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ABSTRACT
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.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Funding
This article is supported by NSFC [Grant No. 71271096].
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