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| Fourier Nonlinear ARDL (Fourier NARDL)× | Test de Causalité de Granger-Fourier× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 2014–2020s | 2016 |
| Auteur d'origine≠ | Extension of Shin, Yu & Greenwood-Nimmo (2014) NARDL, incorporating Fourier terms from Becker, Enders & Lee (2006) | Enders and Jones |
| Type≠ | Nonlinear cointegrating model with smooth break approximation | Causality test |
| Source fondatrice≠ | Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt (pp. 281–314). Springer. link ↗ | Enders, W., & Jones, P. (2016). Grain prices, oil prices, and multiple smooth breaks in a VAR. Studies in Nonlinear Dynamics and Econometrics, 20(4), 399–419. DOI ↗ |
| Alias | Fourier NARDL, Fourier nonlinear ARDL, F-NARDL, Fourier asymmetric ARDL | Fourier Granger causality test, Enders-Jones Granger causality, smooth structural break Granger test, spectral Granger causality |
| Apparentées | 6 | 6 |
| Résumé≠ | Fourier NARDL extends the Nonlinear ARDL (NARDL) bounds-testing framework by adding Fourier trigonometric terms to the error-correction equation, allowing the model to capture smooth, gradual structural breaks in the long-run relationship without requiring the researcher to know or specify the break date in advance. | The Fourier Granger causality test extends the classic Granger causality framework by embedding low-frequency Fourier terms in the VAR equation, allowing the causal relationship to shift gradually over time without requiring the researcher to pre-specify the number or location of structural breaks. |
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