Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Engle-Granger kointegrācijas tests× | Paplašinātais Dikija-Fullera (ADF) vienības saknes tests× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 1987 | 1979–1984 |
| Autors≠ | Robert F. Engle and Clive W. J. Granger | Said & Dickey (1984); building on Dickey & Fuller (1979) |
| Tips≠ | Cointegration test | Hypothesis test (unit root) |
| Pirmavots≠ | Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗ | 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 ↗ |
| Citi nosaukumi | EG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG test | ADF test, ADF unit root test, Dickey-Fuller test (augmented), Said-Dickey test |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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. | 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. |
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