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| Robuster Phillips-Perron (PP) Einheitswurzeltest× | Phillips-Perron-Einheitswurzeltest× | |
|---|---|---|
| Fachgebiet | Ökonometrie | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 1988 (base); 2000s–2010s (robust extensions) | 1988 |
| Urheber≠ | Phillips & Perron (1988); robustification by Cavaliere & Taylor (2008) and related authors | Peter C. B. Phillips and Pierre Perron |
| Typ≠ | Unit root / stationarity test | Hypothesis test (unit root) |
| Wegweisende Quelle | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ | Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗ |
| Aliasnamen | robust Phillips-Perron test, heteroskedasticity-robust PP test, nonparametric robust unit root test, robust PP | PP test, PP unit root test, Phillips-Perron test, nonparametric unit root test |
| Verwandt≠ | 6 | 5 |
| Zusammenfassung≠ | The Robust Phillips-Perron unit root test extends the classical PP test by applying corrections — such as heteroskedasticity-consistent covariance estimation or wild-bootstrap critical values — that maintain valid inference when the error variance of a time series is non-constant or exhibits unconditional heteroskedasticity, conditions under which the standard PP test is severely size-distorted. | 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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