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Kónya Bootstrap Panel Granger-Kausalität×Paneldaten-Fixed-Effects-Modell×
FachgebietÖkonometrieÖkonometrie
FamilieHypothesis testRegression model
Entstehungsjahr20062014
UrheberLászló KónyaHsiao (textbook treatment); within transformation of panel data
TypNon-parametric bootstrap hypothesis testPanel data regression
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 ↗Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗
AliasnamenBootstrap Panel Causality Test, Kónya Panel Granger Causality, SUR-Based Bootstrap Causality, Kónya Önyükleme Nedensellik Testifixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
Verwandt35
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 Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).
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ScholarGateMethoden vergleichen: Kónya Bootstrap Causality · Panel Fixed Effects. Abgerufen am 2026-06-19 von https://scholargate.app/de/compare