Forecasting and Signal Extraction with Misspecified Models
The paper illustrates and compares estimation methods alternative to maximum likelihood, among which multistep estimation and leave-one-out cross-validation, for the purposes of signal extraction, and in particular the separation of the trend from the cycle in economic time series, and long-range forecasting, in the presence of a misspecified, but simply parameterised model. Our workhorse models are two popular unobserved components models, namely the local level and the local linear model. The paper introduces a metric for assessing the accuracy of the unobserved components estimates and concludes that cross- validation is not a suitable estimation criterion for the purpose considered, whereas multistep estimation can be valuable. Finally, we propose a local likelihood estimator in the frequency domain that provides a simple and alternative way of making operative the notion of emphasising the long-run properties of a time series.
|Date of creation:||07 Jan 2004|
|Date of revision:|
|Note:||Type of Document - ; prepared on WinXP; pages: 34; figures: 9|
|Contact details of provider:|| Web page: http://econwpa.repec.org|
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.:
- Robert J. Hodrick & Edward Prescott, 1981.
"Post-War U.S. Business Cycles: An Empirical Investigation,"
451, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
- 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.
- Koopman, S.J.M. & Shephard, N. & Doornik, J.A., 1998.
"Statistical Algorithms for Models in State Space Using SsfPack 2.2,"
1998-141, Tilburg University, Center for Economic Research.
- Siem Jan Koopman & Neil Shephard & Jurgen A. Doornik, 1999. "Statistical algorithms for models in state space using SsfPack 2.2," Econometrics Journal, Royal Economic Society, vol. 2(1), pages 107-160.
- Neil Shephard & Jurgen Doornik & Siem Jan Koopman, 1998. "Statistical algorithms for models in state space using SsfPack 2.2," Economics Series Working Papers 1998-W06, University of Oxford, Department of Economics.
- Proietti, Tommaso, 2000.
"Leave-k-out diagnostics in state space models,"
SFB 373 Discussion Papers
2000,74, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
- Proietti, Tommaso & Harvey, Andrew, 2000. "A Beveridge-Nelson smoother," Economics Letters, Elsevier, vol. 67(2), pages 139-146, May.
- Clements, Michael P & Hendry, David F, 1996.
"Multi-step Estimation for Forecasting,"
Oxford Bulletin of Economics and Statistics,
Department of Economics, University of Oxford, vol. 58(4), pages 657-84, November.
- Clements, Michael P. & Hendry, David F., 1996. "Multi-Step Estimation for Forecasting," The Warwick Economics Research Paper Series (TWERPS) 447, University of Warwick, Department of Economics.
When requesting a correction, please mention this item's handle: RePEc:wpa:wuwpem:0401002. 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: (EconWPA)
If references are entirely missing, you can add them using this form.