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ABSTRACT
Housing cost burden—defined as paying more than 30% of household income for housing—has become a central feature of the American stratification system with dire consequences for the health and well-being of adults and children living in burdened households. To date, existing research has largely focused on the overall prevalence and distribution of housing cost burden—that is, the percentage of households that are cost burdened at a given time and differences in exposure to housing cost burden based on race and income using cross-sectional sources of data. To more fully understand the dynamics of housing cost burden among renter households in the United States including the frequency and duration of spells, we use 50 years of longitudinal data from the Panel Study of Income Dynamics (PSID). The analysis reveals that, in contrast to the episodic nature of poverty, housing cost burden is deep, frequent, and persistent for a growing share of American households.
Disclosure statement
No potential conflict of interest was reported by the authors.
Correction Statement
This article was originally published with errors, which have now been corrected in the online version. Please see Correction (http://dx.doi.org/10.1080/07352166.2024.2314445).
Notes
1. With the exception of 1988 and 1989 waves, when rent payments were not asked about as part of the main household interview. To account for this gap in item coverage, we use linear interpolation based on the 1987 and 1990 values for households that were renting at both of these points in time. Households not observed as renting at both of these time periods must be omitted due to missing information.
2. Though we would prefer to include utilities paid as part of the numerator for our housing cost burden calculation, the PSID only has this measure for the latter half of the panel study. For consistency across time, we accordingly do not use utilities when computing cost burden. In supplementary analyses, we investigated the difference in prevalence associated with including the utilities for the waves where this information is available and found about 10% greater prevalence when utilities can be included. For example, in 2019, our estimate of housing cost burden prevalence is 41% when including utilities and 30% without.
3. If the household goes from renting to owning between waves, this is also interpreted as the end of a spell.
4. To test the importance of zero-income households, we ran all of our analyses excluding this portion of the sample and it did not alter our results in any material respect.
5. To ensure that differences between households in terms of the number of years observed do not bias our results such that interpreting this measure in terms of time is problematic, we ran supplementary analyses available in our Appendix D where we interacted the period of observation with the number of years observed within the period in question. We do not find any differences in the trends according to the number of years observed, so we believe that aggregate exposure can be interpreted as larger values denoting not just a higher proportion of time in a burdened state but also generally more time.
6. It is important to note that our measure of housing cost burden is relatively coarse. It is based on an imputed annual measure that does not capture monthly variation that may occur within a measurement period.
7. Models based on logistic regression produced substantively similar results, so we present the LPMs for ease of interpretation because coefficients can be understood as marginal effects on probability rather than odds ratios.
8. Supplementary analyses based on a White–Black comparison are substantively similar, with Black households slightly more disadvantaged in terms of cost burden measures compared to the non-White estimates.
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Notes on contributors
Gregg Colburn
Gregg Colburn is Associate Professor of Real Estate at the University of Washington’s College of Built Environments. He studies housing policy, housing affordability, and homelessness.
Christian Hess
Christian Hess is a social demographer and Assistant Professor of Sociology at Kennesaw State University. His research focuses on residential segregation, housing inequalities and applying demographic methods to heterogeneous data.
Ryan Allen
Ryan Allen is Professor and Associate Dean for Research at the Humphrey School of Public Affairs at the University of Minnesota. His research focuses on housing affordability, public housing, and immigrant integration.
Kyle Crowder
Kyle Crowder is the Blumstein-Jordan Professor and Chair of the Department of Sociology at the University of Washington. His research focuses on residential segregation, mobility, housing inequality, and the causes and consequences of neighborhood stratification.