Discretionary Revenues as a Measure of Earnings Management

Abstract

This study examines the ability of revenue and accrual models to detect simulated and actual earnings management. The results indicate that revenue models are less biased, better specified, and more powerful than commonly used accrual models. Using a simulation procedure, I find that revenue models are more likely than accrual models to detect a combination of revenue and expense manipulation. Using a sample of firms subject to SEC enforcement actions for a mix of revenue- and expense-related misstatements, I find that, although revenue models detect manipulation, accrual models do not. These findings provide support for using measures of discretionary revenues to study earnings management.

Strategic revenue recognition to achieve earnings benchmarks

“…Roychowdhury (2006) finds no significant evidence that gross accounts receivable are managed to avoid a loss (see footnote 25 of his study). 8 In addition, Stubben (2008) provides evidence suggesting that discretionary models of accounts receivable are better than discretionary models of aggregate accruals at detecting earnings management. 9 In 1999, the Securities Exchange Commission (SEC) issued Staff Accounting Bulletin (SAB) No.…”

An empirical study of voluntary transfer pricing disclosures in China

“…Prior literature uses enforcement actions as a proxy for clients' earnings management activities (e.g., Feroz et al, 1991;DeChow et al, 1996;Beneish, 1999;Stubben, 2010) and audit failures (e.g., D/E = debt-equity ratio. GROWTH = market-to-book equity ratio.…”

Fuzzy linear regression-based detection of earnings management

“…The reason for excluding utilities and financial companies is that revenues and accruals in these regulated industries are likely to differ from those in other industries (e.g. Geiger & North, 2006;Stubben, 2010). Given these constraints, the size of the final data set is 689 companies.…”