Measuring Accounting Fraud and Irregularities Using Public and Private Enforcement

The Accounting Review, Vol. 96 (6), pp. 183-213, November 2021.

51 Pages Posted: 8 Mar 2021 Last revised: 12 Aug 2022

See all articles by Dain C. Donelson

Dain C. Donelson

University of Wisconsin-Madison - Department of Accounting and Information Systems

Antonis Kartapanis

Texas A&M University - Mays Business School

John M. McInnis

University of Texas at Austin - Department of Accounting

Christopher G. Yust

Texas A&M University

Date Written: January 1, 2021

Abstract

Most accounting studies use only public enforcement actions (SEC cases) to measure accounting fraud. However, private cases (securities class actions) also play an important enforcement role. We discuss the legal standards and processes for both public and private enforcement regimes, emphasize the importance of screening cases for credible fraud allegations, and show both yield credible fraud measures. Further, we demonstrate these research design choices affect inferences from prior research and a hypothetical research setting. Finally, we show common measures of accounting irregularities using Audit Analytics to proxy for fraud result in significant false positives and negatives and develop a fraud prediction model for use in future research. We recommend using both public and private enforcement with appropriate screening when examining accounting fraud to reduce Type I and II errors, or reporting the sensitivity of findings across regimes. This is particularly important given the reduction in accounting-related enforcement after 2005.

Keywords: Financial Reporting Fraud, Securities Litigation, AAER, SEC Enforcement, Restatements, Irregularities, Fraud Prediction Models

JEL Classification: G38, K22, K41, K42, M41, M42, M48

Suggested Citation

Donelson, Dain C. and Kartapanis, Antonis and McInnis, John M. and Yust, Christopher, Measuring Accounting Fraud and Irregularities Using Public and Private Enforcement (January 1, 2021). The Accounting Review, Vol. 96 (6), pp. 183-213, November 2021., Available at SSRN: https://ssrn.com/abstract=3744392

Dain C. Donelson

University of Wisconsin-Madison - Department of Accounting and Information Systems ( email )

School of Business
975 University Avenue
Madison, WI 53706
United States

Antonis Kartapanis

Texas A&M University - Mays Business School ( email )

Wehner 401Q, MS 4353
College Station, TX 77843-4218
United States

John M. McInnis

University of Texas at Austin - Department of Accounting ( email )

Austin, TX 78712
United States
512-232-6791 (Phone)

Christopher Yust (Contact Author)

Texas A&M University ( email )

430 Wehner
College Station, TX 77843-4353
United States
979.845.3439 (Phone)

HOME PAGE: http://www.christopheryust.com

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