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Kónya 부트스트랩 패널 Granger 인과관계 검정×두미트레스쿠-허를린 패널 그랜저 인과관계 검정×
분야계량경제학계량경제학
계열Hypothesis testHypothesis test
기원 연도20062012
창시자László KónyaElena-Ivona Dumitrescu & Christophe Hurlin
유형Non-parametric bootstrap hypothesis testNon-causality test for heterogeneous panels
원전Kónya, 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 ↗
별칭Bootstrap 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
관련33
요약Introduced 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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ScholarGate방법 비교: Kónya Bootstrap Causality · Dumitrescu-Hurlin Causality. 2026-06-18에 다음에서 검색함: https://scholargate.app/ko/compare