A Simple Approach to Better Distinguish Real Earnings Manipulation from Strategy Changes

Résumé du livre

Researchers typically infer real earnings management when a firm's operating and investing activities differ from industry norms. One significant problem with classifying deviations from industry averages as “earnings management” is that companies can change their operating and investing decisions for strategic reasons, and it is difficult to distinguish strategy adjustments from earnings management. We focus on opportunistic real earnings management, which we label “manipulation.” We use Principal Components Analysis (PCA) to develop real earnings manipulation (REM) measures that reflect the concurrent use of multiple activities. This approach is promising because, although there are many possible sources of abnormal activity levels aside from manipulation, there are fewer sources that can explain the combined, income-increasing use of these real activities. This simple approach results in REM metrics that (1) associate negatively with future operating performance, (2) reduce earnings persistence, (3) yield high-power tests, and (4) appear to capture “manipulation” reasonably well across most firm life-cycle stages. Importantly, this approach performs better than the standard real earnings management metrics across all dimensions. Also, because this innovation does not require a long time-series of data or rely on future period realizations for classification, it can be useful in more research settings than other recent innovations proposed in prior research.