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Test de Causalitat Panel Toda-Yamamoto×Test de causalitat de Toda-Yamamoto×
CampEconometriaEconometria
FamíliaRegression modelRegression model
Any d'origen1995 (panel extension from 2006)1995
Autor originalToda & Yamamoto (1995); extended to panel settings by Konya (2006) and othersToda, H. Y. and Yamamoto, T.
TipusCausality test (non-causality hypothesis)Causality test
Font seminalToda, H. Y., & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated processes. Journal of Econometrics, 66(1-2), 225-250. 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 ↗
ÀliesPanel TY causality test, Toda-Yamamoto panel causality, panel modified Wald causality test, panel MWALD causalityToda-Yamamoto test, TY causality test, modified Wald test for Granger causality, TY-MWALD
Relacionats55
ResumThe Panel Toda-Yamamoto (PTY) causality test extends the Toda-Yamamoto modified Wald approach to panel data, allowing researchers to test Granger non-causality across multiple cross-sectional units without requiring pre-testing for cointegration or imposing a common causality direction on all units.The Toda-Yamamoto (TY) causality test is a modified Wald procedure for testing Granger causality in vector autoregressions (VARs) estimated in levels, even when variables are nonstationary or cointegrated. By intentionally over-fitting the VAR with extra lags equal to the maximum integration order, it restores the standard chi-squared asymptotic distribution of the Wald statistic without requiring prior unit-root or cointegration pretesting.
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ScholarGateCompara mètodes: Panel Toda-Yamamoto Causality · Toda-Yamamoto causality test. Recuperat el 2026-06-19 de https://scholargate.app/ca/compare