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Granger Causality Test×Autoregressores Vetoriais (VAR)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem19691980
Autor originalClive W. J. GrangerChristopher A. Sims
TipoCausality test (F-test on VAR)Multivariate time-series model
Fonte seminalGranger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438. DOI ↗Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗
Outros nomesGranger test, GC test, predictive causality test, Granger non-causality testVAR, VAR model, vector autoregressive model, multivariate autoregression
Relacionados55
ResumoThe Granger causality test is a statistical hypothesis test that determines whether past values of one time series help predict future values of another, beyond what that series' own past already explains. Introduced by Clive Granger in 1969, it is the standard approach for assessing predictive causality in VAR-based time-series analysis.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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ScholarGateComparar métodos: Granger Causality Test · Vector Autoregression. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare