Syndicated loan data provided by DealScan is an essential input in banking research to answer urging questions on bank lending, e.g., in the presence of financial or geopolitical shocks or climate change. However, many data options raise the question of how to choose the estimation sample. We employ a standard regression framework analyzing bank lending during the financial crisis of 2007/08 to study how conventional but varying usages of DealScan affect the estimates. The key finding is that the direction of coefficients remains relatively robust. However, statistical significance depends on the data and sampling choice, and we provide guidelines for applied research.

We compare the effects of external financing shocks on patient mortality at nonprofit and for-profit hospitals. Using confidential patient-level data, we find that patient mortality increases to a lesser extent at nonprofit hospitals than at for-profit ones facing exogenous, negative shocks to debt capacity. Such an effect is not driven by patient characteristics or their choices of hospitals. It is concentrated among patients without private insurance and patients with higher-risk diagnoses. Potential economic mechanisms include nonprofit hospitals' having deeper cash reserves and greater ability to maintain spending on medical staff and equipment, even at the expense of lower profitability. Overall, our evidence suggests that nonprofit organizations can better serve social interests during financially challenging times.

We study the corporate-loan pricing decisions of a major, systemic bank during the Greek financial crisis. A unique aspect of our data set is that we observe both the actual interest rate and the “break-even rate” (BE rate) of each loan, as computed by the bank’s own loan-pricing department (in effect, the loan’s marginal cost). We document that low-BE-rate (safer) borrowers are charged significant markups, whereas high-BE-rate (riskier) borrowers are charged smaller and even negative markups. We rationalize this de facto cross-subsidization through the lens of a dynamic model featuring depressed collateral values, impaired capital-market access, and limit pricing.