Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Structural Break NARDL× | Vektora kļūdu labojuma modelis (VECM)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2014–2018 | 1987 |
| Autors≠ | Shin, Yu & Greenwood-Nimmo (NARDL base); structural break extensions by subsequent applied researchers | Robert F. Engle and Clive W. J. Granger |
| Tips≠ | Nonlinear cointegration with structural breaks | Multivariate time-series model |
| Pirmavots≠ | Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In W. C. Horrace & R. C. Sickles (Eds.), Festschrift in Honor of Peter Schmidt (pp. 281–314). Springer. DOI ↗ | Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗ |
| Citi nosaukumi | SB-NARDL, NARDL with structural breaks, nonlinear ARDL with break, asymmetric ARDL structural break | VECM, error correction VAR, cointegrated VAR, vector equilibrium correction model |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | Structural Break NARDL extends the Nonlinear Autoregressive Distributed Lag (NARDL) bounds-testing framework by explicitly accommodating one or more structural breaks in the long-run relationship. It separates positive and negative changes in the regressor, tests for cointegration, and allows regime shifts, providing a richer picture of asymmetric and break-sensitive dynamics between variables. | The Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series. |
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