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| Mundlak-Chamberlain 相关随机效应模型× | Hausman规格检验（固定效应 vs 随机效应）× | 面板数据固定效应模型× | |
|---|---|---|---|
| 领域 | 计量经济学 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model | Regression model |
| 起源年份≠ | 1978 | 1978 | 2014 |
| 提出者≠ | Yair Mundlak; Gary Chamberlain | Jerry A. Hausman | Hsiao (textbook treatment); within transformation of panel data |
| 类型≠ | Panel data estimator | Specification test for panel data models | Panel data regression |
| 开创性文献≠ | Mundlak, Y. (1978). On the pooling of time series and cross section data. Econometrica, 46(1), 69–85. DOI ↗ | Hausman, J. A. (1978). Specification Tests in Econometrics. Econometrica, 46(6), 1251–1271. DOI ↗ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| 别名 | Correlated Random Effects, CRE Estimator, Mundlak Device, Korelasyonlu Rassal Etkiler | Hausman specification test, FE vs RE test, Durbin-Wu-Hausman test, Hausman Spesifikasyon Testi (FE vs RE) | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| 相关≠ | 2 | 5 | 5 |
| 摘要≠ | The Mundlak-Chamberlain correlated random effects (CRE) estimator, introduced by Mundlak (1978) and extended by Chamberlain (1982), is a panel data technique that reconciles the fixed effects and random effects approaches by explicitly modelling the correlation between unobserved individual heterogeneity and the observed regressors. By including within-group means of time-varying covariates as additional regressors in a random effects framework, CRE yields estimates numerically equivalent to the within (fixed effects) estimator while permitting identification of time-invariant variables. | The Hausman test is a specification test, introduced by Jerry A. Hausman in 1978, that decides between the fixed-effects (FE) and random-effects (RE) estimators in panel data models. The null hypothesis is that the random-effects estimator is consistent and efficient and should be preferred; the alternative is that random effects is inconsistent and fixed effects is required because the unit-specific effects are correlated with the explanatory variables. | The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014). |
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