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

Stephen Hall, Stepana Lazarova and Giovanni Urga

Oxford Bulletin of Economics and Statistics, 1999, vol. 61, issue S1, 749-767

Abstract: 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.

Date: 1999
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