A Latent Class Model of Earnings Attributes

Abstract:     
While the term "earnings quality" has been overused, rarely defined, and largely misunderstood, there is general agreement that users of financial statements react to their content, and that the accuracy and credibility of that content matters to them. To differentiate among financial reports, many papers rely on the association between one specific earnings attribute (such as accruals variability) and some observable outcome (auditor choice, for example). A notable exception, Francis, LaFond, Olsson and Schipper (2004) examine the relation between the cost of capital and several earnings attributes, including both accounting-based characteristics and market-based attributes. Whether each of these attributes provides incremental information for users of financial data beyond the others has not yet been established.

We draw upon Dechow and Dichev (2002), Francis et al. (2004), and Khan and Watts (2007) to identify potentially informative reporting dimensions or earnings attributes. We use a latent class analysis to show empirically that our measures for Accrual Variability, Persistence, Smoothness, Predictability, and Conservatism all have significant incremental value in differentiating among firms. The best across-firm latent class model also allows us to identify and study six categories of firms that differ significantly in terms of these five distinct measures. We summarize how these groups of firms differ in terms of both the attributes themselves and various innate firm characteristics. We also show how this new classification of firms is related to a principal component analysis, and we seek the best within-group model for each attribute in terms of innate firm characteristics. We find that two primary principal components provide useful and complementary summaries of the primary dimensions of the attributes examined.

Keywords: Earnings Attributes, Accruals, Conservatism, Income Smoothing, Earnings Persistence

JEL Classifications: M41, M43, M49

Working Paper Series