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Linganisha mbinu

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Kipimo cha Uthabiti cha Ukozi wa Johansen×Kipimo cha Engle-Granger cha Uko-na-uhusiano×
NyanjaEkonometrikiEkonometriki
FamiliaRegression modelRegression model
Mwaka wa asili1988–20101987
MwanzilishiJohansen (1988, 1991); robust extensions by Cavaliere, Rahbek, Taylor (2010) and othersRobert F. Engle and Clive W. J. Granger
AinaCointegration rank test (robust variant)Cointegration test
Chanzo asiliaJohansen, 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 ↗
Majina mbadalaoutlier-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
Zinazohusiana55
MuhtasariThe 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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ScholarGateLinganisha mbinu: Robust Johansen Cointegration · Engle-Granger Cointegration Test. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare