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Test de causalitat de Granger×Causalitat de Granger del Panell Bootstrap de Kónya×
CampEconometriaEconometria
FamíliaRegression modelHypothesis test
Any d'origen19692006
Autor originalClive W. J. GrangerLászló Kónya
TipusTime-series predictive causality testNon-parametric bootstrap hypothesis test
Font seminalGranger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗Kónya, L. (2006). Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling, 23(6), 978–992. DOI ↗
ÀliesGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik TestiBootstrap Panel Causality Test, Kónya Panel Granger Causality, SUR-Based Bootstrap Causality, Kónya Önyükleme Nedensellik Testi
Relacionats53
ResumThe 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.Introduced 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.
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ScholarGateCompara mètodes: Granger Causality · Kónya Bootstrap Causality. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare