Estimation of Sparsity-Induced Weak Factor Models
Yoshimasa Uematsu and
Takashi Yamagata
Journal of Business & Economic Statistics, 2022, vol. 41, issue 1, 213-227
Abstract:
This article investigates estimation of sparsity-induced weak factor (sWF) models, with large cross-sectional and time-series dimensions (N and T, respectively). It assumes that the kth largest eigenvalue of a data covariance matrix grows proportionally to Nαk with unknown exponents 0
Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (9)
Downloads: (external link)
http://hdl.handle.net/10.1080/07350015.2021.2008405 (text/html)
Access to full text is restricted to subscribers.
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:taf:jnlbes:v:41:y:2022:i:1:p:213-227
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UBES20
DOI: 10.1080/07350015.2021.2008405
Access Statistics for this article
Journal of Business & Economic Statistics is currently edited by Eric Sampson, Rong Chen and Shakeeb Khan
More articles in Journal of Business & Economic Statistics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().