报告题目：An Empirical Assessment of Alternative Discretionary Accrual Models
报 告 人：Huishan Wan, Associate Professor, University of Northern Iowa
报告时间：6月22日14:00-16:00
报告地点：后主楼1610

Abstract:
Using a large 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 195 firm-year observations of earnings restatements from 1997 to 2002 (GAO 2002), we investigate the relative performance of six extant discretionary accrual models and a Modified Forward-Looking Model. Our 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.