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Robust Structural Vector Autoregression (Robust SVAR) -malli×Vektorimallit (VAR)×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi2000s–2010s1980
KehittäjäExtension of Sims (1980) SVAR with robust inference methodsChristopher A. Sims
TyyppiStructural time series modelMultivariate time-series model
AlkuperäislähdeLutkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. ISBN: 978-3540401728Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗
Rinnakkaisnimetrobust SVAR, robust structural VAR, heteroscedasticity-robust SVAR, outlier-robust structural VARVAR, VAR model, vector autoregressive model, multivariate autoregression
Liittyvät65
TiivistelmäThe 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.Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.
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