Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Test de racine unitaire Augmented Dickey-Fuller (ADF)× | Test de cointégration d'Engle-Granger× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1979–1984 | 1987 |
| Auteur d'origine≠ | Said & Dickey (1984); building on Dickey & Fuller (1979) | Robert F. Engle and Clive W. J. Granger |
| Type≠ | Hypothesis test (unit root) | Cointegration test |
| Source fondatrice≠ | Said, S. E., & Dickey, D. A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599–607. DOI ↗ | Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗ |
| Alias | ADF test, ADF unit root test, Dickey-Fuller test (augmented), Said-Dickey test | EG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG test |
| Apparentées | 5 | 5 |
| Résumé≠ | The Augmented Dickey-Fuller test is the standard procedure for determining whether a univariate time series contains a unit root — that is, whether the series is non-stationary. It extends the original Dickey-Fuller test by including lagged difference terms that absorb serial correlation in the residuals, making the test valid for a wide range of time-series processes encountered in economics and finance. | 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. |
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