Cyclicality in the losses of bank loans is important for bank risk management. Because loans have a different risk profile than bonds, evidence of cyclicality in bond losses need not apply to loans. Based on unique data we show that the default rate and loss given default of bank loans share a...

Some credit booms, though by no means all, result in financial crises. While risk-taking incentives seem a plausible cause, market participants do not appear to anticipate increasing risk. We show how credit expansions driven by credit supply shocks may be misunderstood as productivity driven,...

A novel debate within competition policy and regulation circles is whether autonomous machine learning algorithms may learn to collude on prices. We show that when fims face short-run price commitments, independent Q-learning (a simple but well-established self-learning algorithm) learns to...

The econometrics literature proposed several new causal machine learning methods (CML) in the past few years. These methods harness the strength of machine learning methods to flexibly model the relationship between the treatment, outcome and confounders, while providing valid inferential...

A new empirical reduced-form model for credit rating transitions is introduced. It is a parametric intensity-based duration model with multiple states and driven by exogenous covariates and latent dynamic factors. The model has a generalized semi-Markov structure designed to accommodate many of...

In this article, we provide a novel rationale for credit ratings. The rationale that we propose is that credit ratings serve as a coordinating mechanism in situations where multiple equilibria can obtain. We show that credit ratings provide a focal point for firms and their investors, and...