Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Системный GMM для панельных данных (оценщик Бланделла-Бонда)× | Оценщик метода обобщенных моментов (GMM) по Аррельяно-Бонду× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1998 | 1991 |
| Автор метода≠ | Blundell & Bond (1998); Arellano & Bover (1995) | Manuel Arellano and Stephen Bond |
| Тип | GMM estimator for dynamic panel data | GMM estimator for dynamic panel data |
| 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. Review of Economic Studies, 58(2), 277-297. DOI ↗ |
| Другие названия | System GMM, Blundell-Bond estimator, SYS-GMM, two-step System GMM | AB-GMM, Difference GMM, first-difference GMM, Arellano-Bond estimator |
| Связанные≠ | 6 | 5 |
| Сводка≠ | Panel System GMM is a two-equation GMM estimator for dynamic panel data that stacks the differenced equation (using lagged levels as instruments) with the levels equation (using lagged differences as instruments). Developed by Blundell and Bond (1998) on the foundation of Arellano and Bover (1995), it is the preferred tool when the lagged dependent variable is highly persistent or individual effects are large. | The Arellano-Bond GMM estimator is the standard approach for dynamic panel data models in which the lagged dependent variable appears as a regressor. By first-differencing to remove fixed effects and using deeper lags as instruments, it yields consistent estimates even when the error is serially correlated and regressors are endogenous. |
| ScholarGateНабор данных ↗ |
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