Recently, considerable emphasis has been placed on the problems arising out of cross-sectional dependence in panel unit root tests. This paper adopts the factor-based cross-sectional dependence paradigm of Bai and Ng (2005) but suggests alternative factor extraction methods. Some theoretical results for these methods are provided. Further, a detailed Monte Carlo study of these methods for multiple and persistent factors is undertaken. It is found that results are radically different from the serially uncorrelated single-factor case. Tests perform much worse and in some cases it is preferable not to correct at all for cross-sectional dependence.
