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Dolado-Lütkepohl-Grangerin kausaalisuustesti×Vektorien autoregressiomalli (VAR-malli)×
TieteenalaEkonometriaEkonometria
MenetelmäperheHypothesis testRegression model
Syntyvuosi19962005
KehittäjäJuan Dolado & Helmut LütkepohlLütkepohl (textbook treatment); Sims (1980) macroeconometric tradition
TyyppiModified Wald test for Granger causality in possibly integrated or cointegrated VAR systemsMultivariate time-series model
AlkuperäislähdeDolado, J. J., & Lütkepohl, H. (1996). Making Wald tests work for cointegrated VAR systems. Econometric Reviews, 15(4), 369–386. DOI ↗Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗
RinnakkaisnimetDL Causality Test, Modified Wald Causality Test, Augmented VAR Causality Test, Dolado-Lütkepohl Testivector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon
Liittyvät24
TiivistelmäThe Dolado-Lütkepohl (DL) test, introduced by Dolado and Lütkepohl (1996), is a modified Wald procedure for testing Granger causality in vector autoregressive (VAR) systems whose variables may be integrated or cointegrated. By fitting a VAR of slightly higher order than necessary and restricting the Wald statistic to the first p lag blocks, the test recovers the standard chi-squared limiting distribution without requiring pre-testing for cointegration or transformation to error-correction form.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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ScholarGateVertaile menetelmiä: Dolado-Lütkepohl Causality · VAR Model. Haettu 2026-06-20 osoitteesta https://scholargate.app/fi/compare