This dashboard contains information derived from a random sample of deidentified, consumer-level records from a major credit bureau. The credit bureau data are from 2018 and contain more than 5 million records. We also incorporate estimates from summary tables of the US Census Bureau’s American Community Survey (ACS). We use ACS one-year estimates (2017) where possible, but for areas with smaller populations and for metrics that incorporate zip code–level information, we use the ACS five-year estimates (2013–17).
We define people of color as those who are African American, Hispanic, Asian or Pacific Islander, American Indian or Alaska Native, another race other than white, or multiracial. Debt in collections includes past-due credit lines that have been closed and charged-off on the creditor’s books as well as unpaid bills reported to the credit bureaus that the creditor is attempting to collect. For example, credit card accounts enter collections once they are 180 days past due. Retail installment loans are retail purchases with installment terms—for example, a loan from a furniture store to buy a couch. The map breaks are determined using the Jenks Natural Breaks method.
For more information and metric definitions, view and download the technical appendix.
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This data dashboard was funded by the Annie E. Casey Foundation, with additional support from the Ford Foundation in 2017. We are grateful to them and to all our funders, who make it possible for Urban to advance its mission. The views expressed are those of the authors and should not be attributed to the Urban Institute, its trustees, or its funders. Funders do not determine research findings or the insights and recommendations of our experts. More information on our funding principles is available here. Read our terms of service here.
Caroline Ratcliffe and Signe-Mary McKernan had the original vision for Debt in America. We are grateful to Caroline, Cary Lou, and Hannah Hassani for their work on previous versions of this dashboard.
We thank John van Alst, Henry Chen, and Chris Kukla for helpful counsel in finalizing the auto loan variables and developing the narrative. We also thank Don Baylor and Velvet Bryant of the Annie E. Casey Foundation; John Howat, Chi Chi Wu, and Michael Best of the National Consumer Law Center; Heidi Goldberg of the National League of Cities; and Sue Berkowitz of SC Appleseed for their input.