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Causalidade de Granger Bayesiana×Autoregressores Vetoriais (VAR)×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem1969 (frequentist); 1984 (Bayesian treatment)1980
Autor originalClive W. J. Granger (frequentist basis, 1969); Bayesian extension by Geweke (1984) and subsequent literatureChristopher A. Sims
TipoBayesian causal inference testMultivariate time-series model
Fonte seminalGeweke, J. (1984). Inference and causality in economic time series models. Handbook of Econometrics, 2, 1101-1144. Elsevier. link ↗Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗
Outros nomesBayesian Granger test, Bayesian predictive causality, BGC, Bayesian causality in meanVAR, VAR model, vector autoregressive model, multivariate autoregression
Relacionados65
ResumoBayesian Granger causality tests whether past values of one time series carry predictive information about another, framing the hypothesis through Bayesian inference rather than frequentist p-values. It combines a vector autoregressive (VAR) structure with prior distributions over coefficients and evaluates causal claims via posterior probabilities or Bayes factors, providing a probabilistic and nuanced alternative to the classical Granger test.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: Bayesian Granger Causality · Vector Autoregression. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare