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The distribution of subprime borrowers

Most economists agree the financial sector and high levels of household debt played an important role in the previous recession. But since 2008, the levels of both household debt relative to income and debt service payments relative to income have fallen. The reasons for the fall are hard to pin down and could be driven by a lower demand for credit by borrowers or stricter lending requirements by lenders. Nonetheless, an important implication of lower levels of debt and lower debt payments is an improvement in borrowers’ credit scores, as these factors would translate into less debt and fewer missed payments, which have an important weight in how these scores are computed.

The two graphs show the percentage of the population with a credit score below 660 in each U.S. county in 2009 and 2016. A person with a score below 660 will have a harder time securing credit from a lender and may have to pay a higher interest rate if a loan is secured. Comparing 2009 and 2016, we see that the percentage of the population with a subprime credit score has decreased substantially, consistent with the recent changes described above. In addition, the graphs show that counties in the south and southeast have a larger-than-average concentration of subprime population.

How these maps were created: The original post referenced interactive maps from our now discontinued GeoFRED site. The revised post provides replacement maps from FRED’s new mapping tool. To create FRED maps, go to the data series page in question and look for the green “VIEW MAP” button at the top right of the graph. See this post for instructions to edit a FRED map. Only series with a green map button can be mapped.

Suggested by Maximiliano Dvorkin.

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