andrews, KY16 9TS, UK|
Phone: +44 1334 462479
Web page: http://www.res.org.uk/
More information through EDIRC
|Order Information:||Web: http://www.ectj.org|
References listed on IDEAS
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.:
- repec:oxf:wpaper:1998-w06 is not listed on IDEAS
- Harvey, A C & Jaeger, A, 1993. "Detrending, Stylized Facts and the Business Cycle," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(3), pages 231-247, July-Sept.
- Hodrick, Robert J & Prescott, Edward C, 1997.
"Postwar U.S. Business Cycles: An Empirical Investigation,"
Journal of Money, Credit and Banking,
Blackwell Publishing, vol. 29(1), pages 1-16, February.
- Robert J. Hodrick & Edward Prescott, 1981. "Post-War U.S. Business Cycles: An Empirical Investigation," Discussion Papers 451, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- Edward C. Prescott, 1982. "FORTRAN code for the Hodrick-Prescott filter," QM&RBC Codes 3, Quantitative Macroeconomics & Real Business Cycles.
- Kurt Annen, 2004. "Matlab functions for HP-filter," QM&RBC Codes 166, Quantitative Macroeconomics & Real Business Cycles.
- Christian Zimmermann, 2005. "HP-Filter code (Perl)," QM&RBC Codes 98, Quantitative Macroeconomics & Real Business Cycles.
- Morten Ravn, "undated". "GAUSS program for Hodrick-Prescott filter," QM&RBC Codes 101, Quantitative Macroeconomics & Real Business Cycles.
- Christian Zimmermann, 2005. "HP-Filter (web interface)," QM&RBC Codes 97, Quantitative Macroeconomics & Real Business Cycles.
- Kurt Annen, 2006. "HP-Filter Excel Add-In," QM&RBC Codes 165, Quantitative Macroeconomics & Real Business Cycles.
- Ivailo Izvorski, "undated". "MATLAB code for the Hodrick-Prescott filter," QM&RBC Codes 1, Quantitative Macroeconomics & Real Business Cycles.
- Morten Ravn, "undated". "Alternate GAUSS program for the Hodrick-Prescott Filter," QM&RBC Codes 102, Quantitative Macroeconomics & Real Business Cycles.
- Ken Matheny & Simon van Norden & Robert Vigfusson, 1989. "GAUSS code for the Hodrick-Prescott filter," QM&RBC Codes 2, Quantitative Macroeconomics & Real Business Cycles, revised Apr 1995.
- Kurt Annen, 2006. "HP-Filter DLL executable," QM&RBC Codes 167, Quantitative Macroeconomics & Real Business Cycles.
- Kurt Annen, 2004. "HP-filter for Java," QM&RBC Codes 168, Quantitative Macroeconomics & Real Business Cycles.
- Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999.
"Statistical algorithms for models in state space using SsfPack 2.2,"
Royal Economic Society, vol. 2(1), pages 107-160.
- Koopman, S.J.M. & Shephard, N. & Doornik, J.A., 1998. "Statistical Algorithms for Models in State Space Using SsfPack 2.2," Discussion Paper 1998-141, Tilburg University, Center for Economic Research.
- I. Gijbels & A. Pope & M. P. Wand, 1999. "Understanding exponential smoothing via kernel regression," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 61(1), pages 39-50.
- Watson, Mark W., 1986. "Univariate detrending methods with stochastic trends," Journal of Monetary Economics, Elsevier, vol. 18(1), pages 49-75, July.
- Sandmann, Gleb & Koopman, Siem Jan, 1998. "Estimation of stochastic volatility models via Monte Carlo maximum likelihood," Journal of Econometrics, Elsevier, vol. 87(2), pages 271-301, September.
When requesting a correction, please mention this item's handle: RePEc:ect:emjrnl:v:3:y:2000:i:1:p:84-107. 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: (Wiley-Blackwell Digital Licensing)or (Christopher F. Baum)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.