Determining the number of factors when the number of factors can increase with sample size Academic Article

abstract

• 2016 Elsevier B.V. Correctly specifying the number of factors (r) is a fundamental issue for the application of factor models. In this paper we develop an econometric method to estimate the number of factors in factor models of large dimensions where the number of factors is allowed to increase as the two dimensions, cross-section size (N) and time period (T) increase. Using similar information criteria as proposed by Bai and Ng (2002), we show that the number of factors can be consistently estimated using the criteria. We propose a new procedure that avoids over estimating the number of factors while allowing for one to search for possible number of factors over a wide range of positive integers so that it also avoids underestimation of the number of factors. We conduct Monte-Carlo simulation to investigate the finite sample properties of the proposed approach.

authors

• Li, Qi

published proceedings

• JOURNAL OF ECONOMETRICS

author list (cited authors)

• Li, H., Li, Q. i., & Shi, Y.

citation count

• 32

complete list of authors

• Li, Hongjun||Li, Qi||Shi, Yutang

publication date

• January 2017

publisher

• Elsevier  Publisher

published in

• Journal of Econometrics  Journal

keywords

• Factor Analysis
• Increasing Number Of Factors
• Information Criteria
• Principal Components

Digital Object Identifier (DOI)

• 10.1016/j.jeconom.2016.06.003

start page

• 76

end page

• 86

volume

• 197

issue

• 1

URL

• http://dx.doi.org/10.1016/j.jeconom.2016.06.003