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Engle-Grangers kointegrationstest×Granger-kausalitetstest×
ÄmnesområdeEkonometriEkonometri
FamiljRegression modelRegression model
Ursprungsår19871969
UpphovspersonRobert F. Engle and Clive W. J. GrangerClive W. J. Granger
TypCointegration testCausality test (F-test on VAR)
UrsprungskällaEngle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438. DOI ↗
AliasEG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG testGranger test, GC test, predictive causality test, Granger non-causality test
Närliggande55
SammanfattningThe Engle-Granger two-step method tests whether two or more non-stationary I(1) time series share a common stochastic trend — that is, whether a linear combination of them is stationary. If cointegration is confirmed, an error-correction model (ECM) can be estimated to capture both short-run dynamics and long-run equilibrium adjustment.The Granger causality test is a statistical hypothesis test that determines whether past values of one time series help predict future values of another, beyond what that series' own past already explains. Introduced by Clive Granger in 1969, it is the standard approach for assessing predictive causality in VAR-based time-series analysis.
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ScholarGateJämför metoder: Engle-Granger Cointegration Test · Granger Causality Test. Hämtad 2026-06-18 från https://scholargate.app/sv/compare