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。
| 面板数据分析× | 面板普通最小二乘法（汇总普通最小二乘法）× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1966–1978 | 1986-2003 |
| 提出者≠ | Balestra & Nerlove (1966); Mundlak (1978); Hausman (1978) | Classical least squares applied to pooled panels; foundational treatment in Hsiao (2003) and Wooldridge (2010) |
| 类型≠ | Panel regression framework | Linear panel regression |
| 开创性文献≠ | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. ISBN: 978-3030539528 | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| 别名 | longitudinal data analysis, pooled cross-sectional time-series analysis, panel regression, data panel analysis | pooled OLS, pooled ordinary least squares, panel least squares, POLS |
| 相关≠ | 5 | 4 |
| 摘要≠ | Panel data analysis models data that track multiple units — countries, firms, individuals — over time, enabling researchers to control for unobserved unit-level heterogeneity that would otherwise bias cross-sectional or time-series estimates. The two core specifications are fixed effects and random effects, selected via the Hausman test. | Panel OLS — also called Pooled OLS — applies the classical ordinary least squares estimator to panel data by stacking all cross-sectional units and time periods into a single sample. It estimates one common set of slope coefficients under the assumption that the intercept and slopes are homogeneous across units and time. |
| ScholarGate数据集 ↗ |
|
|