Panel Unit Root Tests in the Presence of Cross-Sectional Dependency and Heterogeneity

Abstract

An IV approach, using as instruments nonlinear transformations of the lagged levels, is explored to test for unit roots in panels with general dependency and heterogeneity across cross-sectional units. We allow not only for the cross-sectional dependencies of innovations, but also for the presence of cointegration across cross sectional levels. Unbalanced panels and panels with differing individual short run dynamics and cross-sectionally related dynamics are also permitted. Panels with such cross-sectional dependencies and heterogeneities appear to be quite commonly observed in practical applications. Yet none of the currently available tests can be used to test for unit roots in such general panels. We also more carefully formulate the unit root hypothesis in panels. In particular, using order statistics we make it possible to test for and against the presence of unit roots in some of the individual units for a given panel. The individual IV t-ratios, which are the bases of our tests, are asymptotically normally distributed and cross-sectionally independent. Therefore, the critical values of the order statistics as well as the usual averaged statistic can be easily obtained from simple elementary probability computations. We show via a set of simulations that our tests work well, while other existing tests fail to perform properly. As an illustration, our tests are applied to some of the data sets that were used in earlier studies.Panels with cross-sectional dependency and heterogeneity, unit root test, cointegration, covariate, nonlinear instrument, order statistics