Salīdzināt metodes

	Robusts strukturālās vektoru autoregresijas (Robust SVAR) modelis	Vektora kļūdu labojuma modelis (VECM)
Nozare	Ekonometrija	Ekonometrija
Saime	Regression model	Regression model
Izcelsmes gads	2000s–2010s	1987
Autors	Extension of Sims (1980) SVAR with robust inference methods	Robert F. Engle and Clive W. J. Granger
Tips	Structural time series model	Multivariate time-series model
Pirmavots	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.
Citi nosaukumi	robust SVAR, robust structural VAR, heteroscedasticity-robust SVAR, outlier-robust structural VAR	VECM, error correction VAR, cointegrated VAR, vector equilibrium correction model
Saistītās	6	5
Kopsavilkums	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.