方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 恩格尔-格兰杰协整检验× | Phillips-Perron单位根检验× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1987 | 1988 |
| 提出者≠ | Robert F. Engle and Clive W. J. Granger | Peter C. B. Phillips and Pierre Perron |
| 类型≠ | Cointegration test | Hypothesis test (unit root) |
| 开创性文献≠ | Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ |
| 别名 | EG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG test | PP test, PP unit root test, Phillips-Perron test, nonparametric unit root test |
| 相关 | 5 | 5 |
| 摘要≠ | The Engle-Granger two-step method tests whether two or more non-stationary I(1) time series share a common stochastic trend — that is, whether a linear combination of them is stationary. If cointegration is confirmed, an error-correction model (ECM) can be estimated to capture both short-run dynamics and long-run equilibrium adjustment. | The Phillips-Perron (PP) test is a nonparametric unit root test for time series that corrects for serial correlation and heteroscedasticity in the error term without adding lagged differences. Introduced by Phillips and Perron (1988), it applies a kernel-based long-run variance estimator to adjust the Dickey-Fuller statistic, making it robust to a wide class of weakly dependent error processes. |
| ScholarGate数据集 ↗ |
|
|