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Test de causalité de Granger robuste×Test de cointégration (Johansen / Engle-Granger)×
DomaineÉconométrieÉconométrie
FamilleRegression modelRegression model
Année d'origine2006 (robust variant); 1969 (original Granger)1988
Auteur d'origineHacker & Hatemi-J (robust bootstrap variant); Granger (original causality concept)Engle & Granger (1987); Johansen (1988)
TypeHypothesis testTime-series cointegration test
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 ↗Johansen, S. (1988). Statistical Analysis of Cointegration Vectors. Journal of Economic Dynamics and Control, 12(2-3), 231-254. DOI ↗
Aliasbootstrap Granger causality, heteroscedasticity-robust Granger causality, non-asymptotic Granger causality test, RGCJohansen cointegration test, Engle-Granger cointegration test, long-run equilibrium test, Eşbütünleşme Testi (Johansen/Engle-Granger)
Apparentées45
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.The cointegration test examines whether non-stationary time series that each contain a unit root share a stable long-run equilibrium relationship. The single-equation residual approach was introduced by Engle and Granger (1987) and the system-based rank approach by Johansen (1988).
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ScholarGateComparer des méthodes: Robust Granger Causality · Cointegration Test. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare