Semiconductor industry cycles: Explanatory factors and forecasting |
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| Institution: | 2. University of Caen Basse Normandie, CREM; Research Department in Economics and Management, 19, rue Claude Bloch 14000 Caen Cedex, France;1. European Patent Office, Controlling Office, Munich, Germany;2. American University, Department of Economics, Washington, D.C., USA;1. Economics Subject Group, University of Hull Business, University of Hull, Cottingham Road, UK;2. Centre for Econometric & Allied Research, University of Ibadan, Nigeria |
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| Abstract: | 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. |
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