A panel data model with interactive effects characterized by multilevel non-parallel factors

摘要

Current research only considers parallel factors in factor models. In this article, we provide an algorithm based on cross principal component analysis that identifies and estimates a panel data model with interactive effects characterized by multilevel and non-parallel factors. The simulation results show that our estimator is consistent, converges quickly and outperforms other estimators that identify the factor structure incorrectly.