Salīdzināt metodes

	Toda-Yamamoto (TY) Granger cēloņsakarības pārbaude	Dolado-Lütkepohl Grangera cēloniskuma tests
Nozare	Ekonometrija	Ekonometrija
Saime	Hypothesis test	Hypothesis test
Izcelsmes gads	1995	1996
Autors	Hiro Toda & Taku Yamamoto	Juan Dolado & Helmut Lütkepohl
Tips	Modified Wald test on augmented VAR	Modified Wald test for Granger causality in possibly integrated or cointegrated VAR systems
Pirmavots	Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1–2), 225–250.	Dolado, J. J., & Lütkepohl, H. (1996). Making Wald tests work for cointegrated VAR systems. Econometric Reviews, 15(4), 369–386.
Citi nosaukumi	TY Causality Test, Modified Wald Granger Causality, MWALD Test, Toda-Yamamoto Nedensellik Testi	DL Causality Test, Modified Wald Causality Test, Augmented VAR Causality Test, Dolado-Lütkepohl Testi
Saistītās	3	2
Kopsavilkums	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.	The Dolado-Lütkepohl (DL) test, introduced by Dolado and Lütkepohl (1996), is a modified Wald procedure for testing Granger causality in vector autoregressive (VAR) systems whose variables may be integrated or cointegrated. By fitting a VAR of slightly higher order than necessary and restricting the Wald statistic to the first p lag blocks, the test recovers the standard chi-squared limiting distribution without requiring pre-testing for cointegration or transformation to error-correction form.