Working Paper: NBER ID: w27994
Authors: Sigurd Galaasen; Rustam Jamilov; Ragnar Juelsrud; Hléne Rey
Abstract: What is the impact of granular credit risk on banks and 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 Gabaix and Koijen (2022, 2023)’s granular instrumental variable strategy to show that idiosyncratic borrower risk survives aggregation in banks’ portfolios. We 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, affecting sizeably the macroeconomy.
Keywords: granular credit risk; bank portfolios; macroeconomy; idiosyncratic risk
JEL Codes: E3; G2
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| idiosyncratic borrower risk (G51) | bank portfolios (G21) |
| granular credit risk (G21) | bank performance (G21) |
| negative firm shock (E44) | loan-level returns (G12) |
| adverse shocks to granular borrowers (F65) | reduced investment among non-granular borrowers (G51) |
| adverse shocks to granular borrowers (F65) | increased bankruptcy probabilities among non-granular borrowers (G33) |
| negative granular credit supply shock (E51) | likelihood of bankruptcy (G33) |
| negative granular credit shock (E44) | loan supply (E51) |
| negative granular credit shock (E44) | interest flows (E43) |