Earnings Quality and the Likelihood of Material Misstatement in the Financial Statements

Abstract

The purpose of this study is to identify financial indicators of poor earnings quality and to determine whether these indicators can distinguish firms with a high likelihood of material misstatement in their financial statements. Firms with significant accrual estimation errors are considered to have a high likelihood of material misstatement. A logistic regression model is developed using 10 financial indicators of poor earnings quality. Using a large sample across a 19 year period, the model is able to correctly classify up to 98% of firms as having either a high or a low likelihood of material misstatement.