How to Use These Data

Our dataset provides the following information for counties in every state:

  • number of homeowners with incomes below 100 percent of the area median income, broken out by all homeowners and those with an active mortgage (2019 American Community Survey data, five-year estimates)
  • number of homeowners with incomes below 150 percent of the area median income, broken out by all homeowners and those with an active mortgage (2019 American Community Survey data, five-year estimates)
  • number of homeowners of color making between 100 and 150 percent of the area median income (2019 American Community Survey data, five-year estimates)
  • median monthly housing costs and the share of homeowners who are cost burdened, defined as those spending at least 30 percent of annual income on housing (2019 American Community Survey data, five-year estimates)
  • share of all homeowners, by race or ethnicity (2019 American Community Survey data, five-year estimates)
  • unemployment rate (Bureau of Labor Statistics data)
  • a predictive foreclosure rate showing foreclosures as a share of total homeowners, based on economic and housing market conditions (Urban Institute data)

With these data, state policymakers can better target HAF dollars to their residents’ specific needs.

Using these data: A Maryland case study

Below, we’ve explored data for Maryland as an example to show how policymakers could use these data to understand homeowners’ needs.

Maryland has nearly 1.5 million homeowners, of which we estimate more than two-thirds earn less than 150 percent of the area median income. The Maryland counties with the highest predicted foreclosure rates account for almost all the state’s census tracts where most homeowners are homeowners of color (Baltimore City, Baltimore County, Charles County, and Prince George’s County). These four counties collectively are home to 43 percent of all Maryland households earning less than 100 percent of the area median income, more than two-thirds of whom have outstanding mortgages.

Predicted foreclosure rate

Source: Urban Institute.

 

Share of households of color, by census tract

Source: 2019 American Community Survey.

 

Prince George’s and Baltimore Counties have similar foreclosure risk and a similar number of homeowners with low-to-moderate incomes, but the data show that homeowners in Prince George’s County tend to face a higher cost burden, spending more on their housing than Baltimore County homeowners. As a result, Prince George’s County has a higher share of borrowers of color earning between 100 and 150 percent of the area median income. These data suggest that policymakers could target Prince George’s County to assist homeowners of color in need.

 

Households of color earning between 100 and 150 percent of the area median income, as a share of total households

Source: 2019 American Community Survey.