Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| Structurele Breuk ARIMA Model× | Bai-Perron-test voor Meervoudige Structurele Breuken× | |
|---|---|---|
| Vakgebied | Econometrie | Econometrie |
| Familie≠ | Regression model | Hypothesis test |
| Jaar van ontstaan≠ | 1989-1998 | 1998 |
| Grondlegger≠ | Perron (1989); extended by Bai & Perron (1998) | Jushan Bai & Pierre Perron |
| Type≠ | Time series model with regime detection | Sequential hypothesis test for multiple structural breaks |
| Oorspronkelijke bron≠ | 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 ↗ |
| Aliassen | ARIMA with structural breaks, break-adjusted ARIMA, piecewise ARIMA, ARIMA with regime shifts | Bai-Perron Multiple Break Test, Multiple Structural Change Test, Sequential Structural Break Test, Çoklu Yapısal Kırılma Testi |
| Verwant≠ | 3 | 2 |
| Samenvatting≠ | 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. | The Bai-Perron test, introduced by Jushan Bai and Pierre Perron in their landmark 1998 Econometrica paper, is a least-squares-based procedure for detecting, estimating, and testing the number of structural breaks in a linear regression model estimated on time-series data. Unlike single-break tests, it simultaneously identifies multiple change-points in a sample, providing economists and empirical researchers with a rigorous, data-driven way to locate parameter instability across time. |
| ScholarGateGegevensset ↗ |
|
|