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Causalidad de Granger con Panel Bootstrap de Kónya×Modelo de Efectos Fijos para Datos de Panel×
CampoEconometríaEconometría
FamiliaHypothesis testRegression model
Año de origen20062014
Autor originalLászló KónyaHsiao (textbook treatment); within transformation of panel data
TipoNon-parametric bootstrap hypothesis testPanel data regression
Fuente seminalKónya, 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 ↗
AliasBootstrap 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
Relacionados35
ResumenIntroduced 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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ScholarGateComparar métodos: Kónya Bootstrap Causality · Panel Fixed Effects. Recuperado el 2026-06-18 de https://scholargate.app/es/compare