Regression modelEconometrics / time series
Phillips-Perron Unit Root Test
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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Sources
- Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI: 10.1093/biomet/75.2.335 ↗
- Hamilton, J. D. (1994). Time Series Analysis. Princeton University Press. ISBN: 978-0691042893
Related methods
Referenced by
Augmented Dickey-Fuller unit root testBayesian ADF unit root testBayesian PP unit root testEngle-Granger Cointegration TestFourier ADF unit root testFourier PP unit root testFourier Zivot-Andrews testNonlinear ADF Unit Root TestNonlinear PP unit root testPanel KPSS testPanel PP unit root testRobust ADF Unit Root TestRobust PP Unit Root TestStructural Break ADF Unit Root TestStructural Break KPSS TestStructural break Zivot-Andrews testTime-varying parameter Zivot-Andrews testZivot-Andrews Structural Break Test