方法对比
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| 傅里叶自回归移动平均模型× | 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≠ | 2004–2006 | 2001-2021 |
| 提出者≠ | Becker, Enders, and Hurn | Pesaran, Shin & Smith (ARDL foundation); Fourier extension by Nazlioglu and related authors |
| 类型≠ | Time series model with smooth structural change | Cointegration / bounds test |
| 开创性文献≠ | Becker, R., Enders, W., & Hurn, S. (2006). A general test for time dependence in parameters. Journal of Applied Econometrics, 21(7), 1005–1028. link ↗ | 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 ARMA, ARMA with Fourier terms, trigonometric ARMA, smooth structural change ARMA | Fourier ARDL, Fourier bounds testing, ARDL with Fourier approximation, F-ARDL cointegration test |
| 相关 | 5 | 5 |
| 摘要≠ | The Fourier ARMA model augments the classical Autoregressive Moving Average framework with low-frequency Fourier (sine and cosine) terms to capture smooth, gradual shifts in the mean or trend of a time series. Unlike dummy-variable approaches, it requires no prior knowledge of when structural change occurred, approximating change with flexible trigonometric functions. | 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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