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Predicting Auditor Switches By Applying Data Mining


  • Efstathios KIRKOS


Auditor dismissals are considered to be a threat to audit quality. Several studies have examined auditor switches by applying typical statistical analysis. In the present study we deal with the auditor switching problem by applying data mining methodologies. Publicly available financial statement and auditing data are used as predictors. The optimum vector of significant input variables is defined by employing feature selection. A number of data mining classification methods are used to develop models capable of predicting the auditor change cases. The methods are compared against the widely used Logistic Regression. According to the results, all the data mining methods outperform Logistic Regression. Significant factors associated with auditor changes are revealed. The results can be useful to auditing firms, managers, investors, creditors and corporate regulators.

Suggested Citation

  • Efstathios KIRKOS, 2012. "Predicting Auditor Switches By Applying Data Mining," Journal of Applied Economic Sciences, Spiru Haret University, Faculty of Financial Management and Accounting Craiova, vol. 7(3(21)/ Fa), pages 246-261.
  • Handle: RePEc:ush:jaessh:v:7:y:2012:i:3(21)_fall2012:p:246

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    References listed on IDEAS

    1. Mohammad Hudaib & T.E. Cooke, 2005. "The Impact of Managing Director Changes and Financial Distress on Audit Qualification and Auditor Switching," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 32(9-10), pages 1703-1739.
    2. Johnson, W. Bruce & Lys, Thomas, 1990. "The market for audit services : Evidence from voluntary auditor changes," Journal of Accounting and Economics, Elsevier, vol. 12(1-3), pages 281-308, January.
    3. Branson, Joel & Breesch, Diane, 2004. "Referral as a determining factor for changing auditors in the Belgian auditing market: An empirical study," The International Journal of Accounting, Elsevier, vol. 39(3), pages 307-326.
    4. Krishnan, Jagan & Stephens, Ray G., 1995. "Evidence on opinion shopping from audit opinion conservatism," Journal of Accounting and Public Policy, Elsevier, vol. 14(3), pages 179-201.
    5. David H. Sinason & Jefferson P. Jones & Sandra Waller Shelton, 2001. "An Investigation of Auditor and Client Tenure," American Journal of Business, Emerald Group Publishing, vol. 16(2), pages 31-40.
    6. DeFond, Mark L. & Subramanyam, K. R., 1998. "Auditor changes and discretionary accruals," Journal of Accounting and Economics, Elsevier, vol. 25(1), pages 35-67, February.
    7. repec:bla:joares:v:18:y:1980:i:1:p:109-131 is not listed on IDEAS
    8. DeAngelo, Linda Elizabeth, 1981. "Auditor size and audit quality," Journal of Accounting and Economics, Elsevier, vol. 3(3), pages 183-199, December.
    9. Lennox, Clive, 2000. "Do companies successfully engage in opinion-shopping? Evidence from the UK," Journal of Accounting and Economics, Elsevier, vol. 29(3), pages 321-337, June.
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    More about this item


    Auditor switching; auditing; data mining;

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • M42 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Auditing


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