Estimating the influence of accounting variables change on earnings management detection

Abstract

Standard earnings management detection is performed using two routes: real earnings management (connected with inventory and expenses manipulations) and accrual earnings management (connected with revenue and accounts receivables manipulations). Neither of these two detection algorithms attempts to quantify earnings management and connect it with the infractions committed by the companies, charged by the regulator (in this case – U.S. SEC). In many known cases of revenue manipulation, it is not possible to say whether real or accrual based earnings management was used. In this research, we look at the cases of financial statement fraud, namely one of the most common variations – revenue manipulation, from the perspective of the practitioner and propose the way of detection and quantification of such manipulations. In order to distinguish the cases of earnings management, we use the components of DuPont formula. In addition, we also look at the accounting variables used in the calculation of the detection criterion and determine which ones of them play the main role in revenue manipulations.