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| Fourier VAR-Modell× | Fourier-ARDL-Bounds-Test (Fourier ARDL Bounds Test)× | |
|---|---|---|
| Fachgebiet | Ökonometrie | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 2010s | 2001-2021 |
| Urheber≠ | Enders & Lee; extended by Nazlioglu and others to VAR systems | Pesaran, Shin & Smith (ARDL foundation); Fourier extension by Nazlioglu and related authors |
| Typ≠ | Multivariate time-series model | Cointegration / bounds test |
| Wegweisende Quelle≠ | Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574-599. DOI ↗ | Nazlioglu, S., Gormus, A., & Soytas, U. (2021). Oil prices and monetary policy in emerging markets: structural breaks, asymmetries, and Fourier approximations. Energy Economics, 95, 105119. link ↗ |
| Aliasnamen | Fourier VAR, smooth structural break VAR, trigonometric VAR, Fourier-augmented VAR | Fourier ARDL, Fourier bounds testing, ARDL with Fourier approximation, F-ARDL cointegration test |
| Verwandt≠ | 6 | 5 |
| Zusammenfassung≠ | The Fourier VAR model extends the standard Vector Autoregression by replacing fixed deterministic terms with Fourier trigonometric components, allowing the intercept (and optionally the trend) to shift gradually and smoothly over time. This eliminates the need to pre-specify the number, timing, or shape of structural breaks in a multivariate time-series system. | The Fourier ARDL bounds test augments the Pesaran-Shin-Smith cointegration framework with trigonometric (Fourier) terms that capture gradual, smooth structural breaks in the data-generating process. It tests for a long-run level relationship between variables without requiring the researcher to specify the number, timing, or form of structural breaks in advance. |
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