Panel unit root tests such as the one derived by Levin et al. (2002) LLC, are a generalization of the augmented Dickey–Fuller (ADF) individual country unit root tests to a common panel unit root test. The idea is that this panel unit root test will be more powerful than performing individual unit root tests for each cross-section. The null hypothesis is that each individual time series contains a unit root against the alternative that each time series is stationary. Computationally, one may elect to include no exogenous regressors, or to include individual constant terms (fixed effects), or to employ constants and trends. This panel unit root test has its limitations. The test crucially depends upon the independence assumption across cross-sections and is not applicable if cross-sectional correlation is present. Second, the assumption that all cross-sections have or do not have a unit root is restrictive. As Maddala (1999) pointed out, the null may be fine for testing convergence in growth among countries, but the alternative restricts every country to converge at the same rate. Im et al. (2003) (IPS) propose an alternative testing procedure based on averaging individual unit root ADF test statistics. The null hypothesis is that each series in the panel contains a unit root, and the alternative hypothesis allows for some (but not all) of the individual series to have unit roots.