The Detection of Earnings Manipulation

Presented are a profile of a sample of earnings manipulators, their distinguishing characteristics, and a suggested model for detecting manipulation. The model's variables are designed to capture either the financial statement distortions that can result from manipulation or preconditions that might prompt companies to engage in such activity. The results suggest a systematic relationship between the probability of manipulation and some financial statement variables. This evidence is consistent with the usefulness of accounting data in detecting manipulation and assessing the reliability of reported earnings. The model identifies approximately half of the companies involved in earnings manipulation prior to public discovery. Because companies that are discovered manipulating earnings see their stocks plummet in value, the model can be a useful screening device for investment professionals. The screening results, however, require determination of whether the distortions in the financial statement numbers r...

[1]  M. D. Beneish,et al.  Incentives and Penalties Related to Earnings Overstatements that Violate GAAP , 1999 .

[2]  Thornton L. O'glove,et al.  Quality of Earnings , 1998 .

[3]  M. D. Beneish,et al.  Detecting GAAP violation: implications for assessing earnings management among firms with extreme financial performance , 1997 .

[4]  B. Lev,et al.  Fundamental Information Analysis , 1993 .

[5]  M. D. Beneish,et al.  Costs of technical violation of accounting-based debt covenants , 1993 .

[6]  Martin S. Fridson,et al.  Financial Statement Analysis: A Practitioner's Guide , 1991 .

[7]  J. Jones.  Earnings Management During Import Relief Investigations , 1991 .

[8]  I. Kellogg,et al.  Fraud, window dressing, and negligence in financial statements , 1991 .

[9]  Ehsan H. Feroz,et al.  The Financial and Market Effects of the SEC's Accounting and Auditing Enforcement Releases , 1991 .

[10]  Charles F. Manski,et al.  Estimation of Response Probabilities From Augmented Retrospective Observations , 1985 .

[11]  M. Paul.  of Bonus Schemes on Accounting Decisions, Journal of Accounting and Economics , 85-107. , 1985 .

[12]  M. Zmijewski.  METHODOLOGICAL ISSUES RELATED TO THE ESTIMATION OF FINANCIAL DISTRESS PREDICTION MODELS , 1984 .

[13]  P. Schmidt,et al.  Limited-Dependent and Qualitative Variables in Econometrics. , 1984 .

[14]  G. Maddala.  Limited-dependent and qualitative variables in econometrics: Introduction , 1983 .

[15]  Joel G. Siegel.  How to analyze businesses, financial statements and the quality of earnings , 1982 .