Sammenlign metoder

	Kónya Bootstrap Panel Granger Causality	Dumitrescu-Hurlin Panel Granger-kausalitetstest
Fagfelt	Økonometri	Økonometri
Familie	Hypothesis test	Hypothesis test
Opprinnelsesår	2006	2012
Opphavsperson	László Kónya	Elena-Ivona Dumitrescu & Christophe Hurlin
Type	Non-parametric bootstrap hypothesis test	Non-causality test for heterogeneous panels
Opprinnelig kilde	Kónya, L. (2006). Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling, 23(6), 978–992.	Dumitrescu, E.-I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29(4), 1450–1460.
Alias	Bootstrap Panel Causality Test, Kónya Panel Granger Causality, SUR-Based Bootstrap Causality, Kónya Önyükleme Nedensellik Testi	DH Causality Test, Panel Granger Causality Test (Heterogeneous), Dumitrescu-Hurlin Test, Heterojen Panel Nedensellik Testi
Relaterte	3	3
Sammendrag	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.	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.