Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Динамическая панельная модель× | Модель с фиксированными эффектами× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1988–1991 | 1971–1978 |
| Автор метода≠ | Arellano & Bond (1991); Holtz-Eakin, Newey & Rosen (1988) | Mundlak (1978); Nerlove (1971); classical panel econometrics |
| Тип≠ | Dynamic regression / GMM estimation | 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 ↗ | Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. ISBN: 978-3030538002 |
| Другие названия | dynamic panel model, panel data model with lagged dependent variable, DPD model, Arellano-Bond model | FE model, within estimator, least squares dummy variable, LSDV regression |
| Связанные | 5 | 5 |
| Сводка≠ | The dynamic panel data model extends standard panel regression by including a lagged value of the outcome variable as a regressor, capturing persistence and adjustment dynamics. Because the lagged dependent variable is correlated with the unit-specific fixed effect, ordinary OLS or within estimators are biased; GMM-based methods using internal instruments are the standard remedy. | The fixed effects (FE) model is the workhorse estimator for panel data when unobserved unit-specific characteristics are suspected to correlate with the regressors. By absorbing each entity's time-invariant heterogeneity into a separate intercept, FE isolates the causal effect of within-unit variation and eliminates omitted-variable bias from time-constant confounders. |
| ScholarGateНабор данных ↗ |
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