Journal of Accounting & Economics最新文献

In 2013, the U.S. Consumer Financial Protection Bureau released a database of consumer complaints filed against banks under its supervision (“CFPB banks”). We find that after the disclosure, rival banks exhibit a greater increase in mortgage approval rates in markets with more intensive mortgage complaints about CFPB banks. The effect is weaker when rivals have more expertise in the local market, are less concerned about credit risk due to mortgage sales, and locate in areas with more alternative information about the CFPB banks. The effect is concentrated in severe complaints and complaints related to loan underwriting practices. In addition to approving more loans, rivals also open more branches and are more likely to post a job opening in these markets. The findings suggest that these banks learn from the nonfinancial disclosures about operational deficiencies of peers (i.e., CFPB banks) in local markets, which alleviates their adverse selection concern about expanding.

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.

The Securities and Exchange Commission encourages the presentation of information or data in graphical form to improve users' ability to understand financial disclosures. We find a dramatic increase in the disclosure of both qualitative and quantitative infographics in 10-K filings over time and substantial cross-sectional variation in firms' choices regarding image types, data content, and the placement of infographics within 10-Ks. We provide evidence on factors associated with firms’ use of infographics and explore the persistence with which they are disclosed over time. Finally, we investigate the relation between the use of infographics and uncertainty in capital markets.

We develop the concept of auditor industry range as the extent to which an auditor has experiences in auditing clients from different industries, and we link this construct to auditor performance, drawing on prior research in psychology and cognitive science. We find that auditors with a wide range of industry experiences are more likely to require audit adjustments than auditors with a narrow range. We conduct an extensive set of analyses to mitigate the concern that our results are driven by endogenous matching between auditors and clients. The positive relation between auditor industry range and audit adjustments exists regardless of whether the industries covered by an auditor's portfolio exhibit strong or weak economic co-movement, and the relation is stronger for more complex clients, in more uncertain environments, and for auditors with more years of audit experience. Overall, our findings suggest that an auditor's diverse experiences in different industries can enhance audit quality.

We examine whether performance reporting leads to inconsistent enforcement at the Securities and Exchange Commission (SEC). In a sample of over 13,000 SEC enforcement actions, we show that SEC staff respond to performance-reporting pressures and file more enforcement actions in September, the final month of the SEC's fiscal year, than in any other month. The increase in case volume in September is not fully explained by staff filing more procedural cases or accelerating case filings. Instead, SEC staff pursue less complex cases and agree to more lenient financial and non-financial sanctions to increase case volume in September. We attempt to rule out alternative explanations for our results, including natural SEC workflow and resource constraints. Overall, our findings suggest that performance reporting creates agency conflicts that lead to regulatory inconsistency within the fiscal year.

This study presents a model in which behavioral investors shape their current expectations based on statistical analysis of historical non-disclosure events. Investors may hold overly optimistic expectations following a non-disclosure event, thereby disrupting unraveling toward forthcoming disclosures. While a regulator can mandate disclosure, this protective intervention has its drawbacks. Overprotection prevents investors from learning from losses and leads to cycles of high compliance followed by high mispricing when innovations in transactions render current regulations ineffective. An unregulated market, on the other hand, tends toward high transparency over time. The model further explains negative market reactions to regulation, an association between price drift and transparency, reversals in market confidence, and that regulators should favor laissez-faire in times of investor pessimism. Further implications are explored for regulations that facilitate learning and prevent cycles.

This paper explores the effects of public information such as accounting earnings in a competitive lending setting with risk shifting. Debt financing creates incentives for borrowers to take on excessive risks, in particular in bad states of the world. If a privately informed inside creditor bids against outside creditors to extend a loan, public information levels the playing field, which affects the bidding and risk shifting. Nonetheless, a perfect public signal would yield the least efficient outcome: introducing some measurement noise alleviates risk shifting by subjecting outside creditors to the winner’s curse, allowing borrowers in bad states cheaper access to loans. However, for pessimistic priors about the borrower, greater public signal precision can alleviate risk shifting, at the margin. We discuss implications for financial reporting regulations along the business cycle and for creditor turnover.

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.