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Causalité de Granger par bootstrap de Kónya×Test de causalité de Granger×
DomaineÉconométrieÉconométrie
FamilleHypothesis testRegression model
Année d'origine20061969
Auteur d'origineLászló KónyaClive W. J. Granger
TypeNon-parametric bootstrap hypothesis testTime-series predictive causality test
Source fondatriceKónya, L. (2006). Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling, 23(6), 978–992. DOI ↗Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗
AliasBootstrap Panel Causality Test, Kónya Panel Granger Causality, SUR-Based Bootstrap Causality, Kónya Önyükleme Nedensellik TestiGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi
Apparentées35
RésuméIntroduced by László Kónya in 2006, this method tests Granger causality in heterogeneous panels by estimating a Seemingly Unrelated Regressions (SUR) system and deriving country-specific critical values through bootstrapping. Unlike pooled panel tests, it delivers a separate causality verdict for each cross-section, making it particularly valuable in applied macroeconomics and international economics when panel units are expected to behave differently.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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ScholarGateComparer des méthodes: Kónya Bootstrap Causality · Granger Causality. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare