Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Тест Грегори-Хансена на коинтеграцию с изменением режима× | Тест на единичный корень Живота-Эндрюса с одним структурным разрывом× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Hypothesis test | Hypothesis test |
| Год появления≠ | 1996 | 1992 |
| Автор метода≠ | Allan Gregory & Bruce Hansen | Eric Zivot & Donald Andrews |
| Тип≠ | Residual-based structural break cointegration test | Sequential unit-root test with endogenous break-point selection |
| Основополагающий источник≠ | Gregory, A. W., & Hansen, B. E. (1996). Residual-based tests for cointegration in models with regime shifts. Journal of Econometrics, 70(1), 99–126. DOI ↗ | Zivot, E., & Andrews, D. W. K. (1992). Further evidence on the great crash, the oil-price shock, and the unit-root hypothesis. Journal of Business & Economic Statistics, 10(3), 251–270. DOI ↗ |
| Другие названия | GH Cointegration Test, Gregory-Hansen Regime Shift Test, Residual-Based Cointegration Test with Structural Break, Rejim Değişimli Koentegrasyon Testi | ZA Test, Zivot-Andrews Break Test, Endogenous Break Unit-Root Test, Zivot-Andrews Birim Kök Testi |
| Связанные | 3 | 3 |
| Сводка≠ | The Gregory-Hansen test, introduced by Allan Gregory and Bruce Hansen in 1996, extends the standard Engle-Granger cointegration framework to allow for a single unknown structural break in the cointegrating relationship. It is designed for researchers who suspect that the long-run equilibrium between integrated variables may have shifted at some point during the sample period, and who wish to test for cointegration without presupposing the break date. | The Zivot-Andrews (ZA) test, introduced by Eric Zivot and Donald Andrews in 1992, is a sequential unit-root test that allows for a single structural break at an unknown date. It extends the augmented Dickey-Fuller framework by endogenously selecting the break point that provides the strongest evidence against the unit-root null hypothesis, making it particularly useful for macroeconomic and financial time series that may have been disrupted by events such as policy changes, financial crises, or supply shocks. |
| ScholarGateНабор данных ↗ |
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