caa a22 4500 463187571 CHVBK 20180406164858.0 cr unu---uuuuu 170326e20070101xx s 000 0 eng 10.1007/s11156-006-0003-x doi (NATIONALLICENCE)springer-10.1007/s11156-006-0003-x Sun Lili Department of Accounting and Information Systems, Rutgers, the State University of New Jersey, Ackerson Hall, Room 317, 180 University Ave, Newark, 07102-1897, New Jersey, NJ, UK aut A re-evaluation of auditors' opinions versus statistical models in bankruptcy prediction [Elektronische Daten] [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. Springer Science+Business Media, LLC, 2006 Bankruptcy prediction nationallicence Going concern opinions nationallicence Financial distress nationallicence Review of Quantitative Finance and Accounting Kluwer Academic Publishers-Plenum Publishers; http://www.springer-ny.com 28/1(2007-01-01), 55-78 0924-865X 28:1<55 2007 28 11156 https://doi.org/10.1007/s11156-006-0003-x text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11156-006-0003-x text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Sun Lili Department of Accounting and Information Systems, Rutgers, the State University of New Jersey, Ackerson Hall, Room 317, 180 University Ave, Newark, 07102-1897, New Jersey, NJ, UK aut NATIONALLICENCE 773 0- Review of Quantitative Finance and Accounting Kluwer Academic Publishers-Plenum Publishers; http://www.springer-ny.com 28/1(2007-01-01), 55-78 0924-865X 28:1<55 2007 28 11156 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer