This paper proposes new error correction-based cointegration tests for panel data, addressing the issue of common factor restrictions that can lead to reduced power in residual-based tests. The tests are designed to be robust to both weak exogeneity and the common factor restriction, and they do not impose any restrictions on the long-run equilibrium relationship between variables. The asymptotic distributions of the tests are derived, and critical values are provided. Simulation results show that the tests have good small-sample properties, with small size distortions and high power compared to popular residual-based panel cointegration tests. An empirical application using international health care expenditures and GDP data demonstrates that these variables are cointegrated, even when the possibility of an invalid common factor restriction is considered. The paper also discusses the construction of the tests, their asymptotic properties, and methods to handle cross-sectional dependence through bootstrap techniques.This paper proposes new error correction-based cointegration tests for panel data, addressing the issue of common factor restrictions that can lead to reduced power in residual-based tests. The tests are designed to be robust to both weak exogeneity and the common factor restriction, and they do not impose any restrictions on the long-run equilibrium relationship between variables. The asymptotic distributions of the tests are derived, and critical values are provided. Simulation results show that the tests have good small-sample properties, with small size distortions and high power compared to popular residual-based panel cointegration tests. An empirical application using international health care expenditures and GDP data demonstrates that these variables are cointegrated, even when the possibility of an invalid common factor restriction is considered. The paper also discusses the construction of the tests, their asymptotic properties, and methods to handle cross-sectional dependence through bootstrap techniques.