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| Mittelineaarne autoregressiivne distributiivsete viivituste mudel (NARDL)× | Vektorautoregressiooni (VAR) mudel× | |
|---|---|---|
| Valdkond | Ökonomeetria | Ökonomeetria |
| Perekond | Regression model | Regression model |
| Tekkeaasta≠ | 2014 | 2005 |
| Looja≠ | Shin, Yu, and Greenwood-Nimmo | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Tüüp≠ | Nonlinear cointegration model | Multivariate time-series model |
| Algallikas≠ | 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. DOI ↗ | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗ |
| Rööpnimetused | NARDL, nonlinear ARDL, asymmetric ARDL, nonlinear bounds test | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| Seotud | 4 | 4 |
| Kokkuvõte≠ | The Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing an explanatory variable into its positive and negative partial sums, it tests whether increases and decreases in a regressor have different effects on the dependent variable — a feature that linear cointegration methods cannot capture. | Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005). |
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