Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Prueba de Causalidad de Granger× | Modelo de Corrección de Errores Vectorial (VECM)× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1969 | 1987 |
| Autor original≠ | Clive W. J. Granger | Robert F. Engle and Clive W. J. Granger |
| Tipo≠ | Causality test (F-test on VAR) | Multivariate time-series model |
| Fuente seminal≠ | Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438. 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 | Granger test, GC test, predictive causality test, Granger non-causality test | VECM, error correction VAR, cointegrated VAR, vector equilibrium correction model |
| Relacionados | 5 | 5 |
| Resumen≠ | The Granger causality test is a statistical hypothesis test that determines whether past values of one time series help predict future values of another, beyond what that series' own past already explains. Introduced by Clive Granger in 1969, it is the standard approach for assessing predictive causality in VAR-based time-series analysis. | The Vector Error Correction Model extends the Vector Autoregression (VAR) framework to a system of variables that share one or more long-run equilibrium relationships. It jointly models short-run dynamics and the speed at which each variable corrects back toward equilibrium after a shock, making it the standard tool for analysing cointegrated multivariate time series. |
| ScholarGateConjunto de datos ↗ |
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