FULL READ FROM HOUSING MATTERS – CLICK HERE TO READ.
Affordability and housing quality are the foundations of housing stability, but low-income households often have to sacrifice one for the other. Research suggests living in poor-quality housing can lead to health hazards, safety concerns, financial degradation, and residential instability. So, who is most likely to live in poor-quality housing, and how much would it cost to address the repair needs of the most vulnerable households? This study from the Federal Reserve Bank of Philadelphia and PolicyMap helps answer these questions.
Using housing-quality data from the American Housing Survey (AHS) and repair-cost estimates provided by Gordian, a firm that specializes in construction costs, researchers analyzed the prevalence of and the cost to repair housing-quality issues among homeowners and renters across the United States. To conduct the analysis, researchers used the AHS data to create a list of housing-problem scenarios and linked those scenarios with their appropriate, cost-effective repairs. Researchers aggregated these housing-quality scenarios and their respective repair costs at the unit, metropolitan statistical area, regional, and national level. Though the methodology helps estimate the scale and severity of household-level home repairs, the data present a couple limitations. First, the AHS data do not account for unobservable factors like indoor air quality, lead exposure, and water contamination that would require significant additional repairs. Second, the cost index likely understates the needs in multifamily buildings because the AHS only collects data specific to individual units and not to buildings as a whole.
To further understand the nuance of the country’s home repair needs, researchers conducted a cluster analysis to create unique household typologies for homeowners and renters based on their household income, building age, the number of years a household lived in a property (for owners only), and the structure type (for renters only). These typologies provide a useful frame to target programmatic and policy decisions for specific household and building types.
Key findings
Overall:
