Semiconductor industry cycles: Explanatory factors and forecasting
| Autor: | Mathilde Aubry, Patricia Renou-Maissant |
|---|---|
| Přispěvatelé: | Centre de recherche en économie et management (CREM), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS), Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols (METIS), Université Pierre et Marie Curie - Paris 6 (UPMC)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), EconomiX, Université Paris Nanterre (UPN)-Centre National de la Recherche Scientifique (CNRS), Louise-Rose, Naïla, Université Pierre et Marie Curie - Paris 6 (UPMC)-École Pratique des Hautes Études (EPHE), Normandie Université (NU)-Normandie Université (NU)-Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Pierre et Marie Curie - Paris 6 (UPMC), Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU) |
| Rok vydání: | 2014 |
| Předmět: |
semi- conductor cycle
JEL: C - Mathematical and Quantitative Methods/C.C5 - Econometric Modeling/C.C5.C53 - Forecasting and Prediction Methods • Simulation Methods Economics and Econometrics Univariate and multivariate models semiconductor industry Bayesian probability Univariate [SHS.ECO]Humanities and Social Sciences/Economics and Finance JEL: L - Industrial Organization/L.L6 - Industry Studies: Manufacturing/L.L6.L63 - Microelectronics • Computers • Communications Equipment Variety (cybernetics) Semiconductor industry Econometric model industry cycles Order (exchange) forecasts [No keyword available] forecasting accuracy Range (statistics) Economics Econometrics Probabilistic forecasting [SHS.ECO] Humanities and Social Sciences/Economics and Finance |
| Zdroj: | 31st Annual International Symposium on Forecasting 31st Annual International Symposium on Forecasting, Jun 2011, Prague, Czech Republic Economic Modelling Economic Modelling, 2014, 39, pp.221-231. ⟨10.1016/j.econmod.2014.02.039⟩ Economic Modelling, Elsevier, 2014, 39, pp.221-231 HAL Economic Modelling, Elsevier, 2014, 39, pp.221-231. ⟨10.1016/j.econmod.2014.02.039⟩ |
| ISSN: | 0264-9993 |
| DOI: | 10.1016/j.econmod.2014.02.039 |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
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