Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Робастный метод разностей GMM× | Модель с фиксированными эффектами панели× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1991 / 2005 | 1978 |
| Автор метода≠ | Arellano & Bond (1991); robust inference extension via Windmeijer (2005) | Mundlak (1978); classical treatment in Wooldridge (2010) and Baltagi (2021) |
| Тип≠ | GMM estimator with robust standard errors | Panel regression estimator |
| Основополагающий источник≠ | Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277-297. DOI ↗ | Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. ISBN: 978-0262232586 |
| Другие названия | robust Arellano-Bond estimator, difference GMM with robust SE, HAC difference GMM, AB-GMM robust | within estimator, FE model, within-group estimator, LSDV model |
| Связанные≠ | 6 | 5 |
| Сводка≠ | Robust Difference GMM applies the Arellano-Bond first-difference GMM estimator with heteroscedasticity- and autocorrelation-consistent (HAC) or Windmeijer-corrected standard errors, delivering valid inference for dynamic panel models even when error variances are non-constant or residuals are cross-sectionally correlated. | 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. |
| ScholarGateНабор данных ↗ |
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