方法对比
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| 傅里叶格兰杰因果检验× | 傅里叶ARDL边界检验× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2016 | 2001-2021 |
| 提出者≠ | Enders and Jones | Pesaran, Shin & Smith (ARDL foundation); Fourier extension by Nazlioglu and related authors |
| 类型≠ | Causality test | Cointegration / bounds test |
| 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 ↗ | 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 ↗ |
| 别名 | Fourier Granger causality test, Enders-Jones Granger causality, smooth structural break Granger test, spectral Granger causality | Fourier ARDL, Fourier bounds testing, ARDL with Fourier approximation, F-ARDL cointegration test |
| 相关≠ | 6 | 5 |
| 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 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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