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Prova de causalitat de Granger robusta×Model d'Autoregressió Vectorial (VAR)×
CampEconometriaEconometria
FamíliaRegression modelRegression model
Any d'origen2006 (robust variant); 1969 (original Granger)2005
Autor originalHacker & Hatemi-J (robust bootstrap variant); Granger (original causality concept)Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
TipusHypothesis testMultivariate time-series model
Font 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 ↗Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
Àliesbootstrap Granger causality, heteroscedasticity-robust Granger causality, non-asymptotic Granger causality test, RGCvector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Relacionats44
ResumRobust 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).
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ScholarGateCompara mètodes: Robust Granger Causality · VAR Model. Recuperat el 2026-06-17 de https://scholargate.app/ca/compare