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Robustā Johansena kointegrācijas pārbaude×Engle-Granger kointegrācijas tests×
NozareEkonometrijaEkonometrija
SaimeRegression modelRegression model
Izcelsmes gads1988–20101987
AutorsJohansen (1988, 1991); robust extensions by Cavaliere, Rahbek, Taylor (2010) and othersRobert F. Engle and Clive W. J. Granger
TipsCointegration rank test (robust variant)Cointegration test
PirmavotsJohansen, S. (1991). Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models. Econometrica, 59(6), 1551–1580. DOI ↗Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗
Citi nosaukumioutlier-robust Johansen test, robust trace test, robust maximum eigenvalue test, robust cointegration rank testEG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG test
Saistītās55
KopsavilkumsThe Robust Johansen Cointegration test extends the classical Johansen (1988, 1991) likelihood-ratio framework for determining the cointegrating rank of a multivariate I(1) system to settings where standard Gaussian assumptions fail — in particular when the data exhibit outliers, fat-tailed innovations, or conditional heteroskedasticity. Robust modifications adjust residuals, re-weight observations, or bootstrap critical values so that rank inference remains valid under these violations.The 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.
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ScholarGateSalīdzināt metodes: Robust Johansen Cointegration · Engle-Granger Cointegration Test. Izgūts 2026-06-18 no https://scholargate.app/lv/compare