Outlier Detection in Cointegration Analysis

Unit root tests and cointegration tests are sensitive to atypical events as outliers and structural breaks. This paper uses outlier robust estimation techniques to reduce the impact of these events on cointegration analysis. As a byproduct of computing the robust estimator, we obtain weights for all observations in the sample. These weights can be used to identify approximate dates of those atypical events. We evaluate our method via some illustrative simulated data. Furthermore, since our robust approach involves a few additional decisions on the values of key parameters, we investigate the sensitivity of our method through extensive Monte- Carlo simulations. Finally, we present an empirical example based on real-life data to show that OLS based cointegration can yield spurious cointegration