Measuring Real Activity Management
Daniel A. Cohen
University of Texas at Dallas - Naveen Jindal School of Management
University of Illinois at Chicago
Charles E. Wasley
University of Rochester - Simon Business School
Ohio State University (OSU) - Fisher College of Business
April 16, 2015
Much recent research focuses on earnings management via the manipulation of real activities (real earnings management, REM). While tests of REM hinge critically on the measurement of abnormal real activities, there is no systematic evidence on the properties of commonly used REM measures or the statistical tests based on them. We provide such evidence by documenting which REM measures lead to well-specified hypothesis tests and which do not. We find that the traditional REM measures used to date in the literature are severely mis-specified in that their Type I error rates differ significantly from nominal significance levels. We analyze alternative REM measures based on performance matching and find that while performance-matched REM measures are not well-specified in each and every setting (no REM measure is), the weight of the evidence suggests that across a wide variety of settings they will provide better-specified tests than the traditional REM measures. Such evidence highlights the importance of using performance-matched REM measures when testing hypotheses related to managers’ incentives to manipulate real activities to ensure that reliable inferences are drawn from the analysis.
Number of Pages in PDF File: 47
Keywords: Real activity management, real earnings management, earnings management, real activity models, test specification, meet or beat, earnings benchmarks, model specification
JEL Classification: M41, C12, C15, M42
Date posted: March 24, 2011 ; Last revised: April 25, 2015
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