ScholarGate
Asistent

Compară metode

Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.

Testul de cauzalitate Granger×Granger Causalitate Bootstrap Kónya pentru Panouri×
DomeniuEconometrieEconometrie
FamilieRegression modelHypothesis test
Anul apariției19692006
Autorul originalClive W. J. GrangerLászló Kónya
TipTime-series predictive causality testNon-parametric bootstrap hypothesis test
Sursa seminalăGranger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗Kónya, L. (2006). Exports and growth: Granger causality analysis on OECD countries with a panel data approach. Economic Modelling, 23(6), 978–992. DOI ↗
Denumiri alternativeGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik TestiBootstrap Panel Causality Test, Kónya Panel Granger Causality, SUR-Based Bootstrap Causality, Kónya Önyükleme Nedensellik Testi
Înrudite53
RezumatThe 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.Introduced 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.
ScholarGateSet de date
  1. v1
  2. 1 Surse
  3. PUBLISHED
  1. v1
  2. 1 Surse
  3. PUBLISHED

Mergi la căutare Descarcă prezentarea

ScholarGateCompară metode: Granger Causality · Kónya Bootstrap Causality. Preluat la 2026-06-18 de pe https://scholargate.app/ro/compare