Forecasting and signal extraction with misspecified models
Tommaso Proietti
Journal of Forecasting, 2005, vol. 24, issue 8, 539-556
Abstract:
This paper evaluates multistep estimation 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 parameterized 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 multistep estimation can be valuable. However, its performance depends crucially on the properties of the series and the paper explores the role of the order of integration and the relative size of the cyclical variation. On the contrary, cross-validation is usually not suitable for the purposes considered. Copyright © 2005 John Wiley & Sons, Ltd.
Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)
Downloads: (external link)
http://hdl.handle.net/10.1002/for.970 Link to full text; subscription required (text/html)
Related works:
Working Paper: Forecasting and Signal Extraction with Misspecified Models (2004) 
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:jof:jforec:v:24:y:2005:i:8:p:539-556
DOI: 10.1002/for.970
Access Statistics for this article
Journal of Forecasting is currently edited by Derek W. Bunn
More articles in Journal of Forecasting from John Wiley & Sons, Ltd.
Bibliographic data for series maintained by Wiley-Blackwell Digital Licensing () and Christopher F. Baum ().