A vast literature following Hayn [1995] and Burgstahler and Dichev [1997] attributes the so-called “discontinuity” in earnings distributions around zero to earnings management. Durtschi and Easton [2005] show that, although earnings management is one possible explanation, the evidence suggests that these discontinuities are driven by sample selection bias and scaling. Jacob and Jorgensen [2007] introduce an alternate methodology and conclude that their findings suggest that “while scaling and associated selection biases might contribute to the observed discontinuities, they are not primarily responsible for these discontinuities.” We show that this conclusion is not supported by their analyses. Hence we reiterate the point in Durtschi and Easton [2005] that the shapes of frequency distributions of earnings metrics are not ipso facto evidence of earnings management, and assert that before one can draw conclusions regarding the presence/absence of earnings management, evidence beyond the shapes of these particular distributions must be bought to bear.

The Jacob and Jorgensen [2007] hereafter JJ methodology consists of comparing the distribution of fiscal year (t) earnings with a benchmark distribution, which is the average of the distributions of three “as-if” years of earnings. Each of the three “as-if” years span four consecutive quarters: (1) ending with quarter one of fiscal year t, (2) ending with quarter two of fiscal year t, and (3) ending with quarter three of fiscal year t. In other words, the Jacob and Jorgensen [2007] benchmark is a weighted average of quarterly earnings over the six quarters ending in the third quarter of year t. JJ argue that earnings measured over these alternate years are less likely to suffer from the effects of managerial income manipulation than earnings of the fiscal year; they claim that differences between the distribution of fiscal year earnings and the distribution of the average of the three “as-if” years of earnings is evidence of earnings management.