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מבחן סיבתיות גריינג'ר של דולדו-לוטקפול×מבחן סיבתיות טודה-ימאמוטו (Toda-Yamamoto Granger Causality Test)×
תחוםאקונומטריקהאקונומטריקה
משפחהHypothesis testHypothesis test
שנת המקור19961995
הוגה השיטהJuan Dolado & Helmut LütkepohlHiro Toda & Taku Yamamoto
סוגModified Wald test for Granger causality in possibly integrated or cointegrated VAR systemsModified Wald test on augmented VAR
מקור מכונןDolado, J. J., & Lütkepohl, H. (1996). Making Wald tests work for cointegrated VAR systems. Econometric Reviews, 15(4), 369–386. DOI ↗Toda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1–2), 225–250. DOI ↗
כינוייםDL Causality Test, Modified Wald Causality Test, Augmented VAR Causality Test, Dolado-Lütkepohl TestiTY Causality Test, Modified Wald Granger Causality, MWALD Test, Toda-Yamamoto Nedensellik Testi
קשורות23
תקצירThe 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.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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ScholarGateהשוואת שיטות: Dolado-Lütkepohl Causality · Toda-Yamamoto Causality. אוחזר בתאריך 2026-06-19 מתוך https://scholargate.app/he/compare