Large-Dimensional Dynamic Factor Models in Real-Time: A Survey

31 Pages Posted: 20 Oct 2014

See all articles by Matteo Luciani

Matteo Luciani

Board of Governors of the Federal Reserve System

Date Written: October 2014

Abstract

In this paper I review the literature on Large-Dimensional Dynamic Factor Models for real-time applications. I first present the Dynamic Factor model, the implications of using large-dimensional databases, and the challenges of real-time applications. Then, I discuss how the literature has solved these problems, and I present numerous empirical applications that show the usefulness of these models in both constructing business cycle indicators, and predicting economic activity. Finally, I present two recent extensions of the Dynamic Factor model, one in a Bayesian and one in a non-stationary setting.

Keywords: Large Dimensional Dynamic Factor models, Real-time forecasting, business cycle indicators

JEL Classification: C32, C53, E32

Suggested Citation

Luciani, Matteo, Large-Dimensional Dynamic Factor Models in Real-Time: A Survey (October 2014). Available at SSRN: https://ssrn.com/abstract=2511872 or http://dx.doi.org/10.2139/ssrn.2511872

Matteo Luciani (Contact Author)

Board of Governors of the Federal Reserve System ( email )

20th Street and Constitution Avenue NW
Washington, DC 20551
United States

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