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Uji Kointegrasi Engle-Granger yang Robust×OLS Robust (OLS dengan Galat Standar Robust)×
BidangEkonometrikaEkonometrika
KeluargaRegression modelRegression model
Tahun asal1987 (base); robust variants 2000s–2020s1980
PencetusEngle & Granger (1987); robust extensions by subsequent authors including Hao & Shaffer and othersHalbert White
TipeCointegration testLinear regression with robust inference
Sumber perintisEngle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI ↗White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48(4), 817–838. DOI ↗
Aliasrobust EG cointegration, outlier-robust cointegration test, robust two-step cointegration, robust EG testHC robust regression, White robust OLS, sandwich estimator OLS, OLS with robust standard errors
Terkait56
RingkasanThe Robust Engle-Granger cointegration test adapts the classic two-step Engle-Granger procedure to withstand outliers, heavy-tailed error distributions, and additive noise that can severely distort standard residual-based cointegration inference. By substituting robust regression and robust unit-root testing for classical OLS and ADF steps, it yields reliable conclusions about long-run equilibrium relationships even when the data contain anomalous observations.Robust OLS applies ordinary least squares to estimate coefficients and then replaces the classical standard errors with heteroscedasticity-consistent (HC) standard errors — commonly called White standard errors. This leaves the point estimates unchanged while yielding valid t-statistics and confidence intervals even when the error variance is not constant across observations.
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ScholarGateBandingkan metode: Robust Engle-Granger Cointegration · Robust OLS. Diakses 2026-06-18 dari https://scholargate.app/id/compare