This paper analyzes multifactor models in the presence of a large number of potential observable risk factors and unobservable common and group-specific pervasive factors. We show how relevant observable factors can be found from a large given set and how to determine the number of common and...

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. The number of explanatory variables can be large. We estimate the model by minimizing the sum of least squared errors with a shrinkage...