Comparar métodos

	Prueba de Causalidad de Toda-Yamamoto con Ruptura Estructural	Modelo VAR con Rupturas Estructurales
Campo	Econometría	Econometría
Familia	Regression model	Regression model
Año de origen	1995 (base); structural break extensions widely adopted 2000s–2010s	1980–1998
Autor original	Toda & Yamamoto (1995); structural break extensions by Zivot & Andrews (1992) and subsequent applied literature	Bai & Perron (structural breaks); Sims (VAR framework)
Tipo	Causality test	Multivariate time series model with regime change
Fuente seminal	Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250.	Bai, J., & Perron, P. (1998). Estimating and testing linear models with multiple structural changes. Econometrica, 66(1), 47–78.
Alias	SB-TY causality, structural break modified Wald test causality, Fourier Toda-Yamamoto causality, causality with regime shifts	VAR with structural breaks, break-point VAR, regime-switching VAR, SB-VAR
Relacionados	6	6
Resumen	The 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.