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Test de cointégration robuste d'Engle-Granger×Test de cointégration d'Engle-Granger×
DomaineÉconométrieÉconométrie
FamilleRegression modelRegression model
Année d'origine1987 (base); robust variants 2000s–2020s1987
Auteur d'origineEngle & Granger (1987); robust extensions by subsequent authors including Hao & Shaffer and othersRobert F. Engle and Clive W. J. Granger
TypeCointegration testCointegration test
Source fondatriceEngle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗
Aliasrobust EG cointegration, outlier-robust cointegration test, robust two-step cointegration, robust EG testEG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG test
Apparentées55
RésuméThe Robust Engle-Granger cointegration test adapts the classic two-step Engle-Granger procedure to withstand outliers, heavy-tailed error distributions, and additive noise that can severely distort standard residual-based cointegration inference. By substituting robust regression and robust unit-root testing for classical OLS and ADF steps, it yields reliable conclusions about long-run equilibrium relationships even when the data contain anomalous observations.The 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.
ScholarGateJeu de données
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ScholarGateComparer des méthodes: Robust Engle-Granger Cointegration · Engle-Granger Cointegration Test. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare