Measuring Real Activity Management

45 Pages Posted: 24 Mar 2011 Last revised: 29 Sep 2020

See all articles by Daniel A. Cohen

Daniel A. Cohen

Vanderbilt University - Owen Graduate School of Management

Shail Pandit

University of Illinois at Chicago; University of Illinois at Chicago

Charles E. Wasley

Simon School, University of Rochester

Tzachi Zach

Ohio State University (OSU) - Department of Accounting & Management Information Systems

Multiple version iconThere are 2 versions of this paper

Date Written: July 17, 2019

Abstract

To test hypotheses about earnings management many studies investigate managers’ manipulation of real activities (real earnings management, REM). Tests using measures of abnormal REM hinge critically on the measurement of normal real activities. Yet there is no systematic evidence on the statistical properties of commonly-used REM measures. We provide such evidence by documenting the Type I error rates and power of the test of the REM measures commonly used in the literature. We find these measures are often mis-specified with Type I error rates that deviate from the nominal significance level of the test, especially in samples of firms with extreme performance or firm characteristics. We also compare the specification and power of traditional REM measures with performance-matched REM measures to see if the latter provide better specified and more powerful tests. While performance-matched REM measures are not immune from mis-specification in all settings, in general, they are better specified under the null hypothesis (i.e., in terms of Type I errors) than are traditional REM measures. Comparisons of the power to detect abnormal REM reveal that neither approach, traditional or performance-matched, is consistently more powerful than the other in terms of detecting abnormal REM ranging from 1% to 10% of (lagged) total assets. The absence of a dominant approach to measure abnormal REM leads us to recommend that future researchers report results using both traditional and performance-matched measures so that readers are able to clearly assess the reliability of the inferences drawn about the magnitude and significance of the abnormal REM documented in a given study.

Keywords: Real activity management; real earnings management; earnings management; real activity models, test specification, Type I errors, Type II errors, power of the test, meet or beat, earnings benchmarks, model specification

JEL Classification: M41, C12, C15, M42

Suggested Citation

Cohen, Daniel A. and Pandit, Shailendra and Pandit, Shailendra and Wasley, Charles E. and Zach, Tzachi, Measuring Real Activity Management (July 17, 2019). Available at SSRN: https://ssrn.com/abstract=1792639 or http://dx.doi.org/10.2139/ssrn.1792639

Daniel A. Cohen

Vanderbilt University - Owen Graduate School of Management ( email )

401 21st Avenue South
Nashville, TN 37203
United States

Shailendra Pandit

University of Illinois at Chicago ( email )

601 South Morgan Street
2323 University Hall
Chicago, IL 60607
United States
(312) 355-1331 (Phone)
(312) 996-4520 (Fax)

HOME PAGE: http://business.uic.edu/faculty/shailendra-shail-pandit

University of Illinois at Chicago ( email )

601 South Morgan Street
University Hall, Room 2303
Chicago, IL 60607
United States
(312) 355-1331 (Phone)
(312) 996-4520 (Fax)

HOME PAGE: http://business.uic.edu/faculty/shailendra-shail-pandit

Charles E. Wasley

Simon School, University of Rochester ( email )

Rochester, NY 14627
United States
585-275-3362 (Phone)
585-442-6323 (Fax)

Tzachi Zach (Contact Author)

Ohio State University (OSU) - Department of Accounting & Management Information Systems ( email )

2100 Neil Avenue
Columbus, OH 43210
United States
614-292-4101 (Phone)

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