This paper proposes a new panel unit root test based on Simes' [Biometrika 1986, An Improved Bonferroni Procedure for Multiple Tests of Significance'] classical intersection test. The test is robust to general patterns of cross-sectional dependence and yet straightforward to implement, only requiring p-values of time series unit root tests of the series in the panel, and no resampling. Monte Carlo experiments show good size and power properties relative to existing panel unit root tests. Unlike previously suggested tests, the new test allows to identify the units in the panel for which the alternative of stationarity can be said to hold. We provide two empirical applications to panels of real gross domestic product (GDP) and real exchange rate data.
Multiple Testing Panel Unit Root Test Cross-Sectional Dependence