Research

“Racial Diversity Exposure and Firm Responses Following the Murder of George Floyd”

with Karthik Balakrishnan, Rafael Copat, and K. Ramesh
Journal of Accounting Research, Forthcoming
Presented at the 2022 JAR Conference

Abstract: George Floyd’s murder caused many firms to reveal how exposed they are to racial diversity issues. We examine investor and firm behaviors after this socially significant event to provide evidence on the valuation effects of the exposure and ensuing corporate responses. We develop a text-based measure of a firm’s exposure to racial diversity issues from conference call transcripts and find that, after the murder of George Floyd, firms with diversity exposure experience a stock price decrease of approximately 0.7% around the date of the conference call. We provide evidence that this effect is attributable to race-related exposure and not gender-related exposure. Initiatives taken by firms mitigate the negative market reaction. We document that firms with racial diversity exposure respond by appointing Black directors. The stock market views appointments of Black directors more favorably after George Floyd’s murder, except when they are perceived as symbolic. We also find that firms with greater exposure to racial diversity are more likely to establish DEI departments, appoint DEI leaders, specify diversity goals, increase supply chain diversity, and donate to racial justice causes. Our paper provides evidence that exposure to racial diversity issues adversely affects firm value, and companies address the exposure by taking actions.

:point_right: Click here to watch the 2022 JAR Conference presentation! :tv:


“Disclosure Firmness of Corporate Language in the Presence of Increased Entry Threat”

Job Market Paper

Abstract: I study firms’ disclosure choices in response to heightened entry threat and their effectiveness at deterring potential entrants. Using the MD&A section of 10-K filings, I develop and validate a measure of disclosure firmness that aggregates hard and soft disclosure attributes consisting of vague, tonal, forward-looking, explanatory, numerical, and specific information, as well as novel metrics of historical and objective content based on natural language processing and machine learning. I find that firms provide firmer/harder disclosures when faced with increased competition threat. This behavior is consistent with an entry-deterrence strategy that relies on more detailed, verifiable, and credible information aimed at convincing potential rivals that entering the market is not profitable. Specifically, firms make greater use of numerical, specific, and factual-based language when entry costs are lower, as well as after import tariff rate reductions that exogenously increase entry threat. Evidence suggests that this disclosure strategy can effectively deter subsequent entry.

:point_right: Click here to see how I used Machine Learning in my Job Market Paper! :robot:


“Protecting Forward Looking Statements”

with Maclean Gaulin and K. Ramesh

Abstract: We examine the increasingly prevalent managerial disclosure practice of listing specific keywords in SEC filings to identify forward-looking statements for obtaining “safe harbor” protection under the Private Securities Litigation Reform Act. We show that proxies for ex ante litigation risk, network/herding effects, disclosure supply, and economic uncertainty are strongly associated with the decision to include the keyword list and the number of keywords. Responding to transient economic circumstances, firms periodically change the number of keywords to customize their forward-looking disclosures. Using factor analysis we unravel the specific linguistic attributes implied by the keywords and show how they enable firms to tailor their disclosure of quantitative and qualitative forward-looking information. Finally, managers facing higher litigation risk find it imperative to protect disclosures that capital markets view as value relevant. Overall, the decision to include the list and the choice of the keywords it contains are neither boilerplate nor ad hoc. Together, our evidence provides an important first look at the determinants of firms’ decisions regarding a central feature of forward-looking disclosures’ “safe harbor” protection.


“The Sound of Uncertainty: A Computational Linguistics Approach to Examining Managerial Acoustic Uncertainty in Conference Calls”

with John Gallemore

Abstract: Building on the literature in linguistics and psychology showing that the manner in which individuals speak can provide context above and beyond the actual spoken words, we study whether the uncertainty expressed via the acoustic features of managerial speech in conference calls impacts analyst behavior. We predict that when managers express greater acoustic uncertainty in their responses to questions during conference calls, analysts rely less on the information provided by managers, affecting their subsequent forecasts. Using over 30,000 hours of conference call audio, we develop and validate a novel measure of managerial uncertainty based on the acoustic features of their speech. We find that when managers sound more uncertain in their responses to analyst questions, analyst forecast dispersion increases, even after accounting for characteristics of the actual language being used by managers and analysts, consistent with analysts relying less on the information conveyed via these responses and more on information idiosyncratic to the analyst. Furthermore, we find that the impact of acoustic uncertainty on analyst behavior depends on the characteristics of the questions and responses, such as the complexity of the analyst’s question and the specificity and forward-looking nature of the manager’s response. Finally, we find that this acoustic uncertainty is also associated with increased bid-ask spreads, a market-based measure of uncertainty, and that this is concentrated within firms with greater increases in post-conference call forecast dispersion. Our findings suggest that the uncertainty expressed in the acoustic features of managerial speech can affect market participants. Furthermore, our study creates and validates an approach to study the acoustic uncertainty of executive speech.


“The Informativeness of Changes in Critical Audit Matters”

with Wayne Landsman, Ryan Peng, and Jianxin (Donny) Zhao

with Vitaly Meursault

Works In Progress

“The Predictive Ability of Corporate Language” with Nick Guest and Mani Sethuraman