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Модель робастной векторной авторегрессии (Robust VAR)×Структурная векторная авторегрессия (SVAR)×
ОбластьЭконометрикаЭконометрика
СемействоRegression modelRegression model
Год появления1980s–2000s1980
Автор методаExtensions by Lutkepohl and others building on Sims (1980) VAR frameworkSims (1980); identification schemes by Blanchard & Quah (1989)
ТипMultivariate time-series model with robust estimationMultivariate time series model
Основополагающий источникGoncalves, S., & Kilian, L. (2004). Bootstrapping autoregressions with conditional heteroskedasticity of unknown form. Journal of Econometrics, 123(1), 89-120. DOI ↗Blanchard, O. J., & Quah, D. (1989). The dynamic effects of aggregate demand and supply disturbances. American Economic Review, 79(4), 655-673. link ↗
Другие названияrobust VAR, outlier-robust VAR, heavy-tailed VAR, RVARSVAR, structural vector autoregression, identified VAR, structural VAR model
Связанные55
СводкаThe Robust VAR model extends the classical Vector Autoregression framework by replacing ordinary least squares estimation with robust estimators — such as M-estimators or median-based methods — to reduce the influence of outliers, structural breaks, and heavy-tailed shocks common in financial and macroeconomic time series.Structural VAR extends the reduced-form VAR by imposing economic theory-based restrictions that identify orthogonal structural shocks. This allows researchers to disentangle the causal effects of distinct economic disturbances — such as supply versus demand shocks — and trace their dynamic propagation through a system of variables via impulse response functions and forecast error variance decompositions.
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  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Robust VAR model · Structural VAR. Получено 2026-06-15 из https://scholargate.app/ru/compare