Hypothesis testCausality

Toda-Yamamoto Granger Causality Test

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.

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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

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Referenced by

ScholarGateToda-Yamamoto Causality (Toda-Yamamoto Granger Causality Test). Retrieved 2026-06-04 from https://scholargate.app/en/econometrics/toda-yamamoto-causality