方法对比
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| 傅里叶格兰杰因果检验× | 傅里叶增广迪基-富勒单位根检验× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2016 | 2006-2012 |
| 提出者≠ | Enders and Jones | Becker, Enders, and Lee; Enders and Lee |
| 类型≠ | Causality test | Unit root test with smooth structural breaks |
| 开创性文献≠ | 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 ↗ | Becker, R., Enders, W., & Lee, J. (2006). A stationarity test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409. DOI ↗ |
| 别名 | Fourier Granger causality test, Enders-Jones Granger causality, smooth structural break Granger test, spectral Granger causality | Fourier ADF test, FADF test, Flexible Fourier ADF, Fourier-based ADF unit root test |
| 相关 | 6 | 6 |
| 摘要≠ | 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. | The Fourier ADF unit root test extends the standard Augmented Dickey-Fuller framework by incorporating low-frequency Fourier terms into the deterministic component. This allows the test to approximate smooth, gradual structural breaks in the level or trend of a time series without requiring prior knowledge of break number, timing, or form. |
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