Regression modelEconometrics / time series

Time-Varying Parameter Toda-Yamamoto Causality

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.

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Sources

  1. Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI: 10.1016/0304-4076(94)01616-8
  2. Adebayo, T. S., & Acheampong, A. O. (2022). Modelling the globalization-emissions nexus: Fresh insights from the novel dynamic ARDL simulations and the Toda-Yamamoto causality approaches. Environmental Science and Pollution Research, 29(3), 3825-3840. DOI: 10.1007/s11356-021-15769-3

Related methods

ScholarGateTime-varying parameter Toda-Yamamoto causality (Time-Varying Parameter Toda-Yamamoto Granger Causality Test). Retrieved 2026-06-04 from https://scholargate.app/tr/econometrics/time-varying-parameter-toda-yamamoto-causality