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Kónya Bootstrap Panel Granger Kauzalitás×Granger Causality×Pesaran CD Teszt: Keresztmetszeti függőség diagnosztikai eljárás paneladatokhoz×
TudományterületÖkonometriaÖkonometriaÖkonometria
MódszercsaládHypothesis testRegression modelHypothesis test
Keletkezés éve200619692021
MegalkotóLászló KónyaClive W. J. GrangerM. Hashem Pesaran
TípusNon-parametric bootstrap hypothesis testTime-series predictive causality testNon-parametric diagnostic test
AlapműKónya, 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 ↗Pesaran, M. H. (2021). General diagnostic tests for cross-sectional dependence in panels. Empirical Economics, 60(1), 13–50. DOI ↗
Alternatív nevekBootstrap 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 TestiCD Test, Cross-Sectional Dependence Test, Pesaran General CD Test, Kesitsel Bağımlılık Testi
Kapcsolódó353
ÖsszefoglalóIntroduced 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.The Pesaran CD test is a general diagnostic procedure for detecting cross-sectional dependence in panel data models. Developed by M. Hashem Pesaran (2021), it is applicable to both balanced and unbalanced panels with large N and T, and retains validity under heterogeneous slope coefficients. The test is widely adopted in empirical economics, finance, and political economy as a prerequisite check before selecting appropriate estimators or unit-root tests for panel datasets.
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ScholarGateMódszerek összehasonlítása: Kónya Bootstrap Causality · Granger Causality · Pesaran CD Test. Letöltve 2026-06-19, forrás: https://scholargate.app/hu/compare