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| توزيع الأبطاء المقطعي× | نموذج الانحدار الذاتي ذي الفجوات الزمنية الموزعة المقطعي× | |
|---|---|---|
| المجال | الاقتصاد القياسي | الاقتصاد القياسي |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 2001 | 2006 |
| صاحب الطريقة≠ | Pesaran, Shin, and Smith | Pesaran and colleagues |
| النوع≠ | Distributed lag model | Dynamic panel model |
| المصدر التأسيسي≠ | Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships and dynamics. Journal of Applied Econometrics, 16(3), 289-326. DOI ↗ | Pesaran, M. H., & Smith, R. (2016). Testing weak cross-sectional dependence in large panels. Econometric Reviews, 34(6-10), 1089-1117. link ↗ |
| الأسماء البديلة | Panel distributed lag model | Panel ARDL with cross-sectional dependence |
| ذات صلة | 3 | 3 |
| الملخص≠ | CS-DL (Cross-Sectional Distributed Lag) is a simplified dynamic panel model regressing outcomes on current and lagged explanatory variables without explicit autoregressive terms, while accounting for cross-sectional dependence. Built on Pesaran et al. (2001) and extended by Chudik et al. (2014), it estimates dynamic effects more parsimoniously than ARDL when autocorrelated lags are less critical. This approach is valuable for short-horizon effects and policy impact analysis. | 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. |
| ScholarGateمجموعة البيانات ↗ |
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