Compară metode

	Testul Bai-Perron pentru rupturi structurale multiple	Model SARIMA
Domeniu	Econometrie	Econometrie
Familie	Hypothesis test	Regression model
Anul apariției	1998	1970 (first edition); 1976 (revised)
Autorul original	Jushan Bai & Pierre Perron	Box, Jenkins, and Reinsel
Tip	Sequential hypothesis test for multiple structural breaks	Seasonal time series model
Sursa seminală	Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78.	Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744
Denumiri alternative	Bai-Perron Multiple Break Test, Multiple Structural Change Test, Sequential Structural Break Test, Çoklu Yapısal Kırılma Testi	SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component
Înrudite	2	5
Rezumat	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.	SARIMA extends ARIMA by adding seasonal autoregressive and moving-average operators to capture repeating patterns at fixed intervals — such as monthly, quarterly, or annual cycles. Denoted SARIMA(p,d,q)(P,D,Q)s, it is the standard workhorse for univariate seasonal time series forecasting in econometrics, economics, and official statistics.