On the determination of the number of factors using information criteria with data-driven penalty
(2017) In Statistical Papers 58(1). p.161-184- Abstract
As is well known, when using an information criterion to select the number of common factors in factor models the appropriate penalty is generally indetermine in the sense that it can be scaled by an arbitrary constant, c say, without affecting consistency. In an influential paper, Hallin and Liška (J Am Stat Assoc102:603–617, 2007) proposes a data-driven procedure for selecting the appropriate value of c. However, by removing one source of indeterminacy, the new procedure simultaneously creates several new ones, which make for rather complicated implementation, a problem that has been largely overlooked in the literature. By providing an extensive analysis using both simulated and real data, the current paper fills this gap.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/bc0fb0f2-d854-40f5-9b9e-54f102046980
- author
- Westerlund, Joakim LU and Mishra, Sagarika
- organization
- publishing date
- 2017-03-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Common factor model, Data-driven penalty, Information criterion, Panel data
- in
- Statistical Papers
- volume
- 58
- issue
- 1
- pages
- 24 pages
- publisher
- Springer
- external identifiers
-
- scopus:84930348545
- wos:000394997000009
- ISSN
- 0932-5026
- DOI
- 10.1007/s00362-015-0692-0
- language
- English
- LU publication?
- yes
- id
- bc0fb0f2-d854-40f5-9b9e-54f102046980
- date added to LUP
- 2017-03-13 09:28:28
- date last changed
- 2024-03-17 10:17:17
@article{bc0fb0f2-d854-40f5-9b9e-54f102046980,
abstract = {{<p>As is well known, when using an information criterion to select the number of common factors in factor models the appropriate penalty is generally indetermine in the sense that it can be scaled by an arbitrary constant, c say, without affecting consistency. In an influential paper, Hallin and Liška (J Am Stat Assoc102:603–617, 2007) proposes a data-driven procedure for selecting the appropriate value of c. However, by removing one source of indeterminacy, the new procedure simultaneously creates several new ones, which make for rather complicated implementation, a problem that has been largely overlooked in the literature. By providing an extensive analysis using both simulated and real data, the current paper fills this gap.</p>}},
author = {{Westerlund, Joakim and Mishra, Sagarika}},
issn = {{0932-5026}},
keywords = {{Common factor model; Data-driven penalty; Information criterion; Panel data}},
language = {{eng}},
month = {{03}},
number = {{1}},
pages = {{161--184}},
publisher = {{Springer}},
series = {{Statistical Papers}},
title = {{On the determination of the number of factors using information criteria with data-driven penalty}},
url = {{http://dx.doi.org/10.1007/s00362-015-0692-0}},
doi = {{10.1007/s00362-015-0692-0}},
volume = {{58}},
year = {{2017}},
}