Panel unit root tests under cross‐sectional dependence

In this paper alternative approaches for testing the unit root hypothesis in panel data are considered. First, a robust version of the Dickey‐Fuller t ‐statistic under contemporaneous correlated errors is suggested. Second, the GLS t ‐statistic is considered, which is based on the t ‐statistic of the transformed model. The asymptotic power of both tests is compared against a sequence of local alternatives. To adjust for short‐run serial correlation of the errors, we propose a pre‐whitening procedure that yields a test statistic with a standard normal limiting distribution as N and T tends to infinity. The test procedure is further generalized to accommodate individual specific intercepts or linear time trends. From our Monte Carlo simulations it turns out that the robust OLS t ‐statistic performs well with respect to size and power, whereas the GLS t ‐statistic may suffer from severe size distortions in small and moderate sample sizes. The tests are applied to test for a unit root in real exchange rates.