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| Модел на робастна структурна векторна авторегресия (Robust SVAR)× | Векторен модел за корекция на грешки (VECM)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 2000s–2010s | 1987 |
| Създател≠ | Extension of Sims (1980) SVAR with robust inference methods | Robert F. Engle and Clive W. J. Granger |
| Тип≠ | Structural time series model | Multivariate time-series model |
| Основополагащ източник≠ | 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 ↗ |
| Други названия | robust SVAR, robust structural VAR, heteroscedasticity-robust SVAR, outlier-robust structural VAR | VECM, error correction VAR, cointegrated VAR, vector equilibrium correction model |
| Свързани≠ | 6 | 5 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
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