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.

DThe interactions between supply chains and sustainable finance have become a key area of research in financial markets, driven by growing global awareness of environmental and social challenges. Article 1 examines how lenders use sustainability clauses to monitor borrowers with negative environmental incidents and compares the use of this unique loan agreement design with conventional loan terms, financial and balance sheet-related clauses. We show that lenders are less inclined to include sustainability clauses in the loan agreement if a borrower has a history of negative environmental incidents. In contrast, lenders use sustainability clauses to attract institutional investors to participate in syndication rather than as monitoring tools for borrowers' environmental performance. Article 2 examines whether banks associated with biodiversity loss in the Amazon region experience a withdrawal of deposits when depositors become aware of their financing activities. I find empirical evidence that so-called ‘Amazon carbon banks’ experience slower growth in deposits once depositors learn about their financing activities. This effect is particularly pronounced when Amazon carbon banks have branches in counties that experience greater biodiversity loss compared to other branches. Article 3, how European companies that are heavily integrated into global supply chains (GSC) are affected by a supply chain disruption (Covid-19). We show that Covid-19 negatively affects the revenue growth of companies that are heavily dependent on GSC in their home country. Crucially, we uncover the role of banking relationships in mitigating the disruptive effects.

There is growing evidence on the role of economic conditions in the recent successes of populist and extremist parties. However, little is known about the role of over-indebtedness, even though debtor distress has grown in Europe following the financial crisis. We study the unique case of the Czech Republic, where by 2017, nearly one in ten citizens had been served at least one debtor distress warrant even though the country consistently features low unemployment. Our municipality-level difference-in-differences analysis asks about the voting consequences of a rise in debtor distress following a 2001 deregulation of consumer-debt collection. We find that debtor distress has a positive effect on support for (new) extreme right and populist parties, but a negative effect on a (traditional) extreme-left party. The effects of debtor distress we uncover are robust to whether and how we control for economic hardship; the effects of debtor distress and economic hardship are of similar magnitude, but operate in opposing directions across the political spectrum.

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.