방법 비교

	CUSUM 검정: 회귀 모형에서 모수 불안정성 탐지	구조적 변화에 대한 Chow 검정	Quandt-Andrews 검정 (알 수 없는 구조적 변화)
분야	계량경제학	계량경제학	계량경제학
계열	Hypothesis test	Regression model	Hypothesis test
기원 연도	1975	1960	1993
창시자	Brown, Durbin & Evans	Gregory C. Chow	Donald Andrews
유형	Recursive residual test	Test for structural break in regression coefficients	Supremum test for structural change
원전	Brown, R. L., Durbin, J., & Evans, J. M. (1975). Techniques for testing the constancy of regression relationships over time. Journal of the Royal Statistical Society: Series B, 37(2), 149–192.	Chow, G. C. (1960). Tests of equality between sets of coefficients in two linear regressions. Econometrica, 28(3), 591–605.	Andrews, D. W. K. (1993). Tests for parameter instability and structural change with unknown change point. Econometrica, 61(4), 821–856.
별칭	Cumulative Sum Test, CUSUMSQ Test, Brown-Durbin-Evans Test, Kümülatif Toplam Testi	Chow breakpoint test, structural break test, Chow yapısal kırılma testi	sup-Wald Test, Andrews Breakpoint Test, Unknown Structural Break Test, Quandt Likelihood Ratio Test
관련	3	2	3
요약	The CUSUM (Cumulative Sum) and CUSUMSQ (Cumulative Sum of Squares) tests, introduced by Brown, Durbin, and Evans (1975), assess whether the coefficients of a linear regression model remain constant over time. They are standard tools in econometrics for detecting structural breaks, policy shifts, or regime changes in time-series data without requiring prior knowledge of when a break occurs.	The Chow test, introduced by Gregory Chow in 1960, checks whether the coefficients of a linear regression are the same across two subsamples — that is, whether a structural break occurs at a known point such as a policy change, crisis, or regime shift. It compares the fit of a single pooled regression with the combined fit of two separate regressions; a large improvement from splitting indicates the relationship differs between the two periods or groups.	The Quandt-Andrews test, formalized by Andrews (1993), detects structural breaks in regression parameters when the breakpoint date is unknown a priori. It sweeps all candidate break dates within a trimmed interior of the sample, computes a Wald (or LM/LR) statistic at each candidate, and reports the supremum of those statistics. Applied economists and time-series analysts use it to test whether coefficients remain stable across a full estimation window without needing to specify when the break occurred.