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Nonlinear Models for Economic Forecasting Applications: An Evolutionary Discussion
This article follows the main contributions brought to the nonlinear modeling literature. We investigate and review a series of parametric initiatives, focusing on the evolution of TAR and ARCH – GARCH model families in econometric and forecasting applications.
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| Published in: | Computational Methods in Social Sciences 2014-01, Vol.2 (1), p.42-47 |
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| Main Authors: | , , |
| Format: | Article |
| Language: | English |
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| container_end_page | 47 |
| container_issue | 1 |
| container_start_page | 42 |
| container_title | Computational Methods in Social Sciences |
| container_volume | 2 |
| creator | Călin, Adrian Cantemir Diaconescu, Tiberiu Popovici, Oana Cristina |
| description | This article follows the main contributions brought to the nonlinear modeling literature. We investigate and review a series of parametric initiatives, focusing on the evolution of TAR and ARCH – GARCH model families in econometric and forecasting applications. |
| format | article |
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| identifier | ISSN: 2344-1232 |
| ispartof | Computational Methods in Social Sciences, 2014-01, Vol.2 (1), p.42-47 |
| issn | 2344-1232 2344-1232 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1692364628 |
| source | Publicly Available Content Database; Social Science Premium Collection (Proquest) (PQ_SDU_P3) |
| subjects | ARCH - GARCH models Arches Computation Economic forecasting Economy Evolution Evolutionary Forecasting Forecasting techniques Mathematical models nonlinear parametric models Nonlinearity Socio-Economic Research Statistical methods Stochastic models threshold models |
| title | Nonlinear Models for Economic Forecasting Applications: An Evolutionary Discussion |
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