Econometric Analysis of Large Factor Models

Posted: 18 Nov 2016

See all articles by Jushan Bai

Jushan Bai

Columbia University

Peng Wang

Hong Kong University of Science & Technology (HKUST) - Department of Economics

Date Written: October 2016

Abstract

Large factor models use a few latent factors to characterize the co-movement of economic variables in a high-dimensional data set. High dimensionality brings challenges as well as new insights into the advancement of econometric theory. Because of their ability to effectively summarize information in large data sets, factor models have been increasingly used in economics and finance. The factors, estimated from the high-dimensional data, can, for example, help improve forecasting, provide efficient instruments, control for nonlinear unobserved heterogeneity, and capture cross-sectional dependence. This article reviews the theory on estimation and statistical inference of large factor models. It also discusses important applications and highlights future directions.

Suggested Citation

Bai, Jushan and Wang, Peng, Econometric Analysis of Large Factor Models (October 2016). Annual Review of Economics, Vol. 8, pp. 53-80, 2016. Available at SSRN: https://ssrn.com/abstract=2870853 or http://dx.doi.org/10.1146/annurev-economics-080315-015356

Jushan Bai (Contact Author)

Columbia University ( email )

3022 Broadway
New York, NY 10027
United States

Peng Wang

Hong Kong University of Science & Technology (HKUST) - Department of Economics ( email )

Clear Water Bay
Kowloon, Hong Kong
China

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