Structural change and the combination of forecasts
Structural change and the combination of forecasts
复制标题
DOI：
10.1002/for.3980060103
复制
发表时间：
1986
期刊：
影响因子：
--
通讯作者：
F. Diebold;Peter Pauly
中科院分区：
文献类型：
--
作者：
F. Diebold;Peter Pauly
Forecasters are generally concerned about the properties of model-based predictions in the presence of structural change. In this paper, it is argued that forecast errors can under those conditions be greatly reduced through systematic combination of forecasts. We propose various extensions of the standard regression-based theory of forecast combination. Rolling weighted least squares and time-varying parameter techniques are shown to be useful generalizations of the basic framework. Numerical examples, based on various types of structural change in the constituent forecasts, indicate that the potential reduction in forecast error variance through these methods is very significant. The adaptive nature of these updating procedures greatly enhances the effect of risk-spreading embodied in standard combination techniques.
