方法对比
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| 时变参数Toda-Yamamoto因果关系× | 向量自回归 (VAR) 模型× | |
|---|---|---|
| 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); TVP variant emerged early 2000s–2010s | 2005 |
| 提出者≠ | Toda & Yamamoto (1995); TVP extension by subsequent applied econometricians | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| 类型≠ | Causality test (time-varying) | Multivariate 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 ↗ | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗ |
| 别名 | TVP-TY causality, time-varying Toda-Yamamoto, TVP Granger causality (Toda-Yamamoto), rolling/recursive Toda-Yamamoto causality | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| 相关≠ | 3 | 4 |
| 摘要≠ | The TVP Toda-Yamamoto causality test combines Toda and Yamamoto's (1995) augmented VAR approach — which handles possibly integrated or cointegrated series without pre-testing for unit roots — with time-varying parameters, allowing causal relationships between variables to shift across different periods rather than remaining fixed throughout the sample. | Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005). |
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