Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Панельная авторегрессионная (Panel AR) модель× | Динамическая панельная модель× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1980s-2000s | 1991–1998 |
| Автор метода≠ | Hsiao, C.; Arellano, M. | Arellano & Bond (1991); Blundell & Bond (1998) |
| Тип≠ | Autoregressive time-series model for panel data | Dynamic panel regression |
| Основополагающий источник≠ | Hsiao, C. (2003). Analysis of Panel Data (2nd ed.). Cambridge University Press. ISBN: 978-0521522717 | 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 | panel autoregressive model, PAR model, AR model for panel data, panel AR(p) | dynamic panel model, lagged dependent variable panel model, Arellano-Bond type dynamic panel, GMM dynamic panel |
| Связанные | 5 | 5 |
| Сводка≠ | The Panel AR model extends the classical univariate autoregressive model to panel data, capturing how each unit's own past values predict its current value while controlling for unobserved individual heterogeneity through fixed or random effects. It is foundational for modelling dynamic persistence in micro or macro panel datasets. | 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. |
| ScholarGateНабор данных ↗ |
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