Porównaj metody

	Test kointegracji Engle'a-Grangera	Model ARIMA (Autoregresyjny Zintegrowany Model Średniej Ruchomej)
Dziedzina	Ekonometria	Ekonometria
Rodzina	Regression model	Regression model
Rok powstania	1987	1970
Twórca	Robert F. Engle and Clive W. J. Granger	George Box and Gwilym Jenkins
Typ	Cointegration test	Time series forecasting model
Źródło pierwotne	Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
Inne nazwy	EG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG test	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
Pokrewne	5	6
Podsumowanie	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 ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics.