We extend the theory on factor models by incorporating “local” factors into the model. Local
factors affect only an unknown subset of the observed variables. This implies a continuum of …

This article investigates estimation of sparsity-induced weak factor (sWF) models, with large
cross-sectional and time-series dimensions (N and T, respectively). It assumes that the k th …

A fractionally integrated panel data model with a multi-level cross-sectional dependence is
proposed. Such dependence is driven by a factor structure that captures comovements …

In this article, we consider statistical inference for high-dimensional approximate factor
models. We posit a weak factor structure, in which the factor loading matrix can be sparse …

This paper assesses the international comovement of gross capital inflows and outflows
using a two-level factor model. Among advanced and emerging countries, capital flows …

This survey looks at the literature on factor extraction in the context of Dynamic Factor
Models (DFMs) fitted to multivariate systems of economic and financial variables. Many of …

Linear factor models are generally not identified. We provide sufficient conditions for
identification: under a sparsity assumption, we can estimate the individual loading vectors …

We develop a novel approach based on the canonical correlation analysis to identify the
number of the global factors in the multilevel factor model. We propose the two consistent …

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 …

This article develops an adaptive group lasso estimator for factor models with both global
and group-specific factors. The global factors can affect all variables, whereas the group …