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| 结构性断点Toda-Yamamoto因果检验× | 结构性断裂格兰杰因果关系× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1995 (base); structural break extensions widely adopted 2000s–2010s | 1995-2010 |
| 提出者≠ | Toda & Yamamoto (1995); structural break extensions by Zivot & Andrews (1992) and subsequent applied literature | Granger (1969) causality framework extended by Toda & Yamamoto (1995) and Balcilar et al. (2010) |
| 类型≠ | Causality test | Hypothesis test / 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 ↗ | Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI ↗ |
| 别名 | SB-TY causality, structural break modified Wald test causality, Fourier Toda-Yamamoto causality, causality with regime shifts | break-robust Granger causality, Granger causality under regime change, time-varying Granger causality, structural change Granger test |
| 相关≠ | 6 | 3 |
| 摘要≠ | 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. | Structural break Granger causality extends the classic Granger causality framework to accommodate regime shifts and parameter instability in time series. By detecting break points and testing causality within sub-samples or via rolling/recursive windows, it reveals whether a predictive relationship between variables switches on, switches off, or changes direction over time. |
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