EconPapers    
Economics at your fingertips  
 

Identification of matrix-valued factor models

Ying Lun Cheung

Economics Bulletin, 2024, vol. 44, issue 2, 550 - 556

Abstract: The analysis of matrix-valued time series has been popular in recent years. When the dimensions of the matrix observations are large, one can use the matrix-valued factor model to extract information from the data. However, as in standard factor analysis, the common factors and factor loadings are not separately identifiable. This note considers two sets of identification restrictions that help exactly identify the model.

Keywords: Approximate factor models; Matrix-valued time series; Principal components; 2DSVD (search for similar items in EconPapers)
JEL-codes: C3 G1 (search for similar items in EconPapers)
Date: 2024-06-30
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.accessecon.com/Pubs/EB/2024/Volume44/EB-24-V44-I2-P40.pdf (application/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:ebl:ecbull:eb-23-00461

Access Statistics for this article

More articles in Economics Bulletin from AccessEcon
Bibliographic data for series maintained by John P. Conley ().

 
Page updated 2025-03-19
Handle: RePEc:ebl:ecbull:eb-23-00461