# Inctest = HHINCOME *0.95
# Single_earner_1 = INCTOT >= INCTEST
# single_earner_2 = any(Single_earner_1)

# new_df <- lville_2019 %>%
#   mutate(
#   earner_var = if_else(HHINCOME <= (0.95*INCTOT) , "single_earner", "multi_earner")
#   )
#     earner_var = case_when(
#     HHINCOME == 0 ~ 'no_earnings',
#     INCTOT >= 0.65 * HHINCOME ~ "single_earner",
#     TRUE ~ "multi_earner"
#     )
#   )

      # earner_type = case_when(
      #   HHINCOME == 0 ~ 'no_earnings',
      #   any(INCTOT >= 0.90 * HHINCOME) ~ 'single_earner',
      #   TRUE ~ 'multi_earner'


Access to safe and affordable housing is foundational for families’ well-being. In this report, we examine the intersection between gender and housing. We find that while in Louisville, women and men have similar rates of homeowership, women are far more likely to live in housing that is not affordable to them. This is exacerbated for women from a single-income home, women with children, and women of color. Disproportionate cost of living burdens and care-taking responsibilities can perpetuate a viscous cycle of inequity. Understanding the true size of the ‘equity gap’ can help inform policy decisions to stop this cycle from continuing.

Key Definitions

  • Cost-burdened household - when a household pays more than 30% of their income toward housing costs (including rent, utilities, mortgage payments, and any other homeownership costs). This is a standard cutoff for “affordability.”
  • Severely cost-burdened household - when a household has to pay more than 50% of their income toward housing costs.
  • Single-earner household and Multiple-earner household - A single-income household has only one wage earner, while a multiple-earner household includes multiple earners. Throughout the data, we usually group households into three groups:
    • Multiple-earner households
    • Single-earner, female-headed households
    • Single-earner, male-headed households
  • Households with Children include any households with children under age 18. The Census Bureau collects information on whether household members are related, but this data does not encompass all living situations, particularly people raising children who are not legally related to them. We assume that adults are responsible for the care of any children living in their household. While this is likely complicated in large households with multiple adults and families, all of our analysis that includes children focuses on households with a single income-earner, so we are confident that this assumption reflects their reality in most cases.

The fact that a household falls under the single-earner category reflects their financial situation rather than the personal relationships of the people within the household. Single-earner households might include someone living on their own or living with children, or they might have a spouse or partner who is not working or who lives outside the household.

Key Takeaways

  1. Women and men in single-income households have very similar rates of homeownership in Louisville.
  2. On average, women in single-income households make significantly less money than men from single-income households. As a result, almost half of Louisville women in single-income households are cost-burdened, putting them at increased risk of eviction or foreclosure.
  3. Around 39% of women in single-income households earn a living wage that covers their basic expenses. Single-earner women without children are most likely to earn a living wage. Only around 1 in 4 single-income women with one child, 1 in 20 single-income women with two children, and 1 in 50 single-income women with three children earn a living wage.
  4. Compared to peer cities, Louisville has relatively high homeownership for women in single-income households with no children. However, for single-income women with children, we are second to last. Additionally, homeownership for women from a one-income household with children has been steadily decreasing since 2016.
  5. Homeownership for single-income women is much lower for women of color.

Other Notes

  • This data comes from the U.S. Census Bureau American Community Survey, or ACS for short. The ACS is the nation’s largest annual household survey. Because the data comes from a survey, small changes from year to year might reflect noise in the data due to the random sampling of households from one year to the next. The data becomes even noisier when we look at small groups for whom there were fewer responses (e.g. Black women with children). Small changes from year-to-year should be interpreted with caution.
  • Some graphs include a rolling mean that averages multiple years of data together to reduce noise. This is noted on those graphs.
  • GLP strives to use inclusive language and analyze data for traditionally underrepresented groups whenever possible. However, current data has its limitations. The terminology we use to describe race, sex, gender, and other identities mirrors the way questions were asked in the U.S. Census Bureau’s American Community Survey. Additionally, the survey does not provide us with enough information to create data on many populations in Louisville. When we break data down by race, we include data for white non-Hispanic residents, Black non-Hispanic residents, and Hispanic residents. For the original questionnaire text, see the Appendix section of this report.

Households and Housing

We’ll look at how homeownership and affordability shake out among Louisville residents. We’ll represent the 315,000 households as 100 dots.

Louisville population is 51% female and 49% male.