Detecting Target-Driven Earnings Management Based on the Distribution of Digits

We present a novel research design to detect target-driven earnings management in accounting data. As a particular concern in this line of research, information about the exact earnings target value of a given firm is often not available. We therefore develop an empirical strategy that does not require such information. To this end, we rely on the concept of the distribution of digits rather than the distribution of the earnings metric itself. We then theoretically derive that the mean of the distribution of digits, in particular, exhibits a specific pattern around the earnings target that can be exploited to investigate target-driven earnings management. This pattern arises regardless of the distribution of digits that obtains in unmanaged data. We extensively test our theoretical predictions using both simulated and archival data.