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कोन्या बूटस्ट्रैप पैनल ग्रेंजर कॉज़ैलिटी×पैनल डेटा फिक्स्ड इफेक्ट्स मॉडल×
क्षेत्रअर्थमितिअर्थमिति
परिवारHypothesis testRegression model
उद्भव वर्ष20062014
प्रवर्तकLászló KónyaHsiao (textbook treatment); within transformation of panel data
प्रकारNon-parametric bootstrap hypothesis testPanel data regression
मौलिक स्रोतKónya, 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 ↗
उपनामBootstrap 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
संबंधित35
सारांशIntroduced 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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