A Likelihood Ratio Test for Idiosyncratic Unit Roots in the Exact Factor Model with Integrated Factors

We consider an exact factor model with unobservable common stochastic trends imposed by non-stationary factors, and study, by simulation, the power of the likelihood ratio test for unit roots in the idiosyncratic components. The power of the test is compared with the analogous Lagrange multiplier test and the Fisher-type test proposed by Bai and Ng. The results suggest that the benefit of the likelihood ratio test is in panels with a small cross-section.