Knowledge that Transforms

Researchers often use regression-based x-Scores (e.g., conservatism C-Score , misstatement F-Score ) from a stage 1 model as a dependent variable in stage 2. We argue that this x-Score analysis can cause coefficient biases and interpretation problems because (1) x-Score does not capture new sources of variation, and (2) the estimates often hinge on unacknowledged technical assumptions. Instead, we recommend that researchers include the test variables and the relevant controls in stage 1, obviating the need for an x-Score . In replication analyses, some important published findings change after we remove the coefficient bias caused by the use of x-Score as a dependent variable.

This paper examines whether and how public environmental enforcement affects private lenders’ monitoring efforts and the effectiveness of such monitoring. We capture lender monitoring using environmental covenants in loan agreements. Consistent with the prediction that stringent public environmental enforcement increases lenders’ monitoring incentives, we find that in the presence of higher environmental regulatory enforcement intensity, lenders are more likely to use environmental covenants when lending to polluting borrowers and when the loans are secured by real property collateral. Moreover, consistent with the prediction that stringent public environmental enforcement facilitates lender monitoring, we find that environmental covenants are more effective in reducing borrowers’ toxic chemical releases when environmental regulatory enforcement is stronger. Taken together, our findings corroborate the importance of public environmental enforcement in inducing lenders’ monitoring efforts, as well as the joint role of public enforcement and private lender monitoring in curbing corporate pollution.

We study the optimal dynamic contract that provides incentives for an agent (e.g., SPAC sponsor, VC general partner, CTO) to exploit investment opportunities/targets that arrive randomly over time via a costly search process. The agent is privy to the arrival as well as to the quality of the target and can take advantage of this for rent extraction during the search process and the ensuing production. The optimal contract provides the agent with incentives for timely and truthful reporting via a time-varying threshold for investment and an internal charge for the time spent on search. In the equilibrium, as time elapses, the charge becomes progressively higher while the investment threshold is progressively lower, resulting in overinvestment at a time-varying degree. Our model generates empirically testable predictions regarding investments (such as M&As, hedge fund activism, VC investing, SPACs, and internal innovations), linking the degree of overinvestment to observable firm and industry characteristics. • Optimal dynamic contract for the search and use of investment opportunities/targets. • Adverse selection arises regarding the arrival of targets and their quality. • Optimal contract involves a progressively declining hurdle for investments. • The investments hurdle is always below the first-best, implying overinvestment. • Our results shed light on internal innovation, M&A, SPACs, VC and HFA investments.

This study examines whether the implementation of industry-specific accounting standards helps capital market participants in making decisions about providing capital to firms. We predict and find an, on average, increase in firms’ capital growth in years following implementation of the relevant industry standard. The increase in capital growth arises primarily from equity issuances and is attributable to the implementation of the standards rather than industry-specific trends or economic shocks. We explore heterogeneity in industry standards and find more pronounced effects for (i) industry standards that reveal new information, provide explicit guidance, or increase accounting uniformity, and (ii) small firms, firms with greater information asymmetry, and firms with greater capital constraints before implementation of the standards. We also find evidence consistent with two channels explaining the documented increase in capital flows: reduction of information asymmetry and increase in financial statement comparability.

Advertising is a critical competitive tool that shapes interactions among firms in the product market. Using third-party tracked data on advertising outlet costs, I find that a nontrivial portion of public firms, even those with intense advertising activities, do not disclose advertising expenses in their financial statements, indicating significant disclosure discretion. I further use product category-level advertising data to develop a firm-specific measure of advertising rivalry. I predict and find that advertising rivalry is negatively associated with the likelihood of disclosing advertising expenses. This negative association is more pronounced when firms advertise on less trackable media outlets or have more mature products. These findings suggest that firms consider their advertising expenses proprietary and that concerns about advertising competition discourage the disclosure of advertising expenses.

When firms are forced to publicly disclose financial information, credit rating agencies are generally expected to improve their risk assessments. Theory predicts such an information quality effect but also suggests an adverse reputational concerns effect since credit analysts may become increasingly concerned about alleged rating failures. We empirically examine these predictions using a large-scale quasi-natural experiment in Germany, where a new compliance regime required firms to disclose annual financial statements publicly. Consistent with the reputational concerns hypothesis, we find an average increase in credit rating downgrades that is entirely driven by changes in the discretionary assessments of credit analysts rather than changes in firm fundamentals. Following public disclosure regulations, analysts tend to give positive private information less weight in their risk assessments while assigning greater weight to negative public information. A final set of results indicates that professional credit providers recognize that the resulting downgrades are not warranted.

Prior literature shows decision fatigue reduces analysts' forecast accuracy. We study whether analysts strategically manage their decision fatigue. Firms within an analyst's research portfolio can differentially affect the analyst's reputation and career, with larger firms with greater trading volumes and institutional ownership being more important. We find that analysts choose to issue forecasts for more important firms when they are less decision fatigued, i.e., when the number of prior forecasts the analyst has issued in the day is lower. Young analysts, analysts in low-status brokerage houses, and analysts who become decision fatigued more easily manage fatigue more, and analysts experience more favorable career outcomes after strategically managing fatigue. Finally, fatigued analysts differentiate between more important and other firms in herding and self-herding.

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.