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Bankruptcy prediction in Norway: a comparison study

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  • Rada Dakovic
  • Claudia Czado
  • Daniel Berg
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    Abstract

    In this article we develop statistical models for bankruptcy prediction of Norwegian firms in the limited liability sector using annual balance sheet information. We fit generalized linear, generalized linear mixed and Generalized Additive Models (GAM) in a discrete hazard setting. It is demonstrated that careful examination of the functional relationship between the explanatory variables and the probability of bankruptcy enhances the models' forecasting performance. Using information on the industry sector we model the unobserved heterogeneity between different sectors through an industry-specific random factor in the generalized linear mixed model. The models developed are shown to outperform the model with Altman's variables.

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    File URL: http://www.informaworld.com/openurl?genre=article&doi=10.1080/13504850903299594&magic=repec&7C&7C8674ECAB8BB840C6AD35DC6213A474B5
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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal Applied Economics Letters.

    Volume (Year): 17 (2010)
    Issue (Month): 17 ()
    Pages: 1739-1746

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    Handle: RePEc:taf:apeclt:v:17:y:2010:i:17:p:1739-1746

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    Cited by:
    1. Giordani, Paolo & Jacobson, Tor & von Schedvin , Erik & Villani, Mattias, 2011. "Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios," Working Paper Series 256, Sveriges Riksbank (Central Bank of Sweden).
    2. Martin Kukuk & Michael Rönnberg, 2013. "Corporate credit default models: a mixed logit approach," Review of Quantitative Finance and Accounting, Springer, vol. 40(3), pages 467-483, April.
    3. Milovan Stanisic & Danka Stefanovic & Nada Arezina & Vule Mizdrakovic, 2013. "Analysis of auditor`s reports and bankruptcy risk in banking sector in the Republic of Serbia," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 15(34), pages 431-441, June.

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