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Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Test de racine unitaire de Phillips-Perron à la Fourier (Fourier PP)× | Test de racine unitaire de Phillips-Perron× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 2006 | 1988 |
| Auteur d'origine≠ | Becker, Enders, and Lee | Peter C. B. Phillips and Pierre Perron |
| Type≠ | Unit root test with Fourier approximation | Hypothesis test (unit root) |
| Source fondatrice≠ | Enders, W., & Siklos, P. L. (2001). Cointegration and threshold adjustment. Journal of Business and Economic Statistics, 19(2), 166-176. DOI ↗ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ |
| Alias | Fourier PP test, Flexible Fourier PP unit root test, Enders-Lee Fourier PP test, nonlinear PP unit root test | PP test, PP unit root test, Phillips-Perron test, nonparametric unit root test |
| Apparentées≠ | 6 | 5 |
| Résumé≠ | The Fourier PP unit root test extends the classical Phillips-Perron test by embedding low-frequency Fourier terms in the deterministic component, enabling the test to account for an unknown number of smooth, gradual structural breaks in the level or trend without pre-specifying their timing or shape. | 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. |
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