Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Strukturālā pārtraukuma VAR modelis× | Vektora kļūdu labojuma modelis (VECM)× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1980–1998 | 1987 |
| Autors≠ | Bai & Perron (structural breaks); Sims (VAR framework) | Robert F. Engle and Clive W. J. Granger |
| Tips≠ | Multivariate time series model with regime change | Multivariate time-series model |
| Pirmavots≠ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. 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 | VAR with structural breaks, break-point VAR, regime-switching VAR, SB-VAR | VECM, error correction VAR, cointegrated VAR, vector equilibrium correction model |
| Saistītās≠ | 6 | 5 |
| Kopsavilkums≠ | The Structural Break VAR model extends the standard Vector Autoregression (VAR) framework by allowing coefficient matrices and error covariance to shift at one or more unknown break dates. It is designed for multivariate time series where economic relationships change abruptly due to policy shifts, financial crises, or major structural events. | 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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