Semiconductor industry cycles: Explanatory factors and forecasting

Mathilde Aubry and Patricia Renou-Maissant

Economic Modelling, 2014, vol. 39, issue C, 221-231

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.

Keywords: Univariate and multivariate models; Forecasting accuracy; Industry cycles; Semiconductor industry (search for similar items in EconPapers)
JEL-codes: C53 L63 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecmode:v:39:y:2014:i:c:p:221-231

DOI: 10.1016/j.econmod.2014.02.039

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