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 result from earnings manipulation or have another
structural root.