Abstract
The Detection of Earnings Manipulation
The paper profiles a sample of earnings manipulators, identifies their distinguishingcharacteristics, and estimates a model for detecting manipulation. The model’s variables aredesigned to capture either the effects of manipulation or preconditions that may prompt firms toengage in such activity. The results suggest a systematic relation between the probability of manipulation and financial statement variables. The evidence is consistent with accounting databeing useful in detecting manipulation and assessing the reliability of accounting earnings.In holdout sample tests, the model identifies approximately half of the companies involvedin earnings manipulation prior to public discovery. Because companies discovered manipulatingearnings see their stocks plummet in value, the model can be a useful screening device forinvesting professionals. While the model is easily implemented-- the data can be extracted from anannual report--, the screening results require further investigation to determine whether thedistortions in financial statement numbers result from earnings manipulation or have anotherstructural root