This study evaluates alternative measures of the tone of financial narrative. We present evidence that word-frequency tone measures based on domain-specific wordlists—compared to general wordlists—better predict the market reaction to earnings announcements, have greater statistical power in short-window event studies, and exhibit more economically consistent post-announcement drift. Further, inverse document frequency weighting, advocated in Loughran and McDonald (2011), provides little improvement to the alternative approach of equal weighting. We also provide evidence that word-frequency tone measures are as powerful as the Naïve Bayesian machine-learning tone measure from Li (2010) in a regression of future earnings on MD&A tone. Overall, although more complex techniques are potentially advantageous in certain contexts, equal-weighted, domain-specific, word-frequency tone measures are generally just as powerful in the context of financial disclosure and capital markets. Such measures are also more intuitive, easier to implement, and, importantly, far more amenable to replication.

This study examines the relation between a firm’s supply chain hierarchical position and its information quality. We predict that firms located in a more upstream position within the supply chain network are exposed to greater demand variance, thereby leading to decreased quality of reported earnings and greater uncertainty in the public information available to investors. Consistent with this prediction, we find that firm’s vertical position in the supply chain network is negatively associated with its information quality (i.e., poorer earnings quality and higher stock return synchronicity). Our results are robust to the matched sample analysis, residual analysis, and alternative measures of information quality. We further show that the positive relation between firm’s hierarchical position and stock return synchronicity is more pronounced for firms facing higher information asymmetry. Overall, our findings suggest that a more upstream position in the supply chain network entails not only operational costs associated with amplified demand uncertainty but also costs related to the quality of reported information on which capital providers and other stakeholders rely.