This paper deals with identification and inference on the unobservable conditional factor space and its dimension in large unbalanced panels of asset returns. The model specification is nonparametric regarding the way the loadings vary in time as functions of common shocks and individual...

We examine the relationship between MIDAS regressions and the estimation of state space models applied to mixed frequency data. While in some cases the binding function is known, in general it is not, and therefore indirect inference is called for. The approach is appealing when we consider...

We build a simple diagnostic criterion for approximate factor structure in large panel datasets. Given observable factors, the criterion checks whether the errors are weakly cross-sectionally correlated or share at least one unobservable common factor (interactive effects). A general version...