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Test kointegracji Engle'a-Grangera×Test pierwiastka jednostkowego Phillipsa-Perrona×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania19871988
TwórcaRobert F. Engle and Clive W. J. GrangerPeter C. B. Phillips and Pierre Perron
TypCointegration testHypothesis test (unit root)
Źródło pierwotneEngle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗Phillips, P. C. B., & Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75(2), 335–346. DOI ↗
Inne nazwyEG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG testPP test, PP unit root test, Phillips-Perron test, nonparametric unit root test
Pokrewne55
PodsumowanieThe Engle-Granger two-step method tests whether two or more non-stationary I(1) time series share a common stochastic trend — that is, whether a linear combination of them is stationary. If cointegration is confirmed, an error-correction model (ECM) can be estimated to capture both short-run dynamics and long-run equilibrium adjustment.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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ScholarGatePorównaj metody: Engle-Granger Cointegration Test · Phillips-Perron unit root test. Pobrano 2026-06-18 z https://scholargate.app/pl/compare