Measuring Housing Insecurity in the American Housing Survey
Shawn Bucholtz, Director of PD&R's Housing and Demographic Analysis Division
The American Housing Survey (AHS) is considered to be the nation’s most comprehensive housing survey, covering numerous topics including housing cost and affordability, housing quality, and neighborhood assets. The AHS is an important source of evidence informing a range of policy initiatives from supporting sustainable homeownership to preventing homelessness. The survey collects detailed data on housing cost burdens and severe housing quality deficiencies that form the basis of the “Worst Case Needs” housing reports that HUD submits to Congress every 2 years.
Because the AHS is unique in the level of detail it collects on the characteristics, conditions, and costs of housing and characteristics of occupants, it serves as an ideal platform for testing new ways of measuring housing insecurity. “Housing insecurity” is an umbrella term that encompasses several dimensions of housing problems people may experience, including affordability, safety, quality, insecurity, and loss of housing. This article highlights recent efforts by the Office of Policy Development and Research to measure housing insecurity through special measures of housing affordability and instability in the 2017 AHS and through a forthcoming pilot study of additional housing insecurity questions that we intend to implement in the 2019 AHS.
Trouble Paying Rent and Utilities
Missing a rent or utility payment or receiving an eviction notice is an important sign that a household’s housing situation is unstable. Recently, HUD and the U.S. Census Bureau released new 2017 AHS data from our special topical module, Delinquent Payments and Notices. This module measures how many owners or renters had difficulty paying their housing and utility costs and whether they believe they are at risk for foreclosure or eviction. An initial review of the data provides some insights into the relationship between housing cost burden and the likelihood that households will miss rent or mortgage payments. Compared with renters living in housing that was affordable to them, moderately cost-burdened renters, defined as those having housing costs totaling between 30 and 50 percent of household income, were 1.6 times more likely to miss rent payments or make partial payments. Nearly 10 percent of severely burdened renters (those spending more than 50 percent of their income on housing costs) could not pay all or part of their rent. Owners were less likely to have this problem. Only 6 percent of severely cost-burdened owners had missed or late mortgage payments. Cost-burdened renters were also more likely to be threatened with an eviction notice than similarly burdened owners were to receive a foreclosure notice.
Measuring Eviction Rates
The 2017 AHS also served as a platform for the first national-level survey on the prevalence of evictions, a key contributor to housing instability. The 2017 AHS Eviction module was developed in collaboration with Matt Desmond of Princeton University and closely tracks the methodology for his Milwaukee Area Renters Study. Collecting these data in the AHS marks an important step toward improving national estimates of the prevalence of eviction and forced moves, many of which are informal evictions not documented in administrative records. Families can face severe consequences from a formal or informal eviction, putting them at greater risk of becoming further entrenched in poverty or slipping into homelessness. We look forward to learning more about the causes of eviction and potential policy interventions for improving the housing stability of at-risk families. HUD and Census expect to release these tables through the AHS table creator in 2019.
Toward a Housing Insecurity Index
HUD is engaged in a longer-term effort to study the feasibility of creating a comprehensive housing insecurity index. This effort is motivated by the U.S. Department of Agriculture’s (USDA’s) research into measuring food security and its development of a food security status index.
Building a housing insecurity index requires data, and the type of data we need can be collected only through a survey. To that end, the first step in this process was to develop a housing insecurity module that includes a series of questions to measure housing insecurity that are transferable among different household surveys. This step was particularly challenging because researchers and policymakers often are not consistent in how they define or measure housing insecurity. This inconsistency is attributable in part to the difficulty of choosing among the variety of available measures of housing problems and identifying which measures are most important and can be easily transferred across surveys or studies.
To develop the housing insecurity module, HUD conducted a thorough review of existing measures of housing insecurity and consulted extensively with experts on the subject. We are grateful for the support we have received from federal and academic collaborators in defining the scope of the housing insecurity questions to include in the module and for the input they have provided on the quality and transferability of the questions.
The next step in the process is to field test the housing insecurity modules, which we intend to do in the 2019 AHS. A portion of 2019 AHS respondents meeting income and tenure criteria will be given the opportunity to participate in a follow-on to the 2019 AHS. By including the housing insecurity module field test as a follow-on to the 2019 AHS, we can minimize our survey costs and take advantage of the data gathered in the regular set of AHS questions.
We hope that the data collected from the housing insecurity module will support the development of a validated index to measure the continuum of housing insecurity that mirrors USDA’s strategy for developing their food security index. Success in this index development effort will enable researchers to systematically measure the housing insecurity of U.S. households, track its prevalence over time and space, examine its causes, and evaluate its impact in numerous policy domains.