Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Модель с фиксированными эффектами панели× | Модель случайных эффектов для панельных данных× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1978 | 1966 |
| Автор метода≠ | Mundlak (1978); classical treatment in Wooldridge (2010) and Baltagi (2021) | Balestra & Nerlove |
| Тип≠ | Panel regression estimator | Panel data estimator |
| Основополагающий источник≠ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 | Balestra, P., & Nerlove, M. (1966). Pooling cross section and time series data in the estimation of a dynamic model: The demand for natural gas. Econometrica, 34(3), 585–612. DOI ↗ |
| Другие названия | within estimator, FE model, within-group estimator, LSDV model | random effects estimator, RE model, GLS random effects, error components model |
| Связанные | 5 | 5 |
| Сводка≠ | The panel fixed effects (FE) model controls for all time-invariant, unit-specific unobserved heterogeneity by absorbing it into individual intercepts. By sweeping out unit means through the within transformation, FE yields unbiased estimates of the effect of time-varying regressors even when omitted unit-level confounders are correlated with those regressors. | The panel random effects (RE) model treats individual-specific effects as random draws from a population distribution rather than fixed constants, enabling efficient estimation by generalised least squares and allowing inference about time-invariant regressors that are swept away in fixed effects estimation. |
| ScholarGateНабор данных ↗ |
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