Association for Public Policy Analysis & Management

Our analysis describes how subprime-scored households are distributed across the Seventh district by state, metropolitan area, and neighborhood population density. In addition, this study observes differences in neighborhood characteristics, types of debt held, and amount of debt carried in neighborhoods with relatively large shares of subprime-scored households compared to neighborhoods with few subprime-scored households. We build on the descriptive work of other Federal Reserve Banks using the Federal Reserve Bank of New York’s Consumer Credit Panel (CCP/Equifax), including studies that analyzed outstanding debt by state; credit access and management in counties and zip codes; credit utilization by neighborhood income; the distribution of subprime scores within a metro area; and the relationship between (neighborhood) location characteristics and risk scores in Indian country. Zip code-level data from the Internal Revenue Service and the American Community Survey supplement our analysis.

We conclude from our results that neighborhoods with a greater share of subprime-scored households exhibit more signs of economic adversity and lower levels of credit use compared to neighborhoods where the distribution of credit scores tilts higher. Similar to other work that has found a relationship between debt collections and signs of distress at the neighborhood level, differences along these dimensions have the potential to create additional challenges for the residents living in these neighborhoods. Policy concerns may arise if there is a self-reinforcing mechanism of hardship for households whose lower credit scores may have already played some role in neighborhood selection. The analysis presented here may therefore help inform areas where community advocates may wish to direct resources for neighborhood investments, as well as the associated socio-economic and financial challenges. It may also guide the practices or advice used by credit counselors who work with low-scoring households, helping them recognize the neighborhood economic adversities correlated with low scores. Our work may also add to discussions about the necessary innovations to improve the flow of lending and investment to underserved neighborhoods.