Detecting Earnings Management

This paper evaluates alternative accrual-based models for detecting earnings management. The evaluation compares the specification and power of commonly used test statistics across the measures of discretionary accruals generated by the models and provides the following major insights. First, all of the models appear well specified when applied to a random sample of firm-years. Second, the models all generate tests of low power for earnings management of economically plausible magnitudes (e.g., one to five percent of total assets). Third, all models reject the null hypothesis of no earnings management at rates exceeding the specified test-levels when applied to samples of firms with extreme financial performance. This result highlights the importance of controlling for financial performance when investigating earnings management stimuli that are correlated with financial performance. Finally, a modified version of the model developed by Jones (1991) exhibits the most power in detecting earnings management.