方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| Toda-Yamamoto Granger 因果检验× | 向量自回归 (VAR) 模型× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族≠ | Hypothesis test | Regression model |
| 起源年份≠ | 1995 | 2005 |
| 提出者≠ | Hiro Toda & Taku Yamamoto | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| 类型≠ | Modified Wald test on augmented VAR | 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 | TY Causality Test, Modified Wald Granger Causality, MWALD Test, Toda-Yamamoto Nedensellik Testi | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| 相关≠ | 3 | 4 |
| 摘要≠ | The Toda-Yamamoto (TY) causality test, introduced by Toda and Yamamoto (1995), provides a robust procedure for testing Granger non-causality in vector autoregressive (VAR) models when the variables may be integrated or cointegrated of arbitrary order. By intentionally over-fitting the VAR with extra lags equal to the maximum integration order, the method bypasses the need for pre-testing cointegration and preserves the standard asymptotic chi-squared distribution of the Wald statistic. | 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). |
| ScholarGate数据集 ↗ |
|
|