The evidence in this paper is based on a sample of firms whose manipulation of earnings was publicly discovered. Such firms likely represent the upper tail of the distribution of firms that seek to influence their reported earnings and the evidence should be interpreted in this light. Given this caution, the evidence of a systematic association between earnings manipulation and financial statement data is of interest to both accounting researchers and professionals because it suggests that accounting data not only meet the test of providing useful information but also enable an assessment of reliability. The explicit classification model only requires two years of data (one annual report) to evaluate the likelihood of manipulation and can be inexpensively applied by the SEC, auditors, and investors to screen a large number of firms and identify potential manipulators for further investigation.
While the model is cost-effective relative to a strategy of treating all firms as non- manipulators, its large rate of classification errors makes further investigation of the results an important element to the model’s implementation. That is, since the model’s variables exploit distortions in financial statement data that could result from manipulation, one must recognize that such distortions can have an alternative origin. For example, they could be the result of a material acquisition during the period examined, a material shift in the firm’s value maximizing strategy, or a significant change in the firm’s economic environment.
One limitation of the model is that it is estimated using financial information for publicly traded companies. Therefore, it cannot be reliably used to study privately-held firms. Another limitation is that the earnings manipulation in the sample involves earnings overstatement rather than understatement and therefore, the model cannot be reliably used to study firms operating in circumstances that are conducive to decreasing earnings.