Conventional univariate Dickey-Fuller tests tend to produce spurious stationarity whenthere exist additive outlying observations in the time series. Correct critical values are usuallyobtained by adding dummy variables to the Dickey-Fuller regression. This is a nice theoreticalresult but not attractive from the empirical point of view since almost any result can be obtained just by a convenient selection of dummy variables. In this paper we suggest a robust procedure based on running Dickey-Fuller tests on the trend component instead of the original series. We provide both finite-sample and large-sample justifications. Practical implementation is illustrated through an empirical example based on the US/Finland real exchange rate series.
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