We investigate how institutional (non-commercial bank) investors that simultaneously invest in a firm's debt and equity (dual-holders) influence the firm's voluntary disclosure. Because institutional dual-holders trade on private information gleaned through lending relationships, we predict and find that borrowers increase earnings forecast disclosure to reduce these investors' information advantage following the origination of loans with their participation. We also show that the increase in disclosure is stronger when the access to a borrower's private information endows dual-holders with a greater information advantage and when the consequences of this access are likely to be more pronounced. We further find that institutional dual-holders earn excess returns when trading equity of non-guider firms following loan origination, but not when firms issue guidance, confirming that earnings disclosure helps level the playing field among investors. Our findings highlight that firms actively use disclosure to mitigate the adverse effect of dual-holders on their information environment.

We investigate how the tone of sell-side debt analysts' discussions about debt-equity conflict events affects the informativeness of debt analysts' reports in debt markets. Conflict events such as mergers and acquisitions, debt issuance, share repurchases, or dividend payments potentially generate asset substitution or wealth expropriation by equity holders. We document that debt analysts routinely discuss these conflict events in their reports. More importantly, discussions about conflict events that we code as negative are associated with increases in credit spreads and bond trading volume. Consistent with the informational value of debt analysts' discussions in secondary debt markets, we find that negatively coded conflict discussions predict higher bond offering yields in the primary bond market. In additional analyses, we measure the tone of debt analysts' discussions based on their disagreement with the tone of equity analysts' discussions and find that the informativeness of debt analysts' reports is higher when our coding indicates that conflict events are viewed negatively by debt analysts but positively by equity analysts.

We examine the relation between accounting quality and debt concentration in corporate capital structures (i.e., firms' tendency to rely predominantly on only a few types of debt). Motivated by theoretical and empirical research that supports a strong link between debt concentration and creditors' coordination costs and the importance of accounting quality in reducing these costs, we hypothesize that firms with higher accounting quality have less concentrated debt structures. Measuring accounting quality with a comprehensive index based on the occurrence of material internal control weaknesses, accounting restatements, SEC AAERs, and firms' reliance on small auditors, we find that higher accounting quality is indeed associated with less concentrated debt structures. This relation is stronger for firms with higher default risk, as the probability that creditors need to coordinate is higher, and for firms with lower liquidation values, as creditor coordination to avoid liquidation is more important. Data Availability: Data are available from the public sources cited in the text.

We examine how personal lending relationships between lenders and managers are affected by information and accounting environments of borrowing firms. We address this question by exploring whether, following managerial turnover, lenders migrate with the manager from the firm where a relationship developed (origin firm) to the manager's new firm (destination firm). We find that the opacity of the external information environment of the destination firm significantly increases the probability of lenders' co-migration, while accounting irregularities at both the destination and origin firms decrease it. We also show that co-migration is affected by a lender's monitoring efficiency. A lender's monitoring efficiency increases its co-migration probability when a manager moves to an opaque firm, but not when she moves to a transparent one. When the destination or origin firm experiences accounting irregularities, even lenders with strong monitoring capabilities are mostly reluctant to continue their relationship with a migrating manager.

To mitigate information asymmetry about borrowers in developing economies, digital lenders use machine-learning algorithms and nontraditional data from borrowers’ mobile devices. Consequently, digital lenders have managed to expand access to credit for millions of individuals lacking a prior credit history. However, short-term, high-interest digital loans have raised concerns about predatory lending practices. To examine how digital credit influences borrowers’ financial well-being, we use proprietary data from a digital lender in Kenya that randomly approves loan applications that would have otherwise been rejected based on the borrower’s credit profile. We find that access to digital credit improves borrowers’ financial well-being across various mobile-phone-based well-being measures, including monetary transactions and balances, mobility, and social networks as well as borrowers’ self-reported income and employment. We further show that this positive impact is more pronounced when borrowers have limited access to credit, take loans for business purposes, and obtain more credit.