An Empirical Assessment of Alternative Discretionary Accrual Models: Evidence from Earnings Restatements

Abstract

Using a sample of firms that restated earnings, this study seeks to evaluate the performance of alternative discretionary accrual models along two dimensions:  earnings management detection and accuracy (the ability to accurately estimate the magnitude of managed earnings).  The findings of this study are important for three reasons.  First, discretionary accrual models play a prominent role in several streams of accounting research, especially in earnings management research.  Thus, the ability of discretionary accrual models to isolate the discretionary component from the non-discretionary component of total accruals is critical.  Second, there is concern about earnings management inferences drawn from discretionary accrual estimates generated by existing discretionary accrual models.  One major concern is that extant discretionary accrual models are mis-specified, which results in misleading inferences about earnings management behavior.  Finally, there is lack of consensus in the literature on the relative performance of discretionary accrual models.  Using earnings restatements data, I investigate the relative performance of four extant discretionary accrual models and a Modified Forward-Looking Model.  The findings indicate that the Modified Forward-Looking Model is better specified and outperforms the other models both in terms of detecting earnings management and in estimating the magnitude of managed earnings.