This paper estimates the effect of bankruptcy court caseload on access to credit by exploiting firms’ plausibly exogenous exposure to the largest recorded drop in court backlog in the United States following the 2005 consumer bankruptcy reform. I show that a drop in court congestion reduces the time firms spend in bankruptcy and increases recovery values, which is priced into credit spreads and loan maturities. Consistent with a shock to credit supply, less congested courts increase firm leverage but leave default risk unchanged. A back-of-the-envelope calculation suggests that backlog in bankruptcy courts costs corporate borrowers at least $740 million per year in interest payments.

An extensive literature studies interactions of stock market anomalies using double-sorted portfolios. But given hundreds of known candidate anomalies, examining selected interactions is subject to a data mining critique. In this paper, we conduct a comprehensive analysis of all possible double-sorted portfolios constructed from 102 underlying anomalies. We find hundreds of statistically significant anomaly interactions, even after accounting for multiple hypothesis testing. An out-of-sample trading strategy that invests in the top backward-looking double-sort strategy generates equal-weighted (value-weighted) monthly average returns of 4% (2.7%) at an annualized Sharpe ratio of 2 (1.38), on par with state-of-the-art anomaly-based machine learning strategies.

We study the relationship between credit expansions, macroeconomic fluctuations, and financial crises using a novel database on the sectoral distribution of private credit for 117 countries since 1940. We document that, during credit booms, credit flows disproportionately to the non-tradable sector. Credit expansions to the non-tradable sector, in turn, systematically predict subsequent growth slowdowns and financial crises. In contrast, credit expansions to the tradable sector are associated with sustained output and productivity growth without a higher risk of a financial crisis. To understand these patterns, we show that firms in the non-tradable sector tend to be smaller, more reliant on loans secured by real estate, and more likely to default during crises. Our findings are consistent with models in which credit booms to the non-tradable sector are driven by easy financing conditions and amplified by collateral feedbacks, contributing to increased financial fragility and a boom–bust cycle.

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.