Stationarity tests in heterogeneous panels

Abstract

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 tests, 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 small 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 l2 and LMC tests with p = 1 are recommended for use in empirical work due to their good small sample performances.

Citation

Yin, Y. and Wu, S. (2001), "Stationarity tests in heterogeneous panels", Baltagi, B.H., Fomby, T.B. and Carter Hill, R. (Ed.) Nonstationary Panels, Panel Cointegration, and Dynamic Panels (Advances in Econometrics, Vol. 15), Emerald Group Publishing Limited, Leeds, pp. 275-296. https://doi.org/10.1016/S0731-9053(00)15010-8