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| 面板分位数-分位数回归× | 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≠ | 2015 (QQ); panel applications from ~2018 | 1986-2003 |
| 提出者≠ | Sim and Zhou (cross-section QQ); panel extension in applied energy/finance econometrics | Classical least squares applied to pooled panels; foundational treatment in Hsiao (2003) and Wooldridge (2010) |
| 类型≠ | Nonparametric quantile regression | Linear panel regression |
| 开创性文献≠ | Sim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1-8. DOI ↗ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| 别名 | Panel QQ regression, panel QQ approach, panel quantile-on-quantile approach, PQQ regression | pooled OLS, pooled ordinary least squares, panel least squares, POLS |
| 相关≠ | 6 | 4 |
| 摘要≠ | Panel quantile-on-quantile (QQ) regression jointly maps any quantile of the outcome distribution onto any quantile of the predictor distribution across multiple cross-sectional units observed over time. It generalises Sim and Zhou's (2015) cross-sectional QQ framework to a panel setting, revealing a full dependence surface rather than a single average effect, while accounting for individual heterogeneity through fixed or random effects correction. | 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. |
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