A new approach to evaluating earnings management models

Abstract

This paper proposes a new full-scale simulation approach for correctly measuring the detection ability of the modified Jones model (MJM). For ideal evaluation accuracy, we define perfect prior information on whether a firm under investigation manipulates its earnings with the allowance for doubtful accounts by differentiating firms that engage in no earnings manipulation from those that do. The MJM shows a detection rate of only 49.1%, which is lower than 50% for a fair coin toss, and thus it is not reliable. This low detection rate is due to the oversensitivity of the MJM, which causes it to misinterpret long-term increases in sales revenue from normal business activity as earnings management. Therefore, the MJM has a tendency to incorrectly detect non-discretionary accruals (NDACs) as discretionary accruals (DACs) and thus misjudge a clean firm as a dirty one, because it shows a low (moderately high) detection rate for clean (dirty) firms.