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| Bai-Perron 다중 구조 변동 검정× | Quandt-Andrews 검정 (알 수 없는 구조적 변화)× | |
|---|---|---|
| 분야 | 계량경제학 | 계량경제학 |
| 계열 | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 1998 | 1993 |
| 창시자≠ | Jushan Bai & Pierre Perron | Donald Andrews |
| 유형≠ | Sequential hypothesis test for multiple structural breaks | Supremum test for structural change |
| 원전≠ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗ | Andrews, D. W. K. (1993). Tests for parameter instability and structural change with unknown change point. Econometrica, 61(4), 821–856. DOI ↗ |
| 별칭 | Bai-Perron Multiple Break Test, Multiple Structural Change Test, Sequential Structural Break Test, Çoklu Yapısal Kırılma Testi | sup-Wald Test, Andrews Breakpoint Test, Unknown Structural Break Test, Quandt Likelihood Ratio Test |
| 관련≠ | 2 | 3 |
| 요약≠ | 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. | 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. |
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