Accessibility navigation


Forecasting with difference and trend stationary models

Clements, M. ORCID: https://orcid.org/0000-0001-6329-1341 and Hendry, J. (2001) Forecasting with difference and trend stationary models. Econometrics Journal, 4. pp. 1-19. ISSN 1368-423X

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1111/1368-423X.00050

Abstract/Summary

Although difference-stationary (DS) and trend-stationary (TS) processes have been subject to considerable analysis, there are no direct comparisons for each being the data-generation process (DGP). We examine incorrect choice between these models for forecasting for both known and estimated parameters. Three sets of Monte Carlo simulations illustrate the analysis, to evaluate the biases in conventional standard errors when each model is mis-specified, compute the relative mean-square forecast errors of the two models for both DGPs, and investigate autocorrelated errors, so both models can better approximate the converse DGP. The outcomes are surprisingly different from established results.

Item Type:Article
Refereed:Yes
Divisions:Henley Business School > ICMA Centre
ID Code:35197
Uncontrolled Keywords:Forecasting;Trend Stationarity;Difference Stationarity.
Publisher:Wiley

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation