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| 문들락-챔버레인 상관 무작위 효과 (Mundlak-Chamberlain Correlated Random Effects)× | 패널 데이터 고정 효과 모형× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 1978 | 2014 |
| 창시자≠ | Yair Mundlak; Gary Chamberlain | Hsiao (textbook treatment); within transformation of panel data |
| 유형≠ | Panel data estimator | Panel data regression |
| 원전≠ | Mundlak, Y. (1978). On the pooling of time series and cross section data. Econometrica, 46(1), 69–85. DOI ↗ | Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗ |
| 별칭 | Correlated Random Effects, CRE Estimator, Mundlak Device, Korelasyonlu Rassal Etkiler | fixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli |
| 관련≠ | 2 | 5 |
| 요약≠ | 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 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). |
| ScholarGate데이터셋 ↗ |
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