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Modelo de Autoregressores Vetoriais Robusto (Robust VAR)×Modelo de Vetor de Correção de Erros (VECM)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem1980s–2000s1987
Autor originalExtensions by Lutkepohl and others building on Sims (1980) VAR frameworkEngle & Granger
TipoMultivariate time-series model with robust estimationMultivariate time-series model
Fonte seminalGoncalves, S., & Kilian, L. (2004). Bootstrapping autoregressions with conditional heteroskedasticity of unknown form. Journal of Econometrics, 123(1), 89-120. DOI ↗Engle, R. F. & Granger, C. W. J. (1987). Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 55(2), 251-276. DOI ↗
Outros nomesrobust VAR, outlier-robust VAR, heavy-tailed VAR, RVARvector error correction model, error correction model, cointegration model, VECM (Vektör Hata Düzeltme Modeli)
Relacionados54
ResumoThe 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.The Vector Error Correction Model is a multivariate time-series model for cointegrated series that captures both their short-run dynamics and their long-run equilibrium relationship. It was introduced by Engle and Granger in 1987 as part of the cointegration and error-correction framework.
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ScholarGateComparar métodos: Robust VAR model · VECM. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare