Knowledge that Transforms

We take advantage of a new composite measure of political risk (Hassan et al., 2019) to study the effects of firm-level political risk on private debt markets. First, we use panel data tests and exploit the redrawing of US congressional districts to uncover plausibly exogenous variation in firm-level political risk. We show that borrowers’ political risk is linked to interest rates set by lenders. Second, we test for the transmission of political risk from lenders to borrowers. We predict and find that lender-level political risk propagates to borrowers through lending relationships. Our analysis allows for endogenous matching between lenders and borrowers and indicates the presence of network effects in diffusing political risk throughout the economy. Finally, we introduce new text-based methods to analyze the distinct sources of political risk to lenders and borrowers and provide textual evidence of the transmission of political risk from lenders to borrowers.

Little is known about how the SEC selects its targets for investigation. We study this subject using a new database of formal SEC investigations. We predict and find that case selection is associated with a firm's (i) likelihood of regulatory noncompliance, (ii) exposure to private sector scrutiny, and (iii) conspicuous public trigger events. The relationship between investigations and regulatory noncompliance and private sector scrutiny preferences is sensitive to SEC constraints, whereas the relationship with triggers is not. We also examine the association between investigation motives and enforcement actions, an important SEC outcome reported to Congress. While regulatory noncompliance-motivated and public trigger-motivated investigations are more likely to result in public charges, specifically when the SEC is constrained, private sector scrutiny-motivated investigations are less likely to result in public charges. Finally, investigation rates of potential targets are associated with the career trajectories of SEC personnel, while investigation outcomes are not.

We examine broad effects of MiFID II, which mandated unbundled pricing of analyst research in the European Union beginning in 2018. We find significant reductions in sell-side analyst following, particularly for firms for which the marginal analyst was less important (larger, older, less volatile firms with greater coverage and more accurate forecasts). High quality analysts (more accurate, experienced, and in positions of seniority) were more likely to leave the sell-side and move to the buy-side, while remaining sell-side analysts increased efforts to make their forecasts more informative (more accurate, more detailed, and more likely to include informative recommendations resulting in larger stock price responses). Firms responded to a loss of sell-side coverage with more frequent, forward-looking, and informative investor relations events, especially for firms that lost the most coverage. Our results support recent theoretical analysis predicting that unbundling had significant implications for sell-side research, buy-side research, and firm responses.

Previous studies find mixed evidence on whether institutional investors exploit capital market anomalies. Examining a large sample of accounting-based anomalies, we find that institutions trade in the wrong direction of overreaction anomalies, but in the right direction of underreaction anomalies. These heterogenous trading patterns, rather than reflecting institutions' differential anomaly trading skills, can be simply explained by institutions’ tendency to trade in the same direction as the sentiment of news. Examining earnings news and a comprehensive sample of newswire releases, we find strong support for this explanation. Finally, institutional trading appears to exacerbate (mitigate) mispricing associated with overreaction (underreaction) anomalies.

We review the accounting literature on innovation, focusing on the economic attributes of innovation that collectively differentiate innovation from other assets: novelty, nonrivalry, and partial excludability. These attributes help innovation drive economic growth but create unique information-based challenges that accounting information and researchers are well suited to address. We discuss the definition and measurement of innovation and highlight common mistakes researchers make when measuring innovation and when using sources of plausibly exogenous variation. We then review the accounting literatures on the disclosure, management, financial reporting, taxation, and contracting and financing of innovation. For each of these literatures we identify challenges and opportunities for future research.

Minnis, Sutherland, and Vetter (MSV) documents a sharp decline in lenders’ collection of attested financial statements (including unqualified audits, reviews, and compilations) over the period 2002 to 2017. They attribute this change to lenders adopting new technology and new non-bank lenders entering the lending market. In this discussion, I explore several dimensions of their findings. First, I provide a framework for usefulness of financial statement information in debt contracting. Using this framework, I consider how financial statements may be useful for the small and medium loans the authors study, and how this role could be disrupted. Second, I consider how financial technology (FinTech) has disrupted traditional lending and potentially changed the role of financial statements. Finally, I consider the implications for this change on the accounting profession.

The patent system grants inventors temporary monopoly rights in exchange for a public disclosure detailing their innovation. These disclosures are meant to allow others to recreate and build on the patented innovation. We examine how the quality of these disclosures affects follow-on innovation. We use the plausibly exogenous assignment to patent applications of examiners who differ in their enforcement of disclosure requirements as a source of variation in disclosure quality. We find that some examiners are significantly more lenient with respect to patent disclosure quality requirements, and that patents granted by these examiners include significantly lower-quality disclosures and generate significantly less follow-on innovation. Overall, our evidence suggests that high-quality patent disclosures create knowledge spillovers that spur follow-on innovation.

I explore whether big-data sources can crowd out the value of private information acquired through lending relationships. Institutional lenders have been shown to exploit their access to borrowers' private information by trading on it in financial markets. As a shock to this advantage, I use the release of the satellite data of car counts in store parking lots of U.S. retailers. This data provides accurate and near–real-time signals of firm performance, which can undermine the value of borrowers' private information obtained through syndicate participation. I find that once the satellite data becomes commercially available, institutional lenders are less likely to participate in syndicated loans. The effect is more pronounced when borrowers are opaque or disseminate private information to their lenders earlier and when the data predicts borrower performance more accurately. I also show that institutional lenders’ reduced demand for private information leads to less favorable loan terms for borrowers.

Internal and external parties meaningfully shape corporate tax outcomes. However, we lack a holistic understanding of the major parties involved and their comparative effects. Using proprietary IRS data for public and private firms, we identify the top executives, corporate accountants, external accounting firms, and individual tax preparers and examine the comparative importance of these parties on corporate tax outcomes. We find that external individual tax preparers matter much more than the accounting firms that employ them. Internal actors (top accountants and executives) explain more of the variation in corporate tax outcomes than external actors (individual tax preparers and accounting firms). We also find some evidence that individuals’ characteristics are associated with the tax behavior of the corporations they serve. Overall, we conclude that some of the actors who are unobservable in public data play a greater role in corporate tax outcomes than parties that are a focus of prior research.

This study empirically examines whether firms reclassify related-party payments to avoid the base erosion and anti-abuse tax (BEAT) of the Tax Cuts and Jobs Act (TCJA). We leverage the BEAT filing threshold and use both a difference-in-differences design among U.S. firms and a triple-difference design utilizing the parent company's location to provide evidence that firms reclassify related-party payments to avoid the BEAT. This effect is stronger in firms with greater pre-TCJA income shifting incentives. We estimate a $6 billion aggregate reduction in U.S. taxes for our sample firms in 2018. We also examine the consequences of reclassifying related-party payments and find some evidence of an increase in tax reserves and a reduction in internal information quality for firms that engage in cost reclassification to avoid the BEAT. These findings help explain observed BEAT collection shortfalls, contribute to the current policy debate about international tax reform, and document spillover effects of tax policy.