Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Strukturālā pārtraukuma VAR modelis× | ARIMA modelis ar strukturālām pārtraukumiem× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1980–1998 | 1989-1998 |
| Autors≠ | Bai & Perron (structural breaks); Sims (VAR framework) | Perron (1989); extended by Bai & Perron (1998) |
| Tips≠ | Multivariate time series model with regime change | Time series model with regime detection |
| Pirmavots≠ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47-78. DOI ↗ |
| Citi nosaukumi | VAR with structural breaks, break-point VAR, regime-switching VAR, SB-VAR | ARIMA with structural breaks, break-adjusted ARIMA, piecewise ARIMA, ARIMA with regime shifts |
| Saistītās≠ | 6 | 3 |
| 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. | A structural break ARIMA model extends the standard ARIMA framework by explicitly identifying and accommodating one or more abrupt shifts in the level, trend, or dynamics of a time series. Rather than forcing a single set of ARIMA parameters across the entire sample, it fits separate ARIMA specifications for each regime defined by the detected break dates. |
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