High-dimensional dynamic factor models: a selective survey and lines of future research

TL;DR

This paper reviews high-dimensional dynamic factor models, focusing on their structure, assumptions, and potential future research directions, especially highlighting the role of singular ARMA models in theory and applications.

Contribution

It provides a selective survey emphasizing model classes, structure theory, and future research avenues rather than estimation techniques.

Findings

Highlights the importance of singular ARMA models in high-dimensional factor analysis

Identifies promising research directions in model structure and applications

Clarifies the theoretical foundations of high-dimensional dynamic factor models

Abstract

High-Dimensional Dynamic Factor Models are presented in detail: The main assumptions and their motivation, main results, illustrations by means of elementary examples. In particular, the role of singular ARMA models in the theory and applications of High-Dimensional Dynamic Factor Models is discussed.The emphasis of the paper is on model classes and their structure theory, rather than on estimation in the narrow sense. Our aim is not a comprehensive survey. Rather we try to point out promising lines of research and applications that have not yet been sufficiently developed.