Working Paper: NBER ID: w11735
Authors: David K. Musto; Nicholas S. Souleles
Abstract: To compute risk-adjusted returns and gauge the volatility of their portfolios, lenders need to know the covariances of their loans' returns with aggregate returns. Cross-sectional differences in these covariances also provide insight into the nature of the shocks hitting different types of consumers. We use a unique panel dataset of credit bureau records to measure the 'covariance risk' of individual consumers, i.e., the covariance of their default risk with aggregate consumer default rates, and more generally to analyze the cross-sectional distribution of credit, including the effects of credit scores. We obtain two key sets of results. First, there is significant systematic heterogeneity in covariance risk across consumers with different characteristics. Consumers with high covariance risk tend to also have low credit scores (high default probabilities). Second, the amount of credit obtained by consumers significantly increases with their credit scores, and significantly decreases with their covariance risk (especially revolving credit), though the effect of covariance risk is smaller in magnitude.
Keywords: No keywords provided
JEL Codes: E21; E51; G21
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| consumer characteristics (D12) | covariance risk (C10) |
| covariance risk (C10) | credit allocation (E51) |
| credit scores (G51) | credit allocation (E51) |
| covariance risk (C10) | credit scores (G51) |
| demographic characteristics (J21) | covariance risk (C10) |
| lack of health insurance (I13) | covariance risk (C10) |
| divorce rates (J12) | covariance risk (C10) |
| covariance risk (C10) | revolving credit (G21) |