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Journal of Management and Governance

, Volume 22, Issue 4, pp 863–890 | Cite as

External audit and bankruptcy prediction

  • Velia Gabriella CenciarelliEmail author
  • Giulio Greco
  • Marco Allegrini
Article
  • 429 Downloads

Abstract

In this paper, we investigate the relationship between external auditor characteristics and the likelihood of bankruptcy. We use a sample of US public companies to analyse whether auditor attributes are associated with default. We also test whether the inclusion of such attributes in bankruptcy prediction models improves their predictive ability. We find that firms audited by industry-expert auditors, large audit firms and long-tenured auditors are less likely to default. Firms with higher audit fees are more likely to default. Our results also show that the inclusion of auditor attributes significantly increases the predictive ability of bankruptcy prediction models. This paper contributes to the literature about auditing and bankruptcy prediction. Our results suggest that the auditor attributes can provide predictive signals concerning a default risk and that an external audit can play a relevant role in early warnings of financial distress. Our study also suggests that bankruptcy prediction models can become more effective if they are complemented with audit data. Our results are of interest to market participants, auditors, regulating authorities, banks and other financial institutions that are interested in credit risk assessment.

Keywords

Bankruptcy prediction External audit Auditor characteristics 

Notes

Acknowledgements

The Authors gratefully acknowledge the helpful comments of two anonymous reviewers. The Authors gratefully acknowledge the financial support of the SIR program of the Italian Ministry of Education, University and Research (MIUR). The paper is the result of a joint effort of the Authors. In particular, Marco Allegrini wrote the Sect. 1, Giulio Greco wrote the Sect. 5, while Velia Gabriella Cenciarelli wrote the Sects. 24.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Economics and ManagementUniversity of PisaPisaItaly

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