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Testi i kauzalitetit jo-linear Toda-Yamamoto×Granger Causality×
FushaEkonometriEkonometri
FamiljaRegression modelRegression model
Viti i origjinës1995 (base); nonlinear extensions 2000s–2010s1969
KrijuesiToda & Yamamoto (1995) for the linear base; nonlinear extension developed by subsequent researchers applying rank transformations or neural-network-augmented VARClive W. J. Granger
LlojiCausality testTime-series predictive causality test
Burimi themeluesToda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. DOI ↗Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗
Emërtime të tjeranonlinear TY causality, rank-based Toda-Yamamoto test, modified Wald nonlinear causality, NTY causality testGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi
Të lidhura55
PërmbledhjaThe Nonlinear Toda-Yamamoto causality test extends the classic Toda-Yamamoto (1995) modified Wald procedure to detect causal linkages that are hidden in the means of series but manifest through nonlinear dynamics such as asymmetries, threshold effects, or volatility transmission. It fits an augmented VAR on rank-transformed or otherwise nonlinearly mapped series and applies a chi-squared Wald test on the extra-lag coefficients.The Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause.
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ScholarGateKrahasoni metodat: Nonlinear Toda-Yamamoto Causality · Granger Causality. Marrë më 2026-06-19 nga https://scholargate.app/sq/compare