方法对比
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| 稳健随机效应模型× | 稳健面板数据分析× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1980s–2000s | 1987 |
| 提出者≠ | Wooldridge; White (sandwich covariance); Arellano | Arellano (1987); White (1980) heteroscedasticity-consistent framework |
| 类型≠ | Panel GLS estimator with robust inference | Robust estimation / inference correction |
| 开创性文献≠ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 | Arellano, M. (1987). Computing robust standard errors for within-groups estimators. Oxford Bulletin of Economics and Statistics, 49(4), 431–434. link ↗ |
| 别名 | robust RE model, sandwich random effects estimator, cluster-robust random effects, GLS-robust RE | robust panel regression, cluster-robust panel estimation, panel regression with robust standard errors, HC/CR panel estimator |
| 相关≠ | 5 | 6 |
| 摘要≠ | The Robust Random Effects model estimates panel data relationships using the GLS random effects estimator while replacing the conventional standard errors with sandwich (heteroscedasticity- and cluster-robust) variance estimates. This protects inference against arbitrary within-group correlation and heteroscedasticity without discarding the efficiency gains of random effects when unit-specific effects are genuinely uncorrelated with the regressors. | Robust panel data analysis applies standard panel estimators — fixed effects, random effects, or pooled OLS — while replacing conventional standard errors with cluster-robust or heteroscedasticity-consistent (HC) variants. The point estimates remain unchanged; what changes is the variance-covariance matrix used for inference, making t-tests and F-tests valid even when errors are heteroscedastic or correlated within cross-sectional units over time. |
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