Comparer des méthodes

	Modèle ARIMA avec rupture structurelle	Test de ruptures structurelles multiples de Bai-Perron
Domaine	Économétrie	Économétrie
Famille	Regression model	Hypothesis test
Année d'origine	1989-1998	1998
Auteur d'origine	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
Source fondatrice	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.
Alias	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
Apparentées	3	2
Résumé	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.