Granular Credit Risk
What is the impact of granular credit risk on banks and on the economy? We provide the first causal identification of single-name counterparty exposure risk in bank portfolios by applying a new empirical approach on an administrative matched bank-firm dataset from Norway. Exploiting the fat tail properties of the loan share distribution we use a Gabaix and Koijen (2020a,b) granular instrumental variable strategy to show that idiosyncratic borrower risk survives aggregation in banks portfolios. We also find that this granular credit risk spills over from affected banks to firms, decreases investment, and increases the probability of default of non-granular borrowers, thereby sizably affecting the macroeconomy.
The views expressed are those of the authors and do not necessarily reflect those of Norges Bank. We thank our discussant José-Luis Peydró as well as Christoph Basten, Svetlana Bryzgalova, Andreas Fagereng, Julian di Giovanni, Francisco Gomes, Refet Gürkaynak, Victoria Ivashina, Joseba Martinez, Atif Mian, Steven Ongena, Elias Papaioannou, Anna Pavlova, Kasper Roszbach, Stephen Schaefer, Vania Stavrakeva, Kjetil Storesletten, Paolo Surico, Gianluca Violante and seminar participants at the CEPR/ERC/LBS Conference on Granularity and Applications, EEA 2020, SNDE 2020, WEAI 2020, LBS, Norges Bank, Oslo Macro Group, Statistics Norway and the University of Zurich for valuable comments and suggestions. Rey is very grateful to the ERC (Advanced Grant 695722). All errors are our own. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.