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贝叶斯 Toda-Yamamoto 因果检验×向量自回归 (VAR)×
领域计量经济学计量经济学
方法族Regression modelRegression model
起源年份1995 (base); Bayesian variant developed post-20001980
提出者Toda & Yamamoto (1995) for the frequentist base; Bayesian extension by subsequent applied econometriciansChristopher A. Sims
类型Causality test / VAR-based inferenceMultivariate time-series model
开创性文献Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI ↗Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗
别名Bayesian TY causality, Bayesian modified Wald causality, Bayesian Granger non-causality in VAR, BTY causalityVAR, VAR model, vector autoregressive model, multivariate autoregression
相关35
摘要The Bayesian Toda-Yamamoto causality procedure combines the Toda-Yamamoto VAR augmentation strategy — which sidesteps the need for pre-testing integration and cointegration — with Bayesian prior-posterior updating. It tests Granger non-causality between time series that may be integrated or cointegrated without requiring differencing or error-correction modeling, while incorporating prior information and producing full posterior distributions over the causal parameters.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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ScholarGate方法对比: Bayesian Toda-Yamamoto Causality · Vector Autoregression. 于 2026-06-18 检索自 https://scholargate.app/zh/compare