方法对比
并排查看您选择的方法;存在差异的行会高亮显示。
| 傅里叶面板数据分析× | 面板随机效应模型× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 2006 (Fourier framework); panel extensions 2010s | 1966 |
| 提出者≠ | Becker, Enders, and Lee (Fourier unit root framework); extended to panel data by subsequent applied econometricians | Balestra & Nerlove |
| 类型≠ | Panel regression with Fourier terms | Panel data estimator |
| 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 ↗ | Balestra, P., & Nerlove, M. (1966). Pooling cross section and time series data in the estimation of a dynamic model: The demand for natural gas. Econometrica, 34(3), 585–612. DOI ↗ |
| 别名 | Fourier panel regression, smooth structural break panel model, trigonometric panel data model, Fourier-flexible panel estimator | random effects estimator, RE model, GLS random effects, error components model |
| 相关≠ | 6 | 5 |
| 摘要≠ | 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. | The panel random effects (RE) model treats individual-specific effects as random draws from a population distribution rather than fixed constants, enabling efficient estimation by generalised least squares and allowing inference about time-invariant regressors that are swept away in fixed effects estimation. |
| ScholarGate数据集 ↗ |
|
|