Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Тест причинности Тоды-Ямамото с учетом структурных сдвигов× | Модель векторной авторегрессии со структурными сдвигами× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1995 (base); structural break extensions widely adopted 2000s–2010s | 1980–1998 |
| Автор метода≠ | Toda & Yamamoto (1995); structural break extensions by Zivot & Andrews (1992) and subsequent applied literature | Bai & Perron (structural breaks); Sims (VAR framework) |
| Тип≠ | Causality test | Multivariate time series model with regime change |
| Основополагающий источник≠ | Toda, 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 ↗ |
| Другие названия | 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 |
| Связанные | 6 | 6 |
| Сводка≠ | 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. |
| ScholarGateНабор данных ↗ |
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