Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/81877
Authors: 
Giordani, Paolo
Jacobson, Tor
von Schedvin, Erik
Villani, Mattias
Year of Publication: 
2011
Series/Report no.: 
Sveriges Riksbank Working Paper Series 256
Abstract: 
We demonstrate improvements in predictive power when introducing spline functions to take account of highly non-linear relationships between firm failure and earnings, leverage, and liquidity in a logistic bankruptcy model. Our results show that modeling excessive non-linearities yields substantially improved bankruptcy predictions, on the order of 70 to 90 percent, compared with a standard logistic model. The spline model provides several important and surprising insights into non-monotonic bankruptcy relationships. We find that low-leveraged and highly profitable firms are riskier than given by a standard model. These features are remarkably stable over time, suggesting that they are of a structural nature.
Subjects: 
bankruptcy risk model
micro-data
logistic spline regression
financial ratios
JEL: 
C41
G21
G33
G38
Document Type: 
Working Paper

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