方法对比
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| 非线性 PP 单位根检验× | 非线性 KPSS 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≠ | 1988 (base); 2000s (nonlinear extensions) | 2006 |
| 提出者≠ | Phillips & Perron (1988); nonlinear extensions by Kapetanios, Shin & Snell (2003) and related authors | Becker, Enders & Lee |
| 类型≠ | Unit root test with nonlinear adjustment | Stationarity test (null: stationary) |
| 开创性文献≠ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335-346. DOI ↗ | Becker, R., Enders, W., & Lee, J. (2006). A stationarity test in the presence of an unknown number of smooth breaks. Journal of Time Series Analysis, 27(3), 381-409. DOI ↗ |
| 别名 | Nonlinear PP test, Nonlinear Phillips-Perron test, PP unit root test with nonlinear adjustment, nonlinear PP | KPSS nonlinearity test, nonlinear stationarity test, flexible Fourier KPSS, NL-KPSS |
| 相关≠ | 6 | 3 |
| 摘要≠ | The Nonlinear Phillips-Perron unit root test extends the classic PP test by allowing the adjustment toward equilibrium to follow a nonlinear path — such as a smooth transition or threshold mechanism — rather than assuming a constant linear speed of adjustment. This makes it more powerful when the true data-generating process involves regime-dependent or asymmetric mean-reversion dynamics. | The nonlinear KPSS test extends the classic Kwiatkowski-Phillips-Schmidt-Shin stationarity test by modelling unknown smooth structural breaks in the deterministic trend using a Fourier approximation. Under the null hypothesis the series is stationary around a flexible nonlinear trend, guarding against spurious unit-root findings caused by regime shifts or gradual transitions. |
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