Testing factors in CCE
针对交互效应面板数据模型的共同相关效应估计法，提出一个简单检验统计量，用于检验哪些截面均值足以估计未观测因子，或哪些可观测变量能捕捉这些因子。
One of the most popular estimators of interactive effects panel data models is the common correlated effects (CCE) approach, which uses the cross-sectional averages of the observables to estimate the unobserved factors. The present paper proposes a simple test statistic that is suitable for testing hypotheses about these factors. The statistic can be used to test if a subset of the averages is enough to estimate the factors, or if there are observable variables that capture them. The statistic can also be used sequentially to determine the smallest set of averages needed to estimate the factors.