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Causalidad de Granger con Panel Bootstrap de Kónya×Prueba de causalidad de Granger×
CampoEconometríaEconometría
FamiliaHypothesis testRegression model
Año de origen20061969
Autor originalLászló KónyaClive W. J. Granger
TipoNon-parametric bootstrap hypothesis testTime-series predictive causality test
Fuente seminalKónya, 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
Relacionados35
ResumenIntroduced 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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ScholarGateComparar métodos: Kónya Bootstrap Causality · Granger Causality. Recuperado el 2026-06-17 de https://scholargate.app/es/compare