Testing for Panel Cointegration Using Common Correlated Effects Estimators

Spurious regression analysis in panel data when the time series are cross section dependent is analysed in the article. 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 proposed by Pesaran. This result is used to design a panel cointegration test statistic accounting for cross section dependence. The performance of the proposal is investigated in comparison with factor‐based methods to control for cross section dependence when strong, semi‐weak and weak cross section dependence may be present.