Predicting Railroad Bankruptcies in America
The purpose of this paper is to discuss the urgent need for an early-warning system covering the historically failure-prone railroad industry and to develop a tool for providing such a system. A multivariate statistical technique called linear discriminant analysis is utilized to identify and quantify those financial measures which are effective indicators of bankruptcies. A model which combined several financial statement ratios proved to be extremely accurate in predicting railroad bankruptcies at one and two annual financial statement dates prior to failure. Subsequent tests on additional railroad samples confirm the validity of the model. Finally, currently existing railroads in America are assessed for their bankruptcy potential by this diagnostic model.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Volume (Year): 4 (1973)
Issue (Month): 1 (Spring)
|Contact details of provider:|| Web page: http://www.rje.org|
|Order Information:||Web: https://editorialexpress.com/cgi-bin/rje_online.cgi|
When requesting a correction, please mention this item's handle: RePEc:rje:bellje:v:4:y:1973:i:spring:p:184-211. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()
If references are entirely missing, you can add them using this form.