Exploiting the heteroskedasticity of the changes in short-term and long-term interest rates and exchange rates around the FOMC announcement, we identify three structural monetary policy shocks. We eliminate the predictable part of the shocks and study their effects on financial variables and macro variables. The first shock resembles a conventional monetary policy shock, and the second resembles an unconventional monetary shock. The third shock leads to an increase in interest rates, stock prices, industrial production, consumer prices, and commodity prices. At the same time, the excess bond premium and uncertainty decrease, and the U.S. dollar depreciates. Therefore, this third shock combines all the characteristics of a central bank information shock.

We analyze how the establishment of the Single Supervisory Mechanism (SSM) relates to patterns in banks’ lending activities, risk outcomes, and granular risks within the banking system. Using data on euro area banks from 2010 to 2021, we estimate idiosyncratic shocks to banks’ loan growth to construct a measure of loan growth volatility and to compute the “Banking Granular Residual.” Banks under SSM supervision exhibit lower volatility in loan portfolio growth, indicating more stable lending dynamics. Furthermore, the implementation of the SSM is associated with positive spillover effects on non-SSM banks’ lending and a weaker relationship between granular banking shocks and economic growth.

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.

This paper examines the impact of climate risks on the debt structure of a sample of U.S. firms from 2002 through 2020. Climate risks—mainly physical, regulatory, and transition risks—are associated with a concentrated debt structure for the affected firms. However, when climate risks propagate through the channels of expected bankruptcy costs and sustainability, they are associated with a more diversified debt structure. Additionally, climate risks asymmetrically impact the relationship between access to finance and debt structure. Results from a quasi-natural experiment reaffirm the impact of climate risks on debt structure.