Joakim Westerlund
Professor, Programme director – Master of Data Analytics and Business Economics
On the determination of the number of factors using information criteria with data-driven penalty
Author
Summary, in English
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.
Department/s
- Department of Economics
Publishing year
2017-03-01
Language
English
Pages
161-184
Publication/Series
Statistical Papers
Volume
58
Issue
1
Document type
Journal article
Publisher
Springer
Topic
- Economics
- Probability Theory and Statistics
Keywords
- Common factor model
- Data-driven penalty
- Information criterion
- Panel data
Status
Published
ISBN/ISSN/Other
- ISSN: 0932-5026