Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper proposes a unit root test for panel data with cross-sectional dependence. The test generalizes the nonlinear IV unit root test of Chang (2002) to the case where there exist some common factors in panels. The main idea is to eliminate the cross-sectional dependence through the method of principal components as in Bai and Ng (2004) and then apply Chang's test to the treated data. Under certain conditions, the proposed test is consistent and has a standard normal limiting distribution under the null hypothesis. Simulation results show that the proposed test compares favorably to other alternative tests.