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| 傅里叶随机效应模型× | 傅里叶固定效应模型× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2006-2012 | 2006–2012 |
| 提出者≠ | Becker, Enders & Lee; Enders & Lee | Enders & Lee (building on Becker, Enders & Lee framework) |
| 类型≠ | Panel regression with Fourier approximation | Panel regression with Fourier terms |
| 开创性文献≠ | Becker, R., Enders, W., & Lee, J. (2006). A stationary test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409. DOI ↗ | Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574–599. DOI ↗ |
| 别名 | Fourier RE model, FFF random effects, flexible Fourier random effects, Fourier augmented random effects | Fourier FE model, Fourier panel fixed effects, trigonometric fixed effects regression, smooth structural break fixed effects |
| 相关≠ | 5 | 6 |
| 摘要≠ | The Fourier Random Effects Model extends the standard random effects panel estimator by incorporating trigonometric (Fourier) terms to approximate smooth, gradual structural change in time trends or intercepts. It retains the GLS efficiency advantages of the random effects estimator while allowing parameters to shift continuously over time without requiring knowledge of exact break dates. | The Fourier fixed effects model extends standard panel fixed effects regression by augmenting the specification with low-frequency Fourier (trigonometric) terms. These sine and cosine components approximate unknown, smooth structural shifts in the time trend without requiring the researcher to pre-specify break dates, combining within-unit identification with flexible trend modelling. |
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