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Kónya Bootstrap Panel Granger-Kausalität×Dumitrescu-Hurlin-Panel-Granger-Kausalitätstest×
FachgebietÖkonometrieÖkonometrie
FamilieHypothesis testHypothesis test
Entstehungsjahr20062012
UrheberLászló KónyaElena-Ivona Dumitrescu & Christophe Hurlin
TypNon-parametric bootstrap hypothesis testNon-causality test for heterogeneous panels
Wegweisende QuelleKónya, L. (2006). Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling, 23(6), 978–992. DOI ↗Dumitrescu, E.-I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460. DOI ↗
AliasnamenBootstrap Panel Causality Test, Kónya Panel Granger Causality, SUR-Based Bootstrap Causality, Kónya Önyükleme Nedensellik TestiDH Causality Test, Panel Granger Causality Test (Heterogeneous), Dumitrescu-Hurlin Test, Heterojen Panel Nedensellik Testi
Verwandt33
ZusammenfassungIntroduced 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 Dumitrescu-Hurlin (DH) test, introduced by Elena-Ivona Dumitrescu and Christophe Hurlin in their 2012 Economic Modelling article, tests for Granger non-causality in heterogeneous panel datasets. Unlike standard panel causality approaches, it permits each cross-sectional unit to have its own distinct causal relationship, making it well-suited for macro-panels of countries, firms, or regions where homogeneity cannot be assumed.
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ScholarGateMethoden vergleichen: Kónya Bootstrap Causality · Dumitrescu-Hurlin Causality. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare