We present a test of the null hypothesis of stationarity against unit root alternatives for panel data that allows for arbitrary cross- sectional dependence. We treat the short run time series dynamics non- parametrically and thus avoid the need to fit separate models for the individual series. The statistic is simple to compute and is asymptotically normally distributed, even in the presence of a wide range of deterministic components. Taken together, these features provide a generally applicable solution to the problem of testing for stationarity versus unit roots in macro-panel based data. The test is applied to assess the validity of the purchasing power parity hypothesis and finds significant evidence against the hypothesis being true.