Comparar métodos

	Prueba Robusta de Cointegración de Engle-Granger	Test de cointegración de Engle-Granger
Campo	Econometría	Econometría
Familia	Regression model	Regression model
Año de origen	1987 (base); robust variants 2000s–2020s	1987
Autor original	Engle & Granger (1987); robust extensions by subsequent authors including Hao & Shaffer and others	Robert F. Engle and Clive W. J. Granger
Tipo	Cointegration test	Cointegration test
Fuente seminal	Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276.	Engle, R. F., & Granger, C. W. J. (1987). Co-integration and error correction: Representation, estimation, and testing. Econometrica, 55(2), 251–276.
Alias	robust EG cointegration, outlier-robust cointegration test, robust two-step cointegration, robust EG test	EG cointegration test, Engle-Granger two-step method, residual-based cointegration test, EG test
Relacionados	5	5
Resumen	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.	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.