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Pustylnick Igor (Far Eastern Federal University Vladivostok, Russia; Conestoga College Kitchener, Canada), Temchenko Oksana (Far Eastern Federal University Vladivostok, Russia), Gubarkov Sergey (Far Eastern Federal University Vladivostok, Russia)
Estimating the Influence of Accounting Variables Change on Earnings Management Detection
Journal of International Studies, 2017, vol. 10, nr 1, s. 110-122, rys., tab., bibliogr. 35 poz.
Słowa kluczowe
Zarządzanie zyskami, Analiza Du Ponta, Oszustwa w sprawozdaniach finansowych
Earnings management, DuPont analysis, Fraud in the financial statements
Klasyfikacja JEL: G31, M33
Standard earnings management detection is performed using two routes: real earnings management (connected with inventory and expenses manipulations) and accrual earnings management (connected with revenue and accounts receivables manipulations). Neither of these two detection algorithms attempts to quantify earnings management and connect it with the infractions committed by the companies, charged by the regulator (in this case - U.S. SEC). In many known cases of revenue manipulation, it is not possible to say whether real or accrual based earnings management was used. In this research, we look at the cases of financial statement fraud, namely one of the most common variations - revenue manipulation, from the perspective of the practitioner and propose the way of detection and quantification of such manipulations. In order to distinguish the cases of earnings management, we use the components of DuPont formula. In addition, we also look at the accounting variables used in the calculation of the detection criterion and determine which ones of them play the main role in revenue manipulations. (original abstract)
Pełny tekst
  1. Achleitner, A.-K., Günther, N., Kaserer, C., & Siciliano, G. (2014). Real Earnings Management and Accrual-based Earnings Management in Family Firms. European Accounting Review, 23(3), 431-461. doi:10.1080/09638180.2014.895620
  2. Alexeev, M., & Kim, S. (2008). The Korean financial crisis and the soft budget constraint. Journal of Economic Behavior & Organization, 68(1), 178-193.
  3. Alhadab, M., Clacher, I., & Keasey, K. (2016). A Comparative Analysis of Real and Accrual Earnings Management around Initial Public Offerings under Different Regulatory Environments. Journal of Business Finance & Accounting, 43(7-8), 849-871.
  4. Altman, E. (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy. Journal of Finance. doi:10.1111/j.1540-6261.1968.tb00843.x
  5. Austin, B. J., Haskins, M. E., Ferris, K. R., Sack, R. J., & Allen, B. R. (2000). Financial Accounting and Reporting. Second Canadian Edition. Toronto, ON, Canada: McGraw-Hill.
  6. Bauman, M. P. (2014). Forecasting operating profitability with DuPont analysis: Further evidence. Review of Accounting and Finance, 13(2), 191-205.
  7. Beneish, M. (1997). Detecting GAAP violation: implications for assessing earnings management among firms with extreme financial performance. Journal of Accounting and Public Policy, 16(3), 271-309. doi:
  8. Beneish, M. (2001). Earnings Management: A Perspective. Managerial Finance, 27(12), 3-17.
  9. Beneish, M., Press, E., & Vargus, M. E. (2012). Insider Trading and Earnings Management in Distressed Firms. Contemporary Accounting Research, 29(1), 191-220.
  10. Bruns, W. J., & Merchant, K. A. (1990). The Dangerous Morality of Managing Earnings. Management Accounting, 72(2), 22-25.
  11. Dechow, P. M., Ge, W., Larson, C. R., & Sloan, R. G. (2011). Predicting Material Accounting Misstatements. Contemporary Accounting Research, 28(1), 17-82.
  12. Dechow, P. M., Hutton, A. P., Kim, J. H., & Sloan, R. G. (2012). Detecting Earnings Management: A New Approach. Journal of Accounting Research, 50(2), 275-334. doi:10.1111/j.1475-679X.2012.00449.x
  13. Dechow, P. M., & Skinner, D. J. (2000). Earnings Management: Reconciling the Views of Accounting Academics, Practitioners and Regulators. Accounting Horizons, 14(2), 235-250. doi:
  14. Dechow, P. M., Sloan, R. G., & Sweeney, A. P. (1995). Detecting Earnings Management. The Accounting Review, 70(2), 193-225.
  15. Escalada, J. (2011). 45 Dividend Stocks With Good Credit Scores. Retrieved August 29,2012, from
  16. Ferrer, R. C., & Ferrer, G. J. (2016). Earnings management indicators and their impact on inventory turnover under food, beverage and tobacco sector: a thorough study using simultaneous equations model. Academy of Accounting & Financial Studies Journal, 20(2), 93-103.
  17. Fess, P. E., & Warren, C. S. (1993). Accounting Principles, 17e. Cincinnati, OH: South-Western Publishing Co.
  18. Gerakos, J. (2012). Discussion of Detecting Earnings Management: A New Approach. Journal of Accounting Research, 50(2), 335-347. doi:10.1111/j.1475-679X.2012.00452.x
  19. Jansen, I. P., Ramnath, S., & Yohn, T. L. (2012). A Diagnostic for Earnings Management Using Changes in Asset Turnover and Profit Margin. Contemporary Accounting Research, 29(1), 221-251. doi:10.1111/j.1911-3846.2011.01093.x
  20. Jones, J. J. (1991). Earnings Management Following Import Relief Investigations. Journal of Accounting Research, 29(2), 193-228. doi:10.2307/2491047
  21. Kirkos, E., Spathis, C., & Manopoulos, Y. (2007). Data Mining techniques for the detection of fraudulent financial statements Expert Systems with Applications, 92(4), 995-1003.
  22. Lang, M., Smith Raedy, J., & Wilson, W. (2006). Earnings management and cross listing: Are reconciled earnings comparable to US earnings? Journal of Accounting and Economics, 42(1-2), 255-283. doi:10.1016/j.jacceco.2006.04.005
  23. Leggett, D. M., Parsons, L. M., & Reitenga, A. L. (2016). Real Earnings Management and Subsequent Operating Performance. IUP Journal of Operations Management, 15(4), 7-32.
  24. Lenard, M. J., & Alam, P. (2009). An Historical Perspective on Fraud Detection: From Bankruptcy Models to Most Effective Indicators of Fraud in Recent Incidents. Journal of Forensic & Investigative Accounting, Vol 1, Iss 1.
  25. Marzcewski, D. C., & Akers, M. D. (2005). CPA's Perception on the impact of SAS 99. CPA Journal, 75(6), 38-40.
  26. McKee, T. E. (2005). Earnings Management: An Executive Perspective, 1st Edition: Cengage Learning.
  27. Park, Y. W., & Shin, H.-H. (2004). Board composition and earnings management in Canada. Journal of Corporate Finance, 10(3), 431-457.
  28. Persons, O. A. (2011). Using Financial Statement Data to Identify Factors Associated with Fraudulent Financial Reporting. Journal of Applied Business Research, 11(3).
  29. Pustylnick, I. (2016). Using Z-Score in detection of revenue manipulations. Paper presented at the 21-st International Scientific Conference Economics and Management, Brno, Czech Republic. Retrieved from:
  30. Pustylnik, E. I. (1968). Statistical methods of analisys and processing of observations. Moscow: Nauka Publishing.
  31. Roychowdhury, S. (2006). Earnings management through real activities manipulation. Journal of Accounting and Economics, 42(3), 335-370. doi:10.1016/j.jacceco.2006.01.002
  32. Spathis, C. (2002). Detecting false financial statements using published data: some evidence from Greece. Managerial Auditing Journal, 17(4), 179-191.
  33. Taylor, G. K., & Xu, R. Z. (2010). Consequences of real earnings management on subsequent operating performance. Research in Accounting Regulation, 22(2), 128-132.
  34. Tsipouridou, M., & Spathis, C. (2014). Audit opinion and earnings management: Evidence from Greece. Accounting Forum, 38(1), 38-54. doi:10.1016/j.accfor.2013.09.002
  35. Urri, M. (2002, July 10). Those US scandals couldnt happen here... could they?: Stricter accounting standards make another enron less likely in the UK, reports maggie urry. but vigilance is still needed. Financial Times, 25-25.
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