Detecting Earnings Management

Posted: 26 Aug 1999

See all articles by Patricia M. Dechow

Patricia M. Dechow

University of Southern California - Leventhal School of Accounting; University of California, Berkeley - Accounting Group

Richard G. Sloan

University of Southern California - Leventhal School of Accounting

Amy P. Hutton

Boston College - Carroll School of Management

Date Written: February 1994

Abstract

This paper evaluates alternative models for detecting earnings management. The paper restricts itself to models that assume the construct being managed is discretionary accruals, since such models are commonly used in the extant accounting literature. Existing models range from simple models in which discretionary accruals are measured as total accruals, to more sophisticated models that separate total accruals into a discretionary and a non-discretionary component. Prior to this paper, there had been no systematic evidence bearing on the relative performance of these alternative models at detecting earnings management. This paper evaluates the relative performance of the competing models by comparing the specification and power of commonly used test statistics across the measures of discretionary accruals generated by each model. The specification of the test statistics is evaluated by examining the frequency with which they generate type I errors for a random sample of firm-years and for samples of firm-years with extreme financial performance. We focus on samples with extreme financial performance because the stimuli investigated in previous research are frequently correlated with financial performance. The first sample of firms are targeted by the Securities and Exchange Commission for allegedly overstating annual earnings and the second sample is created by artificially introducing earnings management into a random sample of firms.

JEL Classification: M41

Suggested Citation

Dechow, Patricia M. and Sloan, Richard G. and Hutton, Amy P., Detecting Earnings Management (February 1994 ). Available at SSRN: https://ssrn.com/abstract=5520

Patricia M. Dechow

University of Southern California - Leventhal School of Accounting ( email )

Los Angeles, CA 90089-0441
United States

University of California, Berkeley - Accounting Group ( email )

Haas School of Business
Berkeley, CA 94720
United States

Richard G. Sloan

University of Southern California - Leventhal School of Accounting ( email )

Los Angeles, CA 90089-0441
United States

Amy P. Hutton (Contact Author)

Boston College - Carroll School of Management ( email )

140 Commonwealth Avenue
Chestnut Hill, MA 02467
United States
617 552 1951 (Phone)

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