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| ARIMA (Autoregressive Integrated Moving Average) modell× | Kointegrációs teszt (Johansen / Engle-Granger)× | |
|---|---|---|
| Tudományterület | Ökonometria | Ökonometria |
| Módszercsalád | Regression model | Regression model |
| Keletkezés éve≠ | 2015 | 1988 |
| Megalkotó≠ | Box & Jenkins (Box-Jenkins methodology) | Engle & Granger (1987); Johansen (1988) |
| Típus≠ | Univariate time-series model | Time-series cointegration test |
| Alapmű≠ | Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021 | Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254. DOI ↗ |
| Alternatív nevek≠ | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | Johansen cointegration test, Engle-Granger cointegration test, long-run equilibrium test, Eşbütünleşme Testi (Johansen/Engle-Granger) |
| Kapcsolódó | 5 | 5 |
| Összefoglaló≠ | ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015). | The cointegration test examines whether non-stationary time series that each contain a unit root share a stable long-run equilibrium relationship. The single-equation residual approach was introduced by Engle and Granger (1987) and the system-based rank approach by Johansen (1988). |
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