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Test de causalité de Granger robuste×Modèle de Vector Autoregression (VAR)×
DomaineÉconométrieÉconométrie
FamilleRegression modelRegression model
Année d'origine2006 (robust variant); 1969 (original Granger)2005
Auteur d'origineHacker & Hatemi-J (robust bootstrap variant); Granger (original causality concept)Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
TypeHypothesis testMultivariate time-series model
Source fondatriceHacker, R. S., & Hatemi-J, A. (2006). Tests for causality between integrated variables using asymptotic and bootstrap distributions: Theory and application. Applied Economics, 38(13), 1489–1500. DOI ↗Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
Aliasbootstrap Granger causality, heteroscedasticity-robust Granger causality, non-asymptotic Granger causality test, RGCvector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Apparentées44
RésuméRobust Granger causality extends the classic Granger causality framework by using bootstrap-based or heteroscedasticity-robust critical values rather than asymptotic chi-squared tables. This makes the test reliable in finite samples and when the data exhibit non-normality, heteroscedasticity, or near-integration, settings where the standard F- or Wald-based test is known to over-reject.Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005).
ScholarGateJeu de données
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ScholarGateComparer des méthodes: Robust Granger Causality · VAR Model. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare