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| Robust Structural Vector Autoregression (Robust SVAR) Modell× | Vektor-Fehlerkorrekturmodell (VECM)× | |
|---|---|---|
| Fachgebiet | Ökonometrie | Ökonometrie |
| Familie | Regression model | Regression model |
| Entstehungsjahr≠ | 2000s–2010s | 1987 |
| Urheber≠ | Extension of Sims (1980) SVAR with robust inference methods | Robert F. Engle and Clive W. J. Granger |
| Typ≠ | Structural time series model | Multivariate time-series model |
| Wegweisende Quelle≠ | Lutkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. ISBN: 978-3540401728 | Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗ |
| Aliasnamen | robust SVAR, robust structural VAR, heteroscedasticity-robust SVAR, outlier-robust structural VAR | VECM, error correction VAR, cointegrated VAR, vector equilibrium correction model |
| Verwandt≠ | 6 | 5 |
| Zusammenfassung≠ | The Robust SVAR model extends the classical Structural VAR framework by incorporating robust estimation and inference methods that remain valid in the presence of heteroscedasticity, non-Gaussian errors, or outliers. By combining structural identification with robust statistical procedures, it produces reliable impulse responses and forecast error variance decompositions even when standard SVAR assumptions are violated in macroeconomic data. | 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. |
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