Knowledge that Transforms

To what extent does the narrative context surrounding the numbers in financial statements alter the informativeness of these numbers, that is, contextualize them? Answering this question empirically presents a methodological challenge. Leveraging recent advances in deep learning, we propose a method to uncover the value of contextual information learned from the (deep) interactions between numeric and narrative disclosures. We show that the contextualization of accounting numbers makes them substantially more informative in shaping beliefs about a firm's future, especially when numeric data are less reliable. In fact, the informational value of interactions dominates the direct informational value of the narrative context. We corroborate this finding by showing that stock markets and financial analysts incorporate the interactions between narrative and numeric information when making forecasts. We also demonstrate the value of our approach by identifying rich firm‐year–specific heterogeneity in earnings persistence. We discuss a number of avenues for future research.

Formal theory and empirical research are complementary in building and advancing the body of knowledge in accounting in order to understand real‐world phenomena. We offer thoughts on opportunities for empiricists and theorists to collaborate, build on each other's work, and iterate over models and data to make progress. For empiricists, we see room for more descriptive work, more experimental work on testing formal theories, and more work on quantifying theoretical parameters. For theorists, we see room for theories explicitly tied to descriptive evidence, new theories on individuals' decision making in a data‐rich world, theories focused on accounting institutions and measurement issues, and richer theories for guiding empirical work and providing practical insights. We also encourage explicitly combining formal theory and empirical models by having both in one paper and by structural estimation.

This paper examines the role of peer firm disclosures in shaping corporate research and development (R&D) investments. Drawing on models of two‐stage R&D races, I hypothesize that a firm could be either deterred or encouraged by peer disclosure of interim R&D success, depending on peer firms’ R&D strength in the race. Using granular, project‐level data on clinical trials in the drug development process, I find that a firm's R&D investments in a specific therapeutic area are deterred by disclosures of early‐phase trial initiation from strong rivals in the same area but encouraged by disclosures from weak rivals. Cross‐sectional analyses show that focal firm strength and disclosure relevance moderate the effects of peer firm disclosure. Overall, my evidence suggests that peer firms’ R&D disclosures can have both proprietary costs and deterrence benefits.

Connected financial journalists—those with working relationships, common school ties, or social media connections to company management—introduce a marked media slant into their news coverage. Using a comprehensive set of newspaper articles covering mergers and acquisition (M&A) transactions from 1997 to 2016, I find that connected journalists use significantly fewer negative words in their coverage of connected acquirers. These journalists are also more likely to quote connected executives and include less accurate language in their reporting. Moreover, they tend to portray other firms in the same network in a less negative light. Journalists’ favoritism bias has implications for both capital market outcomes and their careers. I find that acquirers whose M&As are covered by connected journalists receive significantly higher stock returns on the news article publication date. However, these acquirers’ stock prices reverse in the long term, suggesting market overreaction to news covered by connected journalists. Around M&A transactions, connected articles are correlated with increased bid competition and deal premiums. In terms of future career development, connected journalists are more likely to leave journalism and join their associated industries in the long run. Taken together, the evidence suggests that financial journalists’ personal networks promote news bias that potentially hinders the efficient dissemination of information.

This study examines how algorithmic trading (AT) affects forward‐looking disclosures in Management Discussion and Analysis (MD&A) of annual reports. We predict and find evidence that AT relates negatively to modifications in year‐over‐year forward‐looking MD&A disclosures. This evidence is consistent with AT reducing investors’ demand for fundamental information, which reduces managers’ incentives to supply costly forward‐looking disclosures. Cross‐sectional tests provide additional evidence that this negative relation is more pronounced for firms with larger earnings surprises and those with losses. We further validate our conclusion by demonstrating that investors’ fundamental information searches are a channel through which AT affects forward‐looking disclosures. The conclusion is robust to using the SEC's Tick Size Pilot Program as an exogenous shock to AT and to using alternative disclosure measures (e.g., tone revisions and number of sentences in forward‐looking MD&A disclosures). Overall, our study demonstrates that AT is a contributing factor to regulators’ concerns over the diminishing usefulness of forward‐looking information in MD&A disclosures.

Equity compensation is granted out of an equity incentive plan that must be approved by shareholders and cedes discretion over equity grants to boards of directors. We predict and find that equity plan proposals give boards more discretion over grants when the firm faces greater labor market forces and more volatile stock returns. When examining votes, we find that shareholders are less likely to support plans with abnormal discretion. We also find that boards with more discretion grant more equity in response to stock price declines. Lastly, we find that boards request additional shares when their ability to grant equity is more constrained by a smaller pool of available shares, and when they plan to increase equity grants. Overall our findings illuminate how firms balance needs to respond to labor market pressure and volatile operating environments against shareholder governance and oversight of equity compensation.

We study environmental and social (E&S) disclosures in annual reports. Using the word embedding model to examine over 210,000 annual reports from 24,271 public firms in 30 international countries/regions between 2001 and 2020, we create an E&S dictionary that allows us to document trends in annual report E&S disclosure. Specifically, we find: (1) increases in length and boilerplate language and (2) decreases in specificity. Our results also suggest that E&S disclosure quality improves after the adoption of voluntary ESG reporting frameworks but deteriorates after disclosure mandates. Our findings provide systematic evidence on the evolution of E&S disclosure in annual reports over the past two decades and shed light on how voluntary and mandatory standards have shaped global E&S reporting practices.

This paper offers the first systematic evidence on environmental, social, and governance (ESG) disclosures provided by a large global sample of private equity (PE) firms. Using historical websites from 2000 to 2022, we develop and validate a novel dictionary‐based measure of voluntary PE firm ESG disclosures. Descriptive statistics reveal an increasing time trend in these disclosures, with social topics becoming as important as environmental topics recently. Multivariate analyses show that the demand for ESG information from fund investors is a significant determinant of PE firms’ ESG disclosures. Leveraging data on PE firms’ portfolio companies, we document that more PE firm ESG disclosures are associated with better ESG outcomes at the portfolio company level, suggesting that voluntary ESG disclosures align with real actions for the average PE firm.

The Occupational Safety and Health Administration (OSHA) is decentralized, wherein field offices coordinated at the state level undertake inspections. We study whether this structure can lead to interstate frictions in sharing information and how this impacts firms’ compliance with workplace safety laws. We find that firms caught violating in one state subsequently violate less in that state but violate more in other states. Despite this pattern, and in keeping with information frictions, violations in one state do not trigger proactive OSHA inspections in other states. Moreover, firms face lower monetary penalties when subsequent violations occur across state lines, likely due to the lack of documentation necessary to assess severe penalties. Finally, firms are more likely to shift violating behavior into states with greater information frictions. Our findings suggest that internal information within regulators impacts the likelihood and location of corporate misconduct.

Interest in sustainability information, from investors, managers, researchers, and others, has been expanding rapidly. We discuss recent advances and open questions related to sustainability reporting and disclosure through the lens of a supply and demand framework. Our discussion builds on prior research on financial reporting and highlights unique aspects of the provision of sustainability information.