Forecasting and Signal Extraction with Misspecified Models
AbstractThe 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.
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Bibliographic InfoPaper provided by EconWPA in its series Econometrics with number 0401002.
Length: 34 pages
Date of creation: 07 Jan 2004
Date of revision:
Note: Type of Document - ; prepared on WinXP; pages: 34; figures: 9
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Business cycles; Unobserved components models; Cross- validation; Smoothing; Hodrick-Prescott filter; Multistep estimation.;
Other versions of this item:
- Tommaso Proietti, 2005. "Forecasting and signal extraction with misspecified models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 24(8), pages 539-556.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2004-01-12 (All new papers)
- NEP-ECM-2004-01-25 (Econometrics)
- NEP-ETS-2004-01-12 (Econometric Time Series)
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.:
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