Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Динамическая панельная модель× | Модель с фиксированными эффектами панели× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1991–1998 | 1978 |
| Автор метода≠ | Arellano & Bond (1991); Blundell & Bond (1998) | Mundlak (1978); classical treatment in Wooldridge (2010) and Baltagi (2021) |
| Тип≠ | Dynamic panel regression | 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. 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 | dynamic panel model, lagged dependent variable panel model, Arellano-Bond type dynamic panel, GMM dynamic panel | within estimator, FE model, within-group estimator, LSDV model |
| Связанные | 5 | 5 |
| Сводка≠ | The dynamic panel data model extends standard panel regression by including one or more lagged values of the outcome variable as regressors. Because past outcomes directly predict current outcomes, the model captures persistence and adjustment dynamics — but it also introduces a correlation between the lagged dependent variable and the individual fixed effect, rendering OLS and standard fixed-effects estimators inconsistent. GMM-based approaches developed by Arellano-Bond and Blundell-Bond resolve this problem. | 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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