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Toda-Yamamoto (TY) 인과관계 검정×Dolado-Lütkepohl Granger 인과관계 검정×
분야계량경제학계량경제학
계열Hypothesis testHypothesis test
기원 연도19951996
창시자Hiro Toda & Taku YamamotoJuan Dolado & Helmut Lütkepohl
유형Modified Wald test on augmented VARModified Wald test for Granger causality in possibly integrated or cointegrated VAR systems
원전Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1–2), 225–250. DOI ↗Dolado, J. J., & Lütkepohl, H. (1996). Making Wald tests work for cointegrated VAR systems. Econometric Reviews, 15(4), 369–386. DOI ↗
별칭TY Causality Test, Modified Wald Granger Causality, MWALD Test, Toda-Yamamoto Nedensellik TestiDL Causality Test, Modified Wald Causality Test, Augmented VAR Causality Test, Dolado-Lütkepohl Testi
관련32
요약The 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.
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ScholarGate방법 비교: Toda-Yamamoto Causality · Dolado-Lütkepohl Causality. 2026-06-19에 다음에서 검색함: https://scholargate.app/ko/compare