Break Detectability and Mean Square Forecast Error Ratios for Selecting Estimation Windows
Article first published online: 21 JUL 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Journal of Forecasting
Volume 31, Issue 8, pages 688–705, December 2012
How to Cite
Ahumada, H. A. (2012), Break Detectability and Mean Square Forecast Error Ratios for Selecting Estimation Windows. J. Forecast., 31: 688–705. doi: 10.1002/for.1240
- Issue published online: 18 OCT 2012
- Article first published online: 21 JUL 2011
- Manuscript Accepted: 11 MAY 2011
- Manuscript Revised: 27 OCT 2010
- Manuscript Received: 14 OCT 2009
- mean square forecast error ratios;
- estimation windows
It has been suggested that a major problem for window selection when we estimate models for forecasting is to empirically determine the timing of the break. However, if the window choice between post-break or full sample is based on mean square forecast error ratios, it is difficult to understand why such a problem arises since break detectability and these ratios seem to have the same determinants. This paper analyses this issue first for the expected values in conditional models and then by Monte Carlo simulations for more general cases. Results show similar behaviour between rejection frequencies and the ratios but only for break tests that do not take into account forecasting error covariances, as is the case with mean square forecast error measures. Moreover, the asymmetric shape of the frequency distribution of the ratios could help us to better grasp empirical problems. An illustration using actual data is given. Copyright © 2011 John Wiley & Sons, Ltd.