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| اختبار جذر الوحدة غير الخطي لـ PP× | نموذج الانحدار الذاتي غير الخطي (NARDL)× | |
|---|---|---|
| المجال | الاقتصاد القياسي | الاقتصاد القياسي |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 1988 (base); 2000s (nonlinear extensions) | 2014 |
| صاحب الطريقة≠ | Phillips & Perron (1988); nonlinear extensions by Kapetanios, Shin & Snell (2003) and related authors | Shin, Yu & Greenwood-Nimmo |
| النوع≠ | Unit root test with nonlinear adjustment | Nonlinear cointegration model |
| المصدر التأسيسي≠ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346. DOI ↗ | Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (pp. 281–314). Springer. link ↗ |
| الأسماء البديلة | Nonlinear PP test, Nonlinear Phillips-Perron test, PP unit root test with nonlinear adjustment, nonlinear PP | NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model |
| ذات صلة≠ | 6 | 5 |
| الملخص≠ | The Nonlinear Phillips-Perron unit root test extends the classic PP test by allowing the adjustment toward equilibrium to follow a nonlinear path — such as a smooth transition or threshold mechanism — rather than assuming a constant linear speed of adjustment. This makes it more powerful when the true data-generating process involves regime-dependent or asymmetric mean-reversion dynamics. | The Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing the regressor into cumulative positive and negative partial sums, it tests whether increases and decreases in a variable exert different effects on the outcome — a feature especially relevant in financial and energy economics where positive and negative shocks rarely cancel out symmetrically. |
| ScholarGateمجموعة البيانات ↗ |
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