Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Системный ОММ с изменяющимися во времени параметрами× | GMM Арельяно-Бонда с изменяющимися во времени параметрами× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1998 (System GMM); TVP extensions in applied literature thereafter | 1990s-2000s |
| Автор метода≠ | Blundell & Bond (System GMM base); Cooley & Prescott (TVP framework) | Extension of Arellano & Bond (1991); TVP generalisation developed in panel econometrics literature |
| Тип≠ | Dynamic panel estimator with time-varying coefficients | Dynamic panel GMM with time-varying coefficients |
| Основополагающий источник≠ | Blundell, R., & Bond, S. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143. DOI ↗ | 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 ↗ |
| Другие названия | TVP System GMM, time-varying System GMM, TVP-SGMM, dynamic panel TVP estimator | TVP Arellano-Bond GMM, TVP-AB GMM, time-varying coefficient dynamic panel GMM, state-space Arellano-Bond estimator |
| Связанные | 6 | 6 |
| Сводка≠ | Time-Varying Parameter System GMM extends the Blundell-Bond System Generalized Method of Moments estimator to allow regression coefficients to change over time. By combining the instrument-based correction for dynamic endogeneity with a time-varying coefficient structure, the method captures both the persistence of the lagged dependent variable and structural shifts in the effect of regressors across periods. | The time-varying parameter Arellano-Bond GMM (TVP-AB GMM) is a dynamic panel estimator that extends the classic Arellano-Bond difference GMM framework by allowing regression coefficients to evolve over time. It addresses both individual fixed effects and the endogeneity of lagged dependent variables, while accommodating structural change and parameter instability across the sample period. |
| ScholarGateНабор данных ↗ |
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