Unit root tests for time series with outliers

Effects of additive and innovational outliers on unit root tests in ARIMA(p, 1, q) models are investigated. The limiting distribution of the ordinary least-squares estimator of the unit root parameter in the AR(1) model is affected by additive outliers but is unaffected by innovational outliers. To test for a unit root in ARIMA(p, 1, q) models in the presence of outliers, a very simple, easy-to-compute procedure is given that detects additive outliers and adjusts the observations accordingly. The detection method performed well in our numerical experiment. Our unit root tests based on the adjusted data are shown to have very good empirical sizes and powers in AR(1), AR(2) and ARMA(1, 1) models.