A Principal Components Analysis of Common Stochastic Trends in Heterogeneous Panel Data: Some Monte Carlo Evidence.

In this paper we propose a new approach based on principal components analysis to test for the number of common stochastic trends driving the non-stationary series in a panel data set. This test has the advantage that it is also consistent when there is a mixture of I(0) and I(1) series, making it unnecessary to pre-test the panel for unit root. Furthermore, the test solves the problem of dimensionality encountered in large panel data sets. Copyright 1999 by Blackwell Publishing Ltd