The Detection of Earnings Manipulation (2)

The Detection of Earnings Manipulation (2) - The Detection...

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon
The Detection of Earnings Manipulation Messod D. Beneish Presented are a profile of a sample of earnings mniiipjilators, 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 sudi 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. TJic 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 result from earniiigs manipulation or have another structural root. . -^^h e extent to which earnings are manipu- i a lated has long been of interest to analysts, J L-egLtlators, researchers, and other invest- ment professionals. The U,S, SEC's recent commitment to vigorous investigation of earnings manipulation (see Levitt 1998) has sparked renewed interest in the area, but the academic and profes- sional literature contains little discussion of the detection of earnings manipulation. This article presents a model to distinguish manipulated from nonmanipulated reptirting,' Earnings manipulation is defined as an instance in which a company's managers violate generally accepted acccnmting principles (G AAP) to favorably represent the company's financial performance. To develop the mt)del, I used fiiiandal statement data to construct variables that would capture the effects of manipulation and preconditions that might prompt companies to engage in such activity. Sample The sample consisted of 74 companies that manip- ulated earnings and all Compustat companies matched by two-digit SIC numbers for which data were available for the 1982-92 period- The 74 earn- ings manipula tors were either companies subject to Messod D. Beneish is an associae professor at the Kelley School of Business, Indiana University. the SEC's accounting enforcement actions or were identified as manipulators by the news media. To identify companies subject to accounting enforcement actions by the SEC, I used Accounting and Auditing Enforcement Releases (AAERs) #132 through #502, issued from 1987 to 1993. After elim- ination of inappropriate companies from the 363 AAHRs examined (#372 to #379 were not assigned by the SEC), this search yielded a final sample of 103 AAERs relating to 49 compaiues that violated GAAP,- An extensive media search on LEXIS-NEXIS for Jai-iuary 1987 to April 1993 identified 80 compa- nies mentioned in articles discussing earnings
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Image of page 2
This is the end of the preview. Sign up to access the rest of the document.

Page1 / 14

The Detection of Earnings Manipulation (2) - The Detection...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online