Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Тест Живота-Эндрюса на единичный корень с изменяющимися во времени параметрами× | Тест Зивота-Эндрюса на структурный разрыв× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1992 (base test); TVP adaptation in later applied work | 1992 |
| Автор метода≠ | Zivot & Andrews (1992); TVP extension in subsequent applied econometrics literature | Eric Zivot and Donald W. K. Andrews |
| Тип≠ | Unit root test with endogenous structural break under time-varying parameters | Unit root test with endogenous structural break |
| Основополагающий источник | 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 ↗ | 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≠ | TVP Zivot-Andrews test, time-varying Zivot-Andrews unit root test, TVP-ZA test | ZA test, Zivot-Andrews unit root test, endogenous structural break unit root test, ZA structural break test |
| Связанные | 6 | 6 |
| Сводка≠ | The time-varying parameter Zivot-Andrews test extends the classic Zivot-Andrews (1992) structural break unit root test by allowing the regression coefficients to evolve over time. Rather than assuming fixed parameters across the full sample, this approach lets the autoregressive dynamics and break timing adapt through a state-space or rolling framework, improving robustness when economic relationships shift gradually. | The Zivot-Andrews (ZA) test is a unit root test that endogenously identifies the most likely location of a single structural break in a time series. Unlike the standard ADF test, it does not require the researcher to pre-specify when the break occurred, making it robust to data-driven regime shifts such as policy changes, financial crises, or major economic events. |
| ScholarGateНабор данных ↗ |
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