Stationarity tests in heterogeneous panels

Several stationarity tests in heterogeneous panel data models are proposed in this chapter By allowing maximum degree of heterogeneity in the panel, two different ways of pooling information from independent rests, the group mean and the Fisher tests, are used to develop the panel stationarity tests. We consider the case of serially correlated errors in the level and trend stationary models. The smalt sample performances of the tests are investigated via Monte Carlo simulations. The simulation experiments reveal good small sample performances. In the presence of serial correlation, either the group mean or the Fisher tests based on individual KPSS tests with I, and LMC tests with p = 1 are recommended for use in empirical work due to their good small sample performances.