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| 傅里叶随机效应模型× | 傅里叶面板数据分析× | |
|---|---|---|
| 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 (Fourier framework); panel extensions 2010s |
| 提出者≠ | Becker, Enders & Lee; Enders & Lee | Becker, Enders, and Lee (Fourier unit root framework); extended to panel data by subsequent applied econometricians |
| 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 ↗ | 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 ↗ |
| 别名 | Fourier RE model, FFF random effects, flexible Fourier random effects, Fourier augmented random effects | Fourier panel regression, smooth structural break panel model, trigonometric panel data model, Fourier-flexible panel estimator |
| 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. | Fourier panel data analysis embeds trigonometric sine and cosine terms into a standard panel regression to approximate smooth, gradual structural shifts in the data-generating process. Rather than assuming a sharp break at a known date, the Fourier approach lets the data reveal the timing and shape of any structural change through a flexible trigonometric approximation, while retaining the cross-sectional and time-series structure of panel data. |
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