Cointegration analysis under measurement errors

We study the effect of errors-in-variables [EV] on cointegration tests and cointegrating regressions. It turns out that the rate of convergence of static ordinary least squares [OLS] estimators is not affected by EV, whereas the limiting distribution does change. However, procedures accounting for short-run dynamics correct for EV at the same time and hence are robust to measurement errors. This is established asymptotically, and the relevance of our findings for finite samples is confirmed through computer experiments. Although our analysis is restricted to selected procedures, we indicate how our results will extend to related statistical techniques.