Estimation of Weak Factor Models

Yoshimasa Uematsu and Takashi Yamagata

ISER Discussion Paper from Institute of Social and Economic Research, The University of Osaka

Abstract: In this paper, we propose a novel consistent estimation method for the approximate factor model of Chamberlain and Rothschild (1983), with large cross-sectional and time-series dimensions (N and T, respectively). Their model assumes that the r (≪N) largest eigenvalues of data covariance matrix grow as N rises without specifying each diverging rate. This is weaker than the typical assumption on the recent factor models, in which all the r largest eigenvalues diverge proportionally to N, and is frequently referred to as the weak factor models. We extend the sparse orthogonal factor regression (SOFAR) proposed by Uematsu et al. (2019) to consider consistent estimation of the weak factors structure, where the k-th largest eigenvalue grows proportionally to N^{α_{k}} with some unknown exponents 0

Date: 2019-04
New Economics Papers: this item is included in nep-ecm and nep-ets
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
https://www.iser.osaka-u.ac.jp/static/resources/docs/dp/2019/DP1053.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:dpr:wpaper:1053

Access Statistics for this paper

More papers in ISER Discussion Paper from Institute of Social and Economic Research, The University of Osaka Contact information at EDIRC.
Bibliographic data for series maintained by Librarian ().