Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Dynamic Panel Models in Politics× | Системный ОММ (Арельяно-Бовер / Бланделл-Бонд)× | |
|---|---|---|
| Область≠ | Political Science | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1995 | 1998 |
| Автор метода≠ | Nathaniel Beck & Jonathan Katz; Manuel Arellano & Stephen Bond | Arellano & Bover (1995); Blundell & Bond (1998) |
| Тип≠ | Dynamic regression model for time-series cross-section data | Dynamic panel data estimator |
| Основополагающий источник≠ | Beck, N., & Katz, J. N. (1995). What to Do (and Not to Do) with Time-Series Cross-Section Data. American Political Science Review, 89(3), 634–647. 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 | Dynamic TSCS models, Lagged dependent variable panel models, Time-series cross-section dynamic models, Dynamic time-series cross-section analysis | Arellano-Bover estimator, Blundell-Bond estimator, dynamic panel GMM, Sistem GMM (Arellano-Bover / Blundell-Bond) |
| Связанные | 4 | 4 |
| Сводка≠ | Dynamic panel models for political science analyze time-series cross-section (TSCS) data — repeated observations on countries, dyads, states, or other units over many years — where the outcome today depends on its own past. By including a lagged dependent variable alongside unit fixed effects, these models capture persistence and inertia common in comparative politics and international relations, but doing so introduces the Nickell bias. Estimators such as Arellano-Bond and system GMM, and design choices such as Beck-Katz panel-corrected standard errors, were developed to recover credible dynamic estimates from such data. | System GMM is a generalized method of moments estimator for dynamic panel models that contain a lagged dependent variable. Introduced by Blundell and Bond (1998), building on Arellano and Bover, it augments the differenced equation of the earlier difference GMM (Arellano-Bond) with the equation in levels to deliver consistent estimates when N is large and T is small. |
| ScholarGateНабор данных ↗ |
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