Research

We study the economic consequences of managers' vocal delivery quality during earnings conference calls. We introduce a novel measure, vocal delivery quality, that captures the acoustic comprehensibility of audio information for an average listener. Our measure relies on a deep-learning algorithm applied to a large sample of earnings call audio files. Consistent with predictions from the psychology and accounting literatures, we find evidence that the quality of managers' vocal delivery deteriorates when they deliver negative news, such as a decrease in earnings or negative narrative information, and positive but transitory earnings news. We show that the stock market reacts in real time to managers' vocal delivery quality. We also document that the vocal delivery quality has an effect on information intermediaries such as analysts and the media. Overall, our findings underscore the role of vocal dimensions in corporate oral disclosures.

I study whether disclosure mandates alter the equilibrium of cyberattacks by unintentionally informing cybercriminals. The California Consumer Privacy Act (CCPA) requires companies to disclose their personal information collection practices to consumers, inadvertently informing cybercriminals about the potential benefits of breaching each firm. Using a difference-in-differences design, I find that firms disclosing the collection of valuable personal data face an increased probability of data breaches. These firms also strengthen their cyberdefenses, both in terms of software and employee cybersecurity expertise. Firms trade off cybersecurity costs against the risk of data breaches, with the increase in breach probabilities more pronounced among firms that invest less in cybersecurity. Finally, I find that firms voluntarily disclose more about their cyberdefense and adjust their data-collection policies as additional defense strategies. Overall, this study highlights the trade-off between transparency and cybersecurity risks in today's economy.

We show a novel mechanism by which mutual fund managers strategically alter their portfolios to take advantage of investors' reliance on Morningstar star ratings. Specifically, funds achieve higher ratings by changing their holdings to induce Morningstar to reclassify them into size-value style boxes with lower average performance, thereby enabling more favorable peer comparisons. This practice, which we term 'box jumping,' attracts fund flows and higher fees, despite sacrificing return performance with rating upgrades reversing within three years on average. These patterns emerge after 2002 when Morningstar ratings began to be based on relative performance within style boxes, and are predictably absent beforehand. We also show that pervasive box jumping creates negative spillover effects on other funds. Together, our findings highlight portfolio recomposition as a novel strategic lever that funds use to manipulate Morningstar ratings.

Business software and associated technological tools are becoming ubiquitous, but we have little evidence on why firms voluntarily adopt them. To address this, we study how accounting software adoption by private firms responds to labor market conditions. We first show that adoption is increasing in accounting wages and decreasing in the number of accountants in a given market. We confirm this finding in a Bartik-style estimation that exploits the passage of the Sarbanes-Oxley Act and differences in states' pre-Act exposure to public company accounting labor markets. Software adoption frees up accountants to focus on operational and strategic tasks, and enables the implementation of management accounting practices such as inventory management and demand planning. Adoption also reduces the seasonality of accounting labor demand. Our results illustrate how labor market scarcity can induce technology adoption, consistent with models of directed technological change.

We investigate whether ESG investors sacrifice returns for nonpecuniary motives by examining securities lending. Despite widespread lending by passive funds, passive ESG funds lend 30% less than comparable non-ESG funds, even for the same stock. By lending less, ESG funds forgo income equal to roughly 40% of fund expenses and experience increased tracking error. The evidence is most consistent with ESG investors with nonpecuniary motives avoiding lending that facilitates short selling. We contribute to the understanding of ESG investors' nonpecuniary choices and highlight a channel through which passive funds can act on nonpecuniary preferences that is distinct from screening or governance interventions.