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Prueba de Causalidad de Granger Robusta×Prueba de causalidad de Granger×
CampoEconometríaEconometría
FamiliaRegression modelRegression model
Año de origen2006 (robust variant); 1969 (original Granger)1969
Autor originalHacker & Hatemi-J (robust bootstrap variant); Granger (original causality concept)Clive W. J. Granger
TipoHypothesis testTime-series predictive causality test
Fuente seminalHacker, 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 ↗Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗
Aliasbootstrap Granger causality, heteroscedasticity-robust Granger causality, non-asymptotic Granger causality test, RGCGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi
Relacionados45
ResumenRobust 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 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.
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ScholarGateComparar métodos: Robust Granger Causality · Granger Causality. Recuperado el 2026-06-17 de https://scholargate.app/es/compare