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Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Test de racine unitaire de Fourier Zivot-Andrews× | Test de racine unitaire de Phillips-Perron× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 2012 | 1988 |
| Auteur d'origine≠ | Enders & Lee (2012), extending Zivot & Andrews (1992) | Peter C. B. Phillips and Pierre Perron |
| Type≠ | Unit root test with smooth structural break | Hypothesis test (unit root) |
| Source fondatrice≠ | Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574-599. 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 ZA test, FZA unit root test, Fourier structural break unit root test, smooth structural break ADF test | PP test, PP unit root test, Phillips-Perron test, nonparametric unit root test |
| Apparentées≠ | 6 | 5 |
| Résumé≠ | The Fourier Zivot-Andrews test extends the classic Zivot-Andrews (1992) unit root test by replacing sharp, single structural break dummies with a low-frequency Fourier approximation, allowing the test to accommodate smooth, gradual, and multiple unknown breaks in the level or trend of a series. | 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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