A Principal Components Analysis of Common Stochastic Trends in Heterogeneous Panel Data: Some Monte Carlo Evidence
提出一种基于主成分分析的新方法，用于检验面板数据中驱动非平稳序列的共同随机趋势数量。该方法在混合I(0)和I(1)序列时仍有效，无需预检验单位根，并解决了大数据集的维度问题。
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.