A simple feasible procedure to fit models with high-dimensional fixed effects

In this article, we describe an iterative approach for the estimation of linear regression models with high-dimensional fixed effects. This approach is computationally intensive but imposes minimum memory requirements. We also show that the approach can be extended to nonlinear models and to more than two high-dimensional fixed effects.


Issue Date:
2010
Publication Type:
Journal Article
DOI and Other Identifiers:
st0212 (Other)
PURL Identifier:
http://purl.umn.edu/163398
Published in:
Stata Journal, Volume 10, Number 4
Page range:
628-649
Total Pages:
22

Record appears in:



 Record created 2017-04-01, last modified 2017-04-28

Fulltext:
Download fulltext
PDF

Rate this document:

Rate this document:
1
2
3
 
(Not yet reviewed)