Regression modelEconometrics / time series
非线性 Granger 因果检验
非线性 Granger 因果关系将经典的线性 Granger 因果关系框架扩展到检测通过非线性动力学运作的预测关系。它使用基于相关积分或核密度估计的非参数或半参数统计量，识别一个变量的过去值是否能在任何线性模型所能捕捉到的基础上，进一步提高另一个变量的预测精度。
阅读完整方法
仅限会员
登录使用免费账户登录即可阅读本节。
Method map
The neighbourhood of related methods — select a node to explore.
来源
- Diks, C., & Panchenko, V. (2006). A new statistic and practical guidelines for nonparametric Granger causality testing. Journal of Economic Dynamics and Control, 30(9-10), 1647-1669. DOI: 10.1016/j.jedc.2005.08.008 ↗
- Hiemstra, C., & Jones, J. D. (1994). Testing for linear and nonlinear Granger causality in the stock price-volume relation. Journal of Finance, 49(5), 1639-1664. DOI: 10.1111/j.1540-6261.1994.tb04776.x ↗
如何引用本页
ScholarGate. (2026, June 3). Nonlinear Granger Causality Test. ScholarGate. https://scholargate.app/zh/econometrics/nonlinear-granger-causality
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 格兰杰因果检验计量经济学↔ compare
- 非线性ARDL (NARDL) 边界检验计量经济学↔ compare
- 非线性向量自回归模型计量经济学↔ compare
- 非线性向量误差修正模型（非线性VECM）计量经济学↔ compare
- Toda-Yamamoto 因果检验计量经济学↔ compare
- 向量自回归 (VAR)计量经济学↔ compare