方法对比
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| 傅里叶普通最小二乘法（傅里叶增强普通最小二乘法）× | 傅里叶格兰杰因果检验× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2004 | 2016 |
| 提出者≠ | Becker, Enders, and Hurn | Enders and Jones |
| 类型≠ | Augmented linear regression | Causality test |
| 开创性文献≠ | Becker, R., Enders, W., & Hurn, S. (2004). A general test for time dependence in parameters. Journal of Applied Econometrics, 19(7), 899–906. DOI ↗ | 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 ↗ |
| 别名 | Fourier OLS, Fourier-augmented OLS, trigonometric OLS, smooth structural break OLS | Fourier Granger causality test, Enders-Jones Granger causality, smooth structural break Granger test, spectral Granger causality |
| 相关 | 6 | 6 |
| 摘要≠ | Fourier OLS is an OLS regression extended by adding low-frequency trigonometric (sine and cosine) terms to the regressor matrix. These Fourier components approximate smooth, gradual structural changes in the regression relationship over time without requiring knowledge of the number, timing, or form of the breaks. | 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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