Сравнение методов

	Тест на коинтеграцию Энгла-Грэнджера	Модель ARIMA (авторегрессионная интегрированная скользящая средняя)
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1987	1970
Автор метода	Robert F. Engle and Clive W. J. Granger	George Box and Gwilym Jenkins
Тип	Cointegration test	Time series forecasting model
Основополагающий источник	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.
Другие названия	EG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG test	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
Связанные	5	6
Сводка	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.