Reducing Size Distortions of Parametric Stationarity Tests

The use of asymptotic critical values in stationarity tests against the alternative of a unit root process is known to lead to over-rejections in finite samples when the considered process is stationary but highly persistent. We claim that, in recent parametric tests, this is caused by estimation errors which result when the autoregressive parameters used to describe the short-run dynamics of the process are replaced by estimators. We suggest a modification that corrects for these errors. Simulation results show that the modified test works reasonably well when the persistence is moderate and there is no time trend in the model but it is less effective when the model contains a time trend. An empirical illustration with inflation rate data is provided