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随机效应面板模型×面板数据的混合普通最小二乘法×
领域计量经济学计量经济学
方法族Regression modelRegression model
起源年份19782010
提出者Baltagi (textbook treatment); Hausman specification testJeffrey Wooldridge (treatment)
类型Panel data regressionLinear regression on stacked panel observations
开创性文献Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251-1271. DOI ↗Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0-262-23258-8
别名random effects panel regression, RE estimator, GLS panel estimator, Panel Rassal Etkiler ModeliPooled OLS, Pooled Ordinary Least Squares, Simple Panel OLS, Havuzlanmış EKK
相关52
摘要The random effects model is a panel data estimator that explains an outcome using both within-unit and between-unit variation, treating the unobserved unit-specific heterogeneity as a random, normally distributed term rather than a fixed parameter. Its validity is judged with the Hausman (1978) specification test, and it is developed in standard treatments such as Baltagi's Econometric Analysis of Panel Data.Pooled OLS applies standard ordinary least squares to panel data by stacking all cross-sectional and time observations into a single dataset and ignoring the panel structure during estimation. It is the most transparent starting point for panel data analysis, widely used in economics, finance, and social sciences when researchers wish to estimate average partial effects across individuals and time periods without imposing strong distributional assumptions about unobserved heterogeneity.
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ScholarGate方法对比: Random Effects Panel Model · Pooled OLS. 于 2026-06-17 检索自 https://scholargate.app/zh/compare