An Empirical Comparison of Variable Selection Methods in Competing Risks Model
Alessandra Amendola (),
Marialuisa Restaino () and
Luca Sensini ()
Additional contact information
Alessandra Amendola: University of Salerno, Department of Economics and Statistics
Marialuisa Restaino: University of Salerno, Department of Economics and Statistics
Luca Sensini: University of Salerno, Department of Business Studies and Research
A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2014, pp 13-25 from Springer
Abstract:
Abstract The variable selection is a challenging task in statistical analysis. In many real situations, a large number of potential predictors are available and a selection among them is recommended. For dealing with this problem, the automated procedures are the most commonly used methods, without taking into account their drawbacks and disadvantages. To overcome them, the shrinkage methods are a good alternative. Our aim is to investigate the performance of some variable selection methods, focusing on a statistical procedure suitable for the competing risks model. In this theoretical setting, the same variables might have different degrees of influence on the risks due to multiple causes and this has to be taken into account in the choice of the “best” subset. The proposed procedure, based on shrinkage techniques, is evaluated by means of empirical analysis on a data-set of financial indicators computed from a sample of industrial firms annual reports.
Keywords: Financial Distress; Variable Selection Method; Compete Risk Model; Shrinkage Method; Distressed Firm (search for similar items in EconPapers)
Date: 2014
References: Add references at CitEc
Citations:
There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.
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:spr:sprchp:978-3-319-02499-8_2
Ordering information: This item can be ordered from
http://www.springer.com/9783319024998
DOI: 10.1007/978-3-319-02499-8_2
Access Statistics for this chapter
More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().