2014
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.econmod.2014.02.039
Mathilde Aubry et al., « Semiconductor industry cycles: Explanatory factors and forecasting », HAL-SHS : économie et finance, ID : 10.1016/j.econmod.2014.02.039
This paper aims to suggest the best forecasting model for the semiconductor market. A wide range of alternative modern econometric modeling approaches have been implemented, and a large variety of criteria and tests have been employed to assess the out-of-sample forecasting accuracy at various horizons. The results suggest that if a VECM can be an interesting source of information, the Bayesian models are superior forecasting tools compared to univariate and unrestricted VAR models. However, for decision makers a spectral method could be a useful tool, which can be easily implemented. In addition, MS-AR models make it possible to obtain valuable forecasts on turning-points in order to adjust the programming of heavy capital and research investments.