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| 傅里叶-户田-山本格兰杰因果检验× | 格兰杰因果检验× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2019 | 1969 |
| 提出者≠ | Yilanci, Ozgur (building on Toda and Yamamoto 1995; Becker, Enders, and Hurn 2004) | Clive W. J. Granger |
| 类型≠ | Granger causality test | Time-series predictive causality test |
| 开创性文献≠ | Yilanci, V., & Ozgur, O. (2019). Testing the Fourier Toda-Yamamoto causality test with an application to energy demand. Energy Economics, 84, 104498. link ↗ | Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗ |
| 别名 | FTY causality, Fourier TY causality, Toda-Yamamoto causality with Fourier approximation, FTY Granger causality | Granger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi |
| 相关≠ | 3 | 5 |
| 摘要≠ | The Fourier Toda-Yamamoto (FTY) causality test extends the classical Toda-Yamamoto procedure by embedding Fourier trigonometric terms in the augmented VAR to capture smooth, gradual structural breaks in the deterministic component. It retains the key advantage of the Toda-Yamamoto approach — Granger causality can be tested without pre-testing for integration or cointegration order — while dramatically improving size and power when breaks occur. | The Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause. |
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