Given the growing availability of large datasets and following recent research trends on multi-dimensional modelling, we develop three dimensional (3D) panel data models with hierarchical error components that allow for strong cross-sectional dependence through unobserved heterogeneous global...

We develop a novel approach based on the generalised canonical correlation (GCC) analysis to consistently estimating the multilevel factor model and providing the proper inference theory for the high dimensional panel data. Importantly, our approach is shown to be robust to a non-zero...