In this paper we propose a set of new panel tests to detect changes in persistence. These statistics are used to test the null hypothesis of stationarity against the alternative of a change in persistence from I(0) to I(1) or viceversa. Alternative of unknown direction is also considered. The limiting distributions of the panel tests are derived and small sample properties are investigated by Monte Carlo experiments under the hypothesis that the individual series are cross-sectionally independently distributed. These tests have a good size and power properties. Cross-sectional dependence is also considered. A procedure of de-factorizing proposed by Stock and Watson (2002) is applied. Monte Carlo analysis is conducted and the defactored panel tests show to have good size and power. The empirical results obtained from applying these tests to a panel covering 15 European countries between 1970 and 2006 suggest that inflation rate changes from I(1) to I(0) when cross-correlation is considered.