Review of Quantitative Finance and Accounting

, Volume 28, Issue 1, pp 55–78 | Cite as

A re-evaluation of auditors’ opinions versus statistical models in bankruptcy prediction

  • Lili Sun


Existent empirical evidence on the relative performance of auditors’ going concern opinions versus statistical models in predicting bankruptcy is mixed. This study attempts to add new reliable evidence on this important issue by conducting the comparison based upon an improved statistical model. The improved statistical model incorporates some new developments advocated by recent bankruptcy prediction research (e.g., Shumway, 2001). First, the following non-traditional variables are added: a composite measure of financial distress, industry failure rate, abnormal stock returns, and market capitalization. Secondly, a hazard model is employed.

The prediction ability of the hazard model with incorporation of non-financial-ratio variables is superior to that of auditors’ going concern opinions in the holdout sample. This suggests that a well-developed statistical model could serve as a decision aid for auditors to better make going-concern judgments. Further analyses reveal some evidence that industry failure rate does not have a significant impact upon auditors’ going concern judgments as it should be; auditors could improve their going concern judgments by considering industry-level information in addition to firm-specific information. Finally, we find that auditors’ opinions do have incremental contribution beyond stock-market information and industry failure rate in predicting bankruptcy.


Bankruptcy prediction Going concern opinions Financial distress 



This paper is part of my dissertation. I am indebted to my dissertation co-chairs Michael Ettredge and Rajendra P. Srivastava for their guidance and valuable suggestions. I am also grateful to suggestions provided by Cheng-few Lee (the editor), an anonymous reviewer, James McKeown, Xiangdong Yang and participants at the University of Kansas AIS workshop. I thank the Whitcomb Center for Research in Financial Services for providing research support through use of the WRDS system.


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Copyright information

© Springer Science+Business Media, LLC 2006

Authors and Affiliations

  1. 1.Department of Accounting and Information Systems, Rutgersthe State University of New JerseyNew JerseyUK

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