This paper considers modeling and detecting structure breaks associated with cross-sectional dependence for large dimensional panel data models, which are popular in many fields including economics and finance. We propose a dynamic factor structure to measure the degree of cross-sectional...

Bai (2009) proposes a recursive least-squares estimation method for large panel data models with unobservable interactive fixed effects, but the impact of recursion on the asymptotic properties of the least-squares estimators is not taken into account. In this paper, we extend Bai (2009) by...

Statistical inferences for sample correlation matrices are important in high dimensional data analysis. Motivated by this, this paper establishes a new central limit theorem (CLT) for a linear spectral statistic (LSS) of high dimensional sample correlation matrices for the case where the...

In this paper, we investigate binary response models for heterogeneous panel data with interactive fixed effects by allowing both the cross sectional dimension and the temporal dimension to diverge. From a practical point of view, the proposed framework can be applied to predict the probability...