Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Тест Квандта-Ендрюса на наявність невідомих структурних зламів× | Тест Бая-Перрона на множинні структурні злами× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Hypothesis test | Hypothesis test |
| Рік появи≠ | 1993 | 1998 |
| Автор методу≠ | Donald Andrews | Jushan Bai & Pierre Perron |
| Тип≠ | Supremum test for structural change | Sequential hypothesis test for multiple structural breaks |
| Основоположне джерело≠ | Andrews, D. W. K. (1993). Tests for parameter instability and structural change with unknown change point. Econometrica, 61(4), 821–856. DOI ↗ | Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗ |
| Інші назви | sup-Wald Test, Andrews Breakpoint Test, Unknown Structural Break Test, Quandt Likelihood Ratio Test | Bai-Perron Multiple Break Test, Multiple Structural Change Test, Sequential Structural Break Test, Çoklu Yapısal Kırılma Testi |
| Пов'язані≠ | 3 | 2 |
| Підсумок≠ | 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. | 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. |
| ScholarGateНабір даних ↗ |
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