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We calibrate a dynamic model of credit risk and analyze the relation between growth options and credit spreads. Our model features real and financing frictions, a technology with decreasing returns to scale, and endogenous investment options driven by both systematic and idiosyncratic shocks. We find a negative relation between credit spreads and growth options after controlling for determinants of credit risk. This negative relation is a result of the current decision to invest and the associated change in leverage, which, in the presence of external financing needs and financing frictions, increase credit spreads while reducing the value of future investments. We do not find evidence that growth options accrue value in response to systematic risk, thus increasing credit risk premia.

Research summary: This article explores the relationship between corporate social irresponsibility (CSI) and financial risk. We posit that media coverage of CSI generates risk by providing conditions that increase the potential for stakeholder sanctions. Through analyzing an international panel of 539 firms during 2008–2013, we find that firms receiving higher CSI coverage face higher financial risk. We show that the reach of the reporting media outlet is a critical condition for this relationship. Once the outlet has a high reach, the severity of CSI coverage is a boundary condition that further reinforces the effect. Our findings complement existing theory about the risk‐mitigating effect of corporate social responsibility by illuminating the risk‐generating effect of CSI coverage. For executives, these insights suggest complementary strategies for corporate risk management. Managerial summary: This article examines the effect of negative news on financial risk. It shows that negative media articles regarding environmental, social, and governance (ESG) issues increase a firm's credit risk. It also provides a detailed analysis of the impact of an article's reach and severity, i.e., how many readers are exposed to the article and how harshly it criticizes the firm. The results allow to quantitatively assess the risk that emanates from negative ESG news. For executives, three strategies are derived for limiting a firm's exposure to this risk: balancing corporate social responsibility programs with operational safety programs, reporting suboptimal environmental and social performance transparently and proactively, and avoiding acquisition targets and markets with a legacy of negative news. Copyright © 2017 John Wiley & Sons, Ltd. Video

What makes an asset a “safe” asset? We study a model where two countries each issue sovereign bonds to satisfy investors’ safe asset demands. The countries differ in the float of their bonds and the fundamental resources available to rollover debts. A sovereign’s debt is safer if its fundamentals are strong relative to other possible safe assets, not merely strong on an absolute basis. If demand for safe assets is high, a large float enhances safety through a market depth benefit. If demand for safe assets is low, then large debt size is a negative as rollover risk looms large.

As an integrated part of a supply contract, trade credit has intrinsic connections with supply chain coordination and inventory management. Using a model that explicitly captures the interaction of firms’ operations decisions, financial constraints, and multiple financing channels (bank loans and trade credit), this paper attempts to better understand the risk-sharing role of trade credit—that is, how trade credit enhances supply chain efficiency by allowing the retailer to partially share the demand risk with the supplier. Within this role, in equilibrium, trade credit is an indispensable external source for inventory financing, even when the supplier is at a disadvantageous position in managing default relative to a bank. Specifically, the equilibrium trade credit contract is net terms when the retailer’s financial status is relatively strong. Accordingly, trade credit is the only external source that the retailer uses to finance inventory. By contrast, if the retailer’s cash level is low, the supplier offers two-part terms, inducing the retailer to finance inventory with a portfolio of trade credit and bank loans. Further, a deeper early-payment discount is offered when the supplier is relatively less efficient in recovering defaulted trade credit, or the retailer has stronger market power. Trade credit allows the supplier to take advantage of the retailer’s financial weakness, yet it may also benefit both parties when the retailer’s cash is reasonably high. Finally, using a sample of firm-level data on retailers, we empirically observe the inventory financing pattern that is consistent with what our model predicts. This paper was accepted by Vishal Gaur, operations management.

The authors present empirical evidence that borrowers, consciously or not, leave traces of their intentions, circumstances, and personality traits in the text they write when applying for a loan. This textual information has a substantial and significant ability to predict whether borrowers will pay back the loan above and beyond the financial and demographic variables commonly used in models predicting default. The authors use text-mining and machine learning tools to automatically process and analyze the raw text in over 120,000 loan requests from Prosper, an online crowdfunding platform. Including in the predictive model the textual information in the loan significantly helps predict loan default and can have substantial financial implications. The authors find that loan requests written by defaulting borrowers are more likely to include words related to their family, mentions of God, the borrower's financial and general hardship, pleading lenders for help, and short-term-focused words. The authors further observe that defaulting loan requests are written in a manner consistent with the writing styles of extroverts and liars.

We propose a new approach to studying the pass-through of credit expansion policies that focuses on frictions, such as asymmetric information, that arise in the interaction between banks and borrowers. We decompose the effect of changes in banks’ cost of funds on aggregate borrowing into the product of banks’ marginal propensity to lend (MPL) to borrowers and those borrowers’ marginal propensity to borrow (MPB), aggregated over all borrowers in the economy. We apply our framework by estimating heterogeneous MPBs and MPLs in the U.S. credit card market. Using panel data on 8.5 million credit cards and 743 credit limit regression discontinuities, we find that the MPB is declining in credit score, falling from 59% for consumers with FICO scores below 660 to essentially zero for consumers with FICO scores above 740. We use a simple model of optimal credit limits to show that a bank’s MPL depends on a small number of parameters that can be estimated using our credit limit discontinuities. For the lowest FICO score consumers, higher credit limits sharply reduce profits from lending, limiting banks’ optimal MPL to these consumers. The negative correlation between MPB and MPL reduces the impact of changes in banks’ cost of funds on aggregate household borrowing, and highlights the importance of frictions in bank-borrower interactions for understanding the pass-through of credit expansions.

We analyze lending by traditional as well as fintech lenders during COVID-19. Comparing samples of fintech and bank loan records across the outbreak, we find that fintech companies are more likely to expand credit access to new and financially constrained borrowers after the start of the pandemic. However, this increased credit provision may not be sustainable; the delinquency rate of fintech loans triples after the outbreak, but there is no significant change in the delinquency of bank loans. Borrowers holding both loan types prioritize the payment of bank loans. These results shed light on the benefits provided by shadow banking in a crisis and hint at the potential fragility of such institutions when delinquency rates spike.

We model a loop between sovereign and bank credit risk. A distressed financial sector induces government bailouts, whose cost increases sovereign credit risk. Increased sovereign credit risk in turn weakens the financial sector by eroding the value of its government guarantees and bond holdings. Using credit default swap (CDS) rates on European sovereigns and banks, we show that bailouts triggered the rise of sovereign credit risk in 2008. We document that post-bailout changes in sovereign CDS explain changes in bank CDS even after controlling for aggregate and bank-level determinants of credit spreads, confirming the sovereign-bank loop.

Using U.S. data from 1929 to 2015, we show that elevated credit-market sentiment in year t − 2 is associated with a decline in economic activity in years t and t + 1. Underlying this result is the existence of predictable mean reversion in credit-market conditions. When credit risk is aggressively priced, spreads subsequently widen. The timing of this widening is, in turn, closely tied to the onset of a contraction in economic activity. Exploring the mechanism, we find that buoyant credit-market sentiment in year t − 2 also forecasts a change in the composition of external finance: net debt issuance falls in year t, while net equity issuance increases, consistent with the reversal in credit-market conditions leading to an inward shift in credit supply. Unlike much of the current literature on the role of financial frictions in macroeconomics, this article suggests that investor sentiment in credit markets can be an important driver of economic fluctuations.