This paper introduces a spatial panel quantile model with unobserved heterogeneity. The proposed model is capable of capturing high-dimensional cross-sectional dependence and allows heterogeneous regression coefficients. For estimating model parameters, a new estimation procedure is proposed....

This paper introduces a new procedure for clustering a large number of financial time series based on high-dimensional panel data with grouped factor structures. The proposed method attempts to capture the level of similarity of each of the time series based on sensitivity to observable risk...

We consider the problem of testing for slope homogeneity in high-dimensional panel data models with cross-sectionally correlated errors. We consider a Swamy-type test for slope homogeneity by incorporating interactive fixed effects. We show that the proposed test statistic is asymptotically...

This paper studies panel data models with unobserved group factor structures. The group membership of each unit and the number of groups are left unspecified. We estimate the model by minimizing the sum of least squared errors with a shrinkage penalty. The regressions coefficients can be...