What does this measure?
The number of owner-occupied units (not rented) as a percent of all occupied units (not vacant) for various racial and ethnic groups.
Why is this important?
Historically, members of some racial and ethnic groups have suffered discrimination in buying homes and accessing home mortgages. A home is a vital financial asset for a family and an investment in both the local neighborhood and surrounding community.
How is our county doing?
Essex County had greater racial and ethnic disparities in homeownership rates than the nation. In 2017-21, 70% of Asian and white residents in Essex County owned their homes. Significantly higher than those for Black or African American residents (38%) and Hispanic residents (31%). Nationwide, homeownership was substantially higher among African American and Hispanic residents, at 43% and 49%, respectively, compared to Essex. The County's rates were similar to Massachusetts as a whole, except that a smaller share of Asian residents owned homes at the state level (55%).
Since 2000, the County's homeownership rate among Asian residents increased the most, by 19 percentage points, compared to increases of 13 points among African American and 10 points among Hispanic residents. The rate was steady for white residents.
Disparities differed among communities in Essex County. In Lawrence, the white homeownership rate (32%) was almost than half that of the County, while the Hispanic rate (24%) was 7 points lower. In Lynn, African American and Hispanic rates were similar to the County, while rates were lower among Asian and white residents, at 42% and 60%, respectively.
How do we compare to similar counties?
Compared to Essex, 2017-21 homeownership rates were higher for all racial and ethnic groups in Lake, IL, but especially so among Hispanic (58%) and white (80%) residents. In Middlesex, MA, rates were similar for most groups except Asian residents, who had a lower rate (57%) than Essex. Westchester, NY had similar disparities, but its rates were higher for Hispanics (37%), and slightly higher for white residents (73%).
Why do these disparities exist?
A variety of research has shown how disparities in homeownership are connected to racial inequities within systems beyond housing, including financial services, labor market and intergenerational wealth. Historic practices including redlining, exclusionary mortgage practices and restrictive covenants barring property from being owned by members of specific groups directly locked people out of homeownership. These had intergenerational effects when people of color were unable to benefit from wealth transfers of home equity as white homebuyers can. Since Black and Latino households generally have lower wages and wealth accumulation, they have less resources for down payments and higher debt to income ratios. With lower credit scores than other racial/ethnic groups, communities of color may be less likely to qualify for mortgages as underwriting standards increase. Many in the Black and Latino community may lack information about the home buying process and choose to stay renters. Discrimination during the home buying process also influences whether people of color buy a house. Researchers have found that during the search process, people of color were shown fewer houses and provided less information than whites.
Notes about the data
The multiyear figures are from the Census Bureau's American Community Survey. The bureau combined five years of responses to the survey to provide estimates for smaller geographic areas and increase the precision of its estimates. However, because the information came from a survey, the samples responding to the survey were not always large enough to produce reliable results, especially in small geographic areas. CGR has noted on data tables the estimates with relatively large margins of error. Estimates with three asterisks have the largest margins, plus or minus 50% or more of the estimate. Two asterisks mean plus or minus 35%-50%, and one asterisk means plus or minus 20%-35%. For all estimates, the confidence level is 90%, meaning there is 90% probability the true value (if the whole population were surveyed) would be within the margin of error (or confidence interval). The survey provides data on characteristics of the population that used to be collected only during the decennial census. Data for this indicator are released annually in December.