Central banks

We use a novel data set containing all corporate loans throughout the Eurozone to document a series of novel stylized facts on the relationship between collateral and the probability of default. First, we show that the pervasive empirical finding that riskier borrowers pledge collateral is driven by economists’ informational disadvantage relative to banks. Accounting for time-varying bank- and firm-specific risk factors produces negative correlations consistent with theory. Second, the relationship between pledging collateral and the probability of default is non-linear.

We use a novel data set containing all corporate loans throughout the Eurozone to document a series of novel stylized facts on the relationship between collateral and the probability of default. First, we show that the pervasive empirical finding that riskier borrowers pledge collateral is driven by economists’ informational disadvantage relative to banks. Accounting for time-varying bank- and firm-specific risk factors produces negative correlations consistent with theory. Second, the relationship between pledging collateral and the probability of default is non-linear.

We propose a robust semi-parametric framework for persistent time-varying extreme tail behavior, including extreme Value-at-Risk (VaR) and Expected Shortfall (ES). The framework builds on Extreme Value Theory and uses a conditional version of the Generalized Pareto Distribution (GPD) for peaks-over-threshold (POT) dynamics.

Kelsey O'FlahertyThe 2021-2022 inflation episode presented the first opportunity to examine inflation and price dispersion using U.S. scanner data in a high-inflation environment. Data from 50,000 outlets reveals that price changes across similar goods grew more dispersed in 2022 before falling again in 2023. This paper documents how price change dispersion interacts with households' product choices to generate substantial inflation heterogeneity.