Violations of financial covenants shift control rights to lenders. When borrowers have lending relationships with these lenders in control, they experience not only smaller declines in investment, but also lesser deteriorations in both firm survival probabilities and in sales. These effects are largely driven by opaque borrowers without any credit ratings. They are present where lending relationships existed already before loan issuance (ex-ante), but also where a contractual relationship without pre-issuance interaction is more mature (ex-post). Surprisingly, there is no evidence of any “dark side” of lending relationships when creditors are in control, such as an increase in interest expenses or a lesser degree of financial discipline.

Using Compustat to measure industry concentration in the U.S. is problematic. Popular approximations of the Herfindahl Index based on this data set have a vanishingly low correlation with the more comprehensive Census measure. As a result, major variables of interest in corporate finance show markedly different correlations with these indicators, which can lead to a breakdown of regression results. This confirms findings of an earlier article that has been ignored by recent empirical studies. I show that Census concentration ratios are excellent measures and provide a newly compiled data set based on all concentration data ever produced by the Department of Commerce – eliminating the need to use the convenient but flawed Compustat files.

Exploiting spatial and time variation, we find that banks geographically more exposed to lockdown measures experience an increase in loss provisions and non-performing loans. Exposures to the pandemic itself have a similar, but slightly weaker effect. We observe an increase in small business lending driven by government-guaranteed loans which seem to replace regular loans. Interestingly, lenders more exposed to lockdown measures rely more on government-guaranteed loans – even when controlling for borrower exposure. Finally, we observe a reduction in the number and average amount of syndicated loans for banks more affected by the pandemic, as well as an increase in interest spreads. These findings point to a negative impact of the pandemic on the supply side of finance, to previously unknown side effects of government support, and to the critical role of banks in channeling government support measures to small firms.

How do changes in banking regulation affect the syndicated loan market? Because branch networks and loan syndication both enable banks to diversify geographical credit risk, we investigate the staggered implementation of the Riegle–Neal Interstate Branching and Banking Efficiency Act of 1994. Exploiting that the act only changed the legal framework for out-of-state commercial banks, we find that branching deregulation decreased syndicated loan issuance but spurred bilateral lending to corporations. Consistent with a supply-driven substitution effect, this shift is also reflected in interest rate spreads. Our results suggest that changes to banking regulation can substantially alter credit allocation across loan types.

We study bank branching dynamics across 3,143 US counties and 26 years. During the last decade, banks closed their branches at an unprecedented rate. At its peak in 2009, there were 90,783 branches. By 2020, this number has fallen by 12 percent. While technological factors correlate with these branching dynamics, bank fragility and consolidation are also strongly associated with changes in the number of branches (and their openings and closures). Interestingly, technological capabilities to service customers, such as online banking, seem less tightly linked to de-branching than technological capabilities to process internal information. Our analysis shows that large banks rely on internal technology to shed branches, while small banks close branches when they are vulnerable or consolidate.

“Buy Now, Pay Later” (BNPL) is a key innovation in consumer payments. It bundles the sale of a product with a subsidized loan, effectively offering lower prices to low-creditworthiness customers. BNPL thereby allows merchants to price-discriminate among customers with different willingness-to-pay. Consistent with a price-discrimination mechanism, we show that BNPL increases sales by 20%, driven by low-creditworthiness customers and products where market power is larger. We find that the benefits of offering BNPL significantly outweigh the costs for the merchant. Our findings help to explain the surge in popularity of BNPL in e-commerce around the world.