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Teste de Causalidade de Toda-Yamamoto com Ruptura Estrutural×Modelo VAR com Rupturas Estruturais×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem1995 (base); structural break extensions widely adopted 2000s–2010s1980–1998
Autor originalToda & Yamamoto (1995); structural break extensions by Zivot & Andrews (1992) and subsequent applied literatureBai & Perron (structural breaks); Sims (VAR framework)
TipoCausality testMultivariate time series model with regime change
Fonte seminalToda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI ↗Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78. DOI ↗
Outros nomesSB-TY causality, structural break modified Wald test causality, Fourier Toda-Yamamoto causality, causality with regime shiftsVAR with structural breaks, break-point VAR, regime-switching VAR, SB-VAR
Relacionados66
ResumoThe structural break Toda-Yamamoto causality test extends the standard Toda-Yamamoto modified Wald (MWALD) procedure to accommodate one or more structural breaks in the time series. By identifying break dates first and then including dummy variables in the augmented VAR, the test maintains its valid asymptotic chi-squared distribution regardless of the integration or cointegration order of the variables, even in the presence of regime shifts.The Structural Break VAR model extends the standard Vector Autoregression (VAR) framework by allowing coefficient matrices and error covariance to shift at one or more unknown break dates. It is designed for multivariate time series where economic relationships change abruptly due to policy shifts, financial crises, or major structural events.
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ScholarGateComparar métodos: Structural Break Toda-Yamamoto Causality · Structural Break VAR Model. Recuperado em 2026-06-18 de https://scholargate.app/pt/compare