Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Cross-Sectional ARDL× | Квантильна АРДЛ× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи | 2006 | 2006 |
| Автор методу≠ | Pesaran and colleagues | Roger Koenker and Zhijie Xiao |
| Тип≠ | Dynamic panel model | Conditional distribution model |
| Основоположне джерело≠ | Pesaran, M. H., & Smith, R. (2016). Testing weak cross-sectional dependence in large panels. Econometric Reviews, 34(6-10), 1089-1117. link ↗ | Koenker, R., & Xiao, Z. (2006). Quantile autoregression. Journal of the American Statistical Association, 101(475), 980-990. DOI ↗ |
| Інші назви | Panel ARDL with cross-sectional dependence | Quantile ARDL |
| Пов'язані | 3 | 3 |
| Підсумок≠ | CS-ARDL (Cross-Sectional ARDL) applies the ARDL framework to panel data while explicitly accounting for cross-sectional dependence—correlation of shocks and relationships across units (countries, firms, regions). Introduced by Pesaran and colleagues (2016), it extends panel ARDL methods to handle common factors or global shocks affecting all units simultaneously. This is crucial for realistic modeling of internationally integrated economies and firm networks. | QARDL (Quantile Autoregressive Distributed Lag) combines quantile regression with ARDL modeling to estimate conditional relationships at different points of the distribution, revealing heterogeneous short-run and long-run effects. Introduced by Koenker and Xiao (2006) and refined by Cho et al. (2015), it captures how the effect of explanatory variables on outcomes varies across quantiles, essential for understanding tail behavior and distributional impacts rather than just mean effects. |
| ScholarGateНабір даних ↗ |
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