Testing for Panel Cointegration Using Common Correlated Effects

Spurious regression analysis in panel data when time series are cross-section dependent is analyzed in the paper. We show that consistent estimation of the long-run average parameter is possible once we control for cross-section dependence using cross-section averages in the spirit of the common correlated effects approach in Pesaran (2006), Holly, Pesaran and Yamagata (2010) and Kapetanios, Pesaran and Yamagata (2011). This result is used to design a panel cointegration test statistic. The performance of the proposal is investigated in comparison with factor-based methods to control for dependence when both strong and weak cross-section dependence may be present.