EconPapers    
Economics at your fingertips  
 

Identification of the Linear Factor Model

Benjamin Williams ()

No 2018-002, Working Papers from The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting

Abstract: This paper provides several new results on identification of the linear factor model. The model allows for correlated latent factors and dependence among the idiosyncratic errors. I also illustrate identification under a dedicated measurement structure and other reduced rank restrictions. I use these results to study identification in a model with both observed covariates and latent factors. The analysis emphasizes the different roles played by restrictions on the error covariance matrix, restrictions on the factor loadings and the factor covariance matrix, and restrictions on the coefficients on covariates. The identification results are simple, intuitive, and directly applicable to many settings.

Keywords: Latent variables; factor analysis (search for similar items in EconPapers)
JEL-codes: C31 C36 C38 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2018-06
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (16) Track citations by RSS feed

Downloads: (external link)
https://www2.gwu.edu/~forcpgm/2018-002.pdf First version, 2018 (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:gwc:wpaper:2018-002

Access Statistics for this paper

More papers in Working Papers from The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting Contact information at EDIRC.
Bibliographic data for series maintained by GW Economics Department ().

 
Page updated 2023-02-02
Handle: RePEc:gwc:wpaper:2018-002