Predicting Material Accounting Misstatements

Abstract:     
We examine 2,190 SEC Accounting and Auditing Enforcement Releases (AAERs) issued between 1982 and 2005. We obtain 676 firms that are alleged to have misstated their quarterly or annual financial statements. We examine the characteristics of misstating firms along five dimensions: accrual quality; financial performance; non-financial measures; off-balance sheet activities; and market-based measures. We compare misstating firms to themselves during non-misstatement years and misstating firms to the broader population of all publicly listed firms. The results reveal that during misstatement years, accruals and cash and credit sales are unusually high, while return on assets and the number of employees are declining. In addition, misstating firms finance more of their assets through operating leases and have relatively less PP&E. We find that market pressures appear to affect incentives to misstate. Misstating firms are raising new financing, have higher market-to-book ratios, and strong prior stock price performance. We develop a model to predict accounting misstatements. The output of this model is a scaled logistic probability that we term the F-Score, where values greater than one suggest a greater likelihood of a misstatement.

Keywords: earnings quality, accounting misstatement, fraud prediction, accrual quality, F-Score

JEL Classifications: G34, M41

Working Paper Series