Regression modelEconometrics / time series
Robust Engle-Granger Cointegration Test
The 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.
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Sources
- Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276. DOI: 10.2307/1913236 ↗
- Hao, K., & Shaffer, A. (2021). Robust cointegration testing in the presence of outliers. Journal of Statistical Computation and Simulation, 91(10), 2137–2154. DOI: 10.1080/00949655.2021.1876261 ↗