Likelihood-based panel cointegration test in the presence of a linear time trend and cross-sectional dependence

This paper proposes a new likelihood-based panel cointegration rank test which extends the test of ¨Orsal and Droge (2012) (henceforth Panel SL test) to allow for cross-sectional dependence. The dependence is modelled by unobserved common factors which affect the variables in each cross-section through heterogeneous loadings. The common components are estimated following the panel analysis of nonstationarity in idiosyncratic and common components (PANIC) approach of Bai and Ng (2004) and the estimates are subtracted from the observations. The cointegrating rank of the defactored data is then tested by the Panel SL test. A Monte Carlo study demonstrates that the proposed testing procedure has reasonable size and power properties in finite samples