ABSTRACT This study investigates whether and when differences in the credit rating agencies' methodologies result in differences in rating properties. In particular, this study focuses on differences in information processing constraints between a rating agency that utilizes qualitative analysis and direct access to borrowers' management in its rating process (Standard & Poor's) compared to one that does not (Egan Jones Ratings Company) and how these differences affect rating quality. We find that as information uncertainty about borrowers increases, Egan Jones's rating accuracy, informativeness, and timeliness decrease relative to Standard & Poor's. Our findings suggest that Egan Jones's more restricted rating methodology can lead to limitations in information processing and, thus, reductions in Egan Jones's rating quality advantage for borrowers with greater information uncertainty. JEL Classifications: G10; G24.

This study investigates the role of tax avoidance in the credit‐rating process and whether differences exist in how rating agencies account for the risk relevance of tax avoidance. Using a sample of initial credit ratings assigned to public debt issuances during 1994–2013, our evidence is consistent with Moody's Investors Service and Standard & Poor's assessing the costs and benefits associated with tax avoidance differently from one another, resulting in more frequent and pronounced rating agency disagreement. Rating agency disagreement over tax avoidance is most evident when it is accompanied by relatively high levels of uncertain tax positions, foreign activities, research and development activities, or tax footnote opacity. We also find evidence that decreases (increases) in tax avoidance or tax footnote disclosure opacity are positively (negatively) associated with the convergence of split ratings. This suggests that firms can exacerbate or mitigate rating agency disagreement subsequent to bond issuance. Our study complements prior research by examining why sophisticated information intermediaries disagree about the risk relevance of tax avoidance. It also sheds light on how firms can influence rating agencies’ understanding of tax avoidance.

We propose a new measure of readability, the Bog Index, which captures the plain English attributes of disclosure (e.g., active voice, fewer hidden verbs, etc.). We validate this measure using a series of controlled experiments and an archival-based regulatory intervention to prospectus filing readability. We also demonstrate the importance of understanding the underlying drivers of quantity-based measures of readability. In particular, we caution researchers that a vast amount of the variation in Form 10-K file size over time is driven by the inclusion of content unrelated to the underlying text in the 10-K (e.g., HTML, XML, PDFs).