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| Test de Causalité de Panel Toda-Yamamoto× | Test de Causalité de Toda-Yamamoto× | |
|---|---|---|
| Domaine | Économétrie | Économétrie |
| Famille | Regression model | Regression model |
| Année d'origine≠ | 1995 (panel extension from 2006) | 1995 |
| Auteur d'origine≠ | Toda & Yamamoto (1995); extended to panel settings by Konya (2006) and others | Toda, H. Y. and Yamamoto, T. |
| Type≠ | Causality test (non-causality hypothesis) | Causality test |
| Source fondatrice | Toda, 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 ↗ |
| Alias | Panel TY causality test, Toda-Yamamoto panel causality, panel modified Wald causality test, panel MWALD causality | Toda-Yamamoto test, TY causality test, modified Wald test for Granger causality, TY-MWALD |
| Apparentées | 5 | 5 |
| Résumé≠ | The 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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