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A Reexamination of Auditor versus Model Accuracy within the Context of the Going†Concern Opinion Decision

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  • WILLIAM HOPWOOD
  • JAMES C. McKEOWN
  • JANE F. MUTCHLER

Abstract

. The Cohen Commission and previous research have suggested that auditors' opinions are inferior indicators of bankruptcy relative to the predictions of statistical models. This research reexamines this question in light of two important considerations that make the comparison between audit opinions and model predictions considerably more reflective of the auditors' real†world decision environment. First, the sample is partitioned into stressed and nonstressed observations and the importance of doing so is demonstrated; second, the statistical models and the forecast errors are adjusted so that they reflect the proportion of bankrupt firms actually faced by auditors. The empirical results provide convincing evidence suggesting that the notion established in previous research that auditors' opinions are interior to models in predicting bankruptcy is unfounded. It should be noted, however, that neither the auditors' opinions nor the bankruptcy prediction model are very good predictors of bankruptcy when population proportions, differences in misclassification costs, and financial stress levels are considered. Résumé. Les travaux de recherche de la Commission Cohen et d'autres travaux qui les ont précédés semblent indiquer que les opinions des vérificateurs sont des indicateurs de faillite moins efficaces que les prédictions des modèles statistiques. Les auteurs se penchent à leur tour sur cette question, à la lumière de deux éléments importants qui font en sorte que la comparaison entre les opinions des vérificateurs et les modèles prévisionnels s'inscrit beaucoup plus dans le contexte décisionnel véritable dans lequel travaillent les vérificateurs. D'abord, l'échantillon est scindé en deux groupes d'observations selon la présence ou l'absence de contrainte financière, partage dont les auteurs expliquent l'importance; ensuite, les modèles statistiques et les erreurs prévisionnelles sont ajustés de manière & refléter la proportion des sociétés dont la faillite a été envisagée par le vérificateur. Les résultats empiriques démontrent de façon probante que les conclusions tirées des travaux précédents selon lesquelles les opinions des vérificateurs sont moins efficaces que les modèles en matière de prévision des faillites ne sont pas fondées. Il convient de noter, cependant, que ni les opinions des vérificateurs ni les modèles prévisionnels ne sont des prédicteurs très efficaces des faillites si l'on tient compte des proportions de la population, des différences dans le coût des erreurs de classification et du niveau de contrainte financière.

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  • WILLIAM HOPWOOD & JAMES C. McKEOWN & JANE F. MUTCHLER, 1994. "A Reexamination of Auditor versus Model Accuracy within the Context of the Going†Concern Opinion Decision," Contemporary Accounting Research, John Wiley & Sons, vol. 10(2), pages 409-431, March.
  • Handle: RePEc:wly:coacre:v:10:y:1994:i:2:p:409-431
    DOI: 10.1111/j.1911-3846.1994.tb00400.x
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    References listed on IDEAS

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    1. Frank D. Hodge & Roger D. Martin & Jamie H. Pratt, 2006. "Audit Qualifications of Income†Decreasing Accounting Choices," Contemporary Accounting Research, John Wiley & Sons, vol. 23(2), pages 369-394, June.
    2. Agustín J. Sánchez-Medina & Félix Blázquez-Santana & Jesús B. Alonso, 2019. "Do Auditors Reflect the True Image of the Company Contrary to the Clients’ Interests? An Artificial Intelligence Approach," Journal of Business Ethics, Springer, vol. 155(2), pages 529-545, March.
    3. Wu, Chloe Yu-Hsuan & Hsu, Hwa-Hsien & Haslam, Jim, 2016. "Audit committees, non-audit services, and auditor reporting decisions prior to failure," The British Accounting Review, Elsevier, vol. 48(2), pages 240-256.
    4. Jeroen van Raak & Erik Peek & Roger Meuwissen & Caren Schelleman, 2020. "The effect of audit market structure on audit quality and audit pricing in the private‐client market," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 47(3-4), pages 456-488, March.
    5. Donghui Wu & Qing Ye, 2020. "Public Attention and Auditor Behavior: The Case of Hurun Rich List in China," Journal of Accounting Research, Wiley Blackwell, vol. 58(3), pages 777-825, June.
    6. Ahsan Habib & Mabel D' Costa & Hedy Jiaying Huang & Md. Borhan Uddin Bhuiyan & Li Sun, 2020. "Determinants and consequences of financial distress: review of the empirical literature," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(S1), pages 1023-1075, April.
    7. Kim, Hyonok & Fukukawa, Hironori & Routledge, James, 2020. "A comparison of management and auditor going concern risk disclosure: Evidence from regulatory change in Japan," Working Paper Series 234, Management Innovation Research Center, School of Business Administration, Hitotsubashi University Business School.
    8. Desai, Vikram & Bucaro, Anthony C. & Kim, Joung W. & Srivastava, Rajendra & Desai, Renu, 2023. "Toward a better expert system for auditor going concern opinions using Bayesian network inflation factors," International Journal of Accounting Information Systems, Elsevier, vol. 49(C).
    9. Ekaterina Tzvetanova, 2019. "Adaptation of the Altman’s Corporate Insolvency Prediction Model – The Bulgarian Case," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 125-142.
    10. Klaus Ruhnke, 2003. "Nutzen von Abschlussprüfungen: Bezugsrahmen und Einordnung empirischer Studien," Schmalenbach Journal of Business Research, Springer, vol. 55(3), pages 250-280, May.
    11. Wei Ting & Sin‐Hui Yen & Chien‐Liang Chiu, 2008. "The Influence of Qualified Foreign Institutional Investors on the Association between Default Risk and Audit Opinions: Evidence from the Chinese Stock Market," Corporate Governance: An International Review, Wiley Blackwell, vol. 16(5), pages 400-415, September.
    12. Chrysovalantis Gaganis, 2009. "Classification techniques for the identification of falsified financial statements: a comparative analysis," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 16(3), pages 207-229, July.
    13. Mary Jane Lenard & Pervaiz Alam & David Booth & Gregory Madey, 2001. "Decision‐making capabilities of a hybrid system applied to the auditor's going‐concern assessment," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 10(1), pages 1-23, March.
    14. Sergio Davalos & Fei Leng & Ehsan H. Feroz & Zhiyan Cao, 2014. "Designing An If–Then Rules‐Based Ensemble Of Heterogeneous Bankruptcy Classifiers: A Genetic Algorithm Approach," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(3), pages 129-153, July.
    15. Khalil Feghali & Reine Najem & Beverly Dawn Metcalfe, 2022. "Financial Auditing During Crisis: Assessing and Reporting Fraud and Going Concern Risk in Lebanon," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 21(4), pages 575-603, December.
    16. Gregory D. Kane & Frederick M. Richardson & Nancy L. Meade, 1998. "Rank Transformations and the Prediction of Corporate Failure," Contemporary Accounting Research, John Wiley & Sons, vol. 15(2), pages 145-166, June.
    17. Dennis M. O'Reilly & Robert A. Leitch & Brad Tuttle, 2006. "An Experimental Test of the Interaction of the Insurance and Information†Signaling Hypotheses in Auditing," Contemporary Accounting Research, John Wiley & Sons, vol. 23(1), pages 267-289, March.
    18. Dan Dhaliwal & Paul N. Michas & Vic Naiker & Divesh Sharma, 2020. "Greater Reliance on Major Customers and Auditor Going‐Concern Opinions," Contemporary Accounting Research, John Wiley & Sons, vol. 37(1), pages 160-188, March.
    19. Elizabeth Gutierrez & Jake Krupa & Miguel Minutti-Meza & Maria Vulcheva, 2020. "Do going concern opinions provide incremental information to predict corporate defaults?," Review of Accounting Studies, Springer, vol. 25(4), pages 1344-1381, December.
    20. Ting Zhang & So Yean Kwack & Yi Si & Gaoliang Tian, 2023. "Non‐GAAP earnings reporting following going‐concern opinions," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(3), pages 3217-3252, September.
    21. Murugan Anandarajan & Picheng Lee & Asokan Anandarajan, 2001. "Bankruptcy prediction of financially stressed firms: an examination of the predictive accuracy of artificial neural networks," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 10(2), pages 69-81, June.
    22. Sanoran, Kanyarat (Lek), 2018. "Auditors’ going concern reporting accuracy during and after the global financial crisis," Journal of Contemporary Accounting and Economics, Elsevier, vol. 14(2), pages 164-178.
    23. Sarfraz A. Khan & Gerald Lobo & Emeka T. Nwaeze, 2017. "Public re-release of going-concern opinions and market reaction," Accounting and Business Research, Taylor & Francis Journals, vol. 47(3), pages 237-267, April.
    24. Geiger, Marshall A. & Basioudis, Ilias G. & DeLange, Paul, 2022. "The effect of non-audit fees and industry specialization on the prevalence and accuracy of auditor’s going-concern reporting decisions," Journal of International Accounting, Auditing and Taxation, Elsevier, vol. 47(C).
    25. SARUYAMA Sumio & Peng XU, 2019. "Going Concern Notes, Downsizing, and Exit," Discussion papers 19001, Research Institute of Economy, Trade and Industry (RIETI).

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