Salīdzināt metodes

	ARIMA modelis ar strukturālām pārtraukumiem	Bai-Perron daudzkārtējo strukturālo pārtraukumu tests
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Hypothesis test
Izcelsmes gads	1989-1998	1998
Autors	Perron (1989); extended by Bai & Perron (1998)	Jushan Bai & Pierre Perron
Tips	Time series model with regime detection	Sequential hypothesis test for multiple structural breaks
Pirmavots	Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47-78.	Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78.
Citi nosaukumi	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
Saistītās	3	2
Kopsavilkums	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.