A panel cointegrating rank test with structural breaks and cross-sectional dependence

A new panel cointegrating rank test which allows for a linear time trend with breaks and cross-sectional dependence is proposed. The correlation-augmented inverse normal (CAIN) based on modification of the method combines p-values individual likelihood-ratio trace statistics by assuming that number break points are known. Monte Carlo study demonstrates its robustness to superior size power properties compared other meta-analytic tests used in practice. applied investigate long-run relationship between regional house prices personal income United States view structural introduced Global Financial Crisis.