Signalling corporate collapse using a dual classification scheme:Australian evidence

Hossari, Ghassan 2009, Signalling corporate collapse using a dual classification scheme:Australian evidence, International review of business research papers, vol. 5, no. 4, pp. 134-146.

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Title Signalling corporate collapse using a dual classification scheme:Australian evidence
Author(s) Hossari, Ghassan
Journal name International review of business research papers
Volume number 5
Issue number 4
Start page 134
End page 146
Publisher World Business Institute
Place of publication Melbourne, Vic.
Publication date 2009-06-04
ISSN 1832-9543
Summary Regardless of the technical procedure used in signalling corporate collapse, the bottom line rests on the predictive power of the corresponding statistical model. In that regard, it is imperative to empirically test the model using a data sample of both collapsed and non-collapsed companies. A superior model is one that successfully classifies collapsed and non-collapsed companies in their respective categories with a high degree of accuracy. Empirical studies of this nature have thus far done one of two things. (1) Some have classified companies based on a specific statistical modelling process. (2) Some have classified companies based on two (sometimes – but rarely – more than two) independent statistical modelling processes for the purposes of comparing one with the other. In the latter case, the mindset of the researchers has been – invariably – to pitch one procedure against the other. This paper raises the question, why pitch one statistical process against another; why not make the two procedures work together? As such, this paper puts forward an innovative dual-classification scheme for signalling corporate collapse: dual in the sense that it relies on two statistical procedures concurrently. Using a data sample of Australian publicly listed companies, the proposed scheme is tested against the traditional approach taken thus far in the pertinent literature. The results demonstrate that the proposed dual-classification scheme signals collapse with a higher degree of accuracy.
Language eng
Field of Research 150103 Financial Accounting
150201 Finance
Socio Economic Objective 970115 Expanding Knowledge in Commerce, Management, Tourism and Services
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
HERDC collection year 2009
Persistent URL http://hdl.handle.net/10536/DRO/DU:30021324

Document type: Journal Article
Collection: Deakin Graduate School of Business
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