The earnings ‘time-series literature’ in accounting focuses on the statistical characteristics of the processes which generate corporate earnings. In order to further our understanding of earnings behavior, this study investigates the question whether inter-firm differences in these statistical characteristics (autocorrelations and variances of earnings changes) can be explained by economic factors. Various relationships between economic factors and earnings behavior are derived from the economic literature and examined empirically in this study. Findings indicate that autocorrelations and variability of annual earnings and earnings over equity changes are systematically associated with the following factors: the type of product, the height of industry barriers-to-entry (a surrogate for degree of competition), the degree of capital intensity (‘operating leverage’), and the firm size.

GAAP mandates the full expensing of R&D in financial statements, presumably because of concerns with the reliability, objectivity, and value-relevance of R&D capitalization. To address these concerns, we estimate the R&D capital of a large sample of public companies and find these estimates to be statistically reliable and economically meaningful. We then adjust the reported earnings and book values of sample firms for the R&D capitalization and find that such adjustments are value-relevant to investors. Finally, we document a significant intertemporal association between firms' R&D capital and subsequent stock returns, suggesting either a systematic mispricing of the shares of R&D-intensive companies, or a compensation for an extra-market risk factor associated with R&D.

In contrast to theoretical and empirical evidence linking disclosure to information environment benefits, recent research concludes that guidance increases volatility, but leaves open the question of whether volatility plays a role in prompting the issuance of guidance. Consistent with the notion that managers react to rising volatility by providing guidance, we document a link between abnormal run-ups in volatility and the decision to issue a forecast after controlling for the market’s ability to anticipate the guidance. Upon disentangling pre-guidance volatility changes from post-guidance volatility changes, we find no evidence that guidance increases volatility. Indeed, our evidence consistently supports the view that managers seek to and do mitigate share price volatility with guidance.