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| Zivot-Andrews 结构性断点检验× | 格兰杰因果检验× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1992 | 1969 |
| 提出者≠ | Eric Zivot and Donald W. K. Andrews | Clive W. J. Granger |
| 类型≠ | Unit root test with endogenous structural break | Causality test (F-test on VAR) |
| 开创性文献≠ | 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 ↗ | Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438. DOI ↗ |
| 别名 | ZA test, Zivot-Andrews unit root test, endogenous structural break unit root test, ZA structural break test | Granger test, GC test, predictive causality test, Granger non-causality test |
| 相关≠ | 6 | 5 |
| 摘要≠ | 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. | The Granger causality test is a statistical hypothesis test that determines whether past values of one time series help predict future values of another, beyond what that series' own past already explains. Introduced by Clive Granger in 1969, it is the standard approach for assessing predictive causality in VAR-based time-series analysis. |
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