Knowledge that Transforms

In 2014, the PCAOB adopted a new auditing standard, AS 18 Related Parties, with the intention of enhancing auditors’ performance in auditing related-party transactions (RPTs). Using hand-collected data, we find significant reductions in both firms’ restatement risk and their engagement in RPTs following the AS 18 adoption. Such reductions are especially pronounced for smaller firms and firms having RPTs with principals, in which related persons in the counterparty of RPTs are the primary beneficiaries, such as CEOs, board chairs, or primary shareholders. We also find that smaller firms having RPTs with principals tend to pay higher audit fees post-AS 18. Our study responds to the PCAOB’s call to assess the economic consequences of AS 18. The findings suggest that AS 18 is associated with improved audit quality and reductions in auditees’ opportunistic RPT activities. Data Availability: Data are available from public sources as cited in the article and from the authors upon request.

The impact of earnings announcements (EAs) on investor uncertainty depends not only on how much new information they contain but also on how long it would take comparable information to arrive in the future through alternative sources, which I term “earnings horizon.” Using a structural model of periodic EAs, I show that earnings horizon is not captured by standard empirical measures of earnings informativeness or timeliness based on the event-study approach. However, earnings horizon can be estimated using patterns in return volatility over firms’ reporting cycles, which indicate that EAs have a short horizon and thus reduce investor uncertainty by one-third the amount suggested by event studies. Moreover, these patterns indicate that it takes investors considerably longer than the three- to five-day windows commonly applied in event studies to fully process EAs and that more frequent financial reporting may significantly enhance EAs’ informativeness. Data Availability: Data are available from the public sources cited in the text.

We study how nonfinancial firms’ operating risks change after bank competition increases. By exploiting the 1990s staggered regulatory reforms across U.S. states that allowed interstate banking and branching, we show that out-of-state bank entry was associated with lower borrower risk-taking on average. Large, profitable, safe, and geographically diversified firms signed up as new clients of large entrant banks, which offered larger and cheaper loans that reflected their higher efficiency and risk reduction through geographical diversification. We argue that these large banks could substitute for local relationship lending with more data collection from branches in multiple states. Firms that began borrowing from entrant banks increased capital expenditures and project-specific financing and kept R&D expenses stable but reduced R&D risk. Firms that continued borrowing from incumbent banks paid higher interest rates and increased their risk, suggesting that their credit access fell. States that opened up more had bigger changes in these outcomes. Data availability: Data are available from the public sources cited in the text.

We study the effects of disclosure in a dynamic market with imperfect competition. The supply of an asset is determined by a large shareholder with price impact, who trades slowly to diversify away from concentrated ownership. Small investors provide capital and thus risk-bearing capacity to the market. Although it is well known that disclosure impedes risk sharing by shifting risk before future trading opportunities, we show that disclosure, at the same time, can enhance risk sharing by promoting more trades. Resolving this tradeoff, an interior level of disclosure quality maximizes the small investors’ surplus as well as the total surplus, but minimizes the large shareholder’s surplus. Further, efficient disclosure policies feature increasing quality over time.

We investigate whether differences in the mix of financial covenants in debt contracts (i.e., covenant heterogeneity) reflect—and provide a way for lenders to elicit, or screen—borrowers’ pre-contractual private information about their future risk profile. Consistent with adverse selection theories, we predict and find that borrowers with higher future risk negotiate loans with covenants that are less sensitive to performance, compared to borrowers with lower future risk. We differentiate between screening and incentive explanations for this finding and provide evidence that screening accounts for a substantial portion of this overall relation. Our study highlights how, in addition to shaping borrowers’ incentives through monitoring, covenant heterogeneity reflects borrowers’ future risk profiles and can help lenders screen accordingly. Data Availability: Data are available from the public sources cited in the text.

Basel III introduced the first global banking liquidity requirement: the liquidity coverage ratio (LCR). This paper examines whether loosening the regulatory accounting for the LCR, by including certain municipal bonds in its computation, has a spillover effect on the municipal bond market. In contrast to statements made by regulators, I find that the rule decreases affected bonds’ yield spread, relative to unaffected bonds, due to an increase in nonfundamental bank demand for the affected bonds. The regulation also has a real effect on bond issuance: municipalities that can issue either affected or unaffected bonds change their behavior by issuing relatively more of the affected bonds. This suggests that regulatory accounting changes can affect the economic behavior of entities that are not even subject to the regulation.

Global markets are moving toward requiring firms to track and report greenhouse gas emissions across their value chain. This includes self-generated emissions (i.e., Scope 1), emissions from power providers (i.e., Scope 2), and emissions from upstream suppliers and downstream parties (i.e., Scope 3). Yet, obtaining reliable emissions data is a complex task that often relies on cumbersome legacy processes and becomes especially challenging with upstream and downstream emissions. Using the Design Science Research Methodology, we propose and prototype (early-stage) a technological solution that uses blockchain, non-fungible tokens, and smart contracts to track and report greenhouse gas emissions across a firm’s value chain. The proposed model demonstrates how these tools can create a reliable classification and provenance of emissions that all value chain members can access for reporting purposes. Experts in the field evaluate the proposed model, find it technologically feasible, and call attention to some of its challenges.

We compare the ESG ratings of MSCI, a global rater, with those of SINO, a local Chinese rater, to evaluate their effectiveness in capturing ESG risks within the Chinese context. Using ESG issues revealed in negative incidents as a proxy for ESG risk, we find that the ratings from the two raters often diverge, with SINO generally outperforming MSCI in predicting ESG risks in China. This divergence is more pronounced for firms with extensive ESG disclosures and when there are significant differences in how the raters define and measure ESG issues. Distance-based information asymmetry does not appear to play a significant role in explaining the performance gap. The advantage of local raters likely stems from their flexibility in tailoring methodologies to reflect country-specific nuances. In contrast, global raters adopt consistent methodologies to meet investor demand for comparability, but this approach may inadvertently reduce their relevance for capturing localized ESG risks. Data Availability: Data are available from sources identified in the text.

Although q2 measures how well a pattern of means fits a custom contrast, there is no guidance for what values are “good.” We survey experimental accounting researchers who assess the fit between plots of means and contrast weights as poor, acceptable, good, or excellent. We find that graphical presentation effects and researchers’ individual attributes influence their assessments. This suggests that research needs an ex ante method for evaluating q2, grounded empirically in the wisdom of the crowd across many different presentations, rather than relying solely on the idiosyncratic assessments of individual researchers. Using fuzzy set theory, we develop such a method that researchers can use to characterize q2 = 0.100, for example, as mostly good fit, leaning toward acceptable. Our approach has significant advantages over bright-line cutoffs commonly used for other statistical indices. Overall, our study can improve our discipline’s assessments of fit between experimental results and custom contrast weights. Data Availability: Data are available from the authors upon request.

In this paper, we test the “labor donation” hypothesis, which posits that intrinsically motivated individuals willingly accept lower compensation to work in nonprofit organizations (NPOs). We do so by examining the response of NPO CEO compensation to exogeneous increases in labor costs resulting from state-level minimum wage hikes, finding these increases are followed by declines in CEO compensation. Consistent with the labor donation hypothesis, we find the declines in compensation are larger for CEOs who we expect to have greater intrinsic motivation, i.e., those whose NPOs are headquartered in counties with higher levels of religiosity, in counties with greater levels of social capital, and those who work for a local NPO as opposed to a national NPO. In contrast to the decline in compensation we observe for NPO CEOs, we do not find an impact on for-profit CEO compensation.