방법 비교

	구조적 분절 SARIMA 모형	Bai-Perron 다중 구조 변동 검정
분야	계량경제학	계량경제학
계열	Regression model	Hypothesis test
기원 연도	1970s–1998	1998
창시자	Box & Jenkins (SARIMA); Bai & Perron (structural break detection)	Jushan Bai & Pierre Perron
유형	Time series model with regime shifts	Sequential hypothesis test for multiple structural breaks
원전	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.
별칭	SARIMA with structural breaks, break-augmented SARIMA, piecewise SARIMA, SARIMA-SB	Bai-Perron Multiple Break Test, Multiple Structural Change Test, Sequential Structural Break Test, Çoklu Yapısal Kırılma Testi
관련	3	2
요약	The Structural Break SARIMA model extends the classical Seasonal ARIMA framework by explicitly detecting and accommodating abrupt, permanent shifts in the level, trend, or seasonal pattern of a time series. Rather than forcing a single SARIMA specification across the entire sample, the model partitions the series at estimated breakpoints and fits separate SARIMA processes to each resulting segment, producing more accurate forecasts and reliable inference in the presence of regime changes.	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.