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«Contesting the streets Volume 18, number 1 • 2016 U.S. Department of Housing and Urban Development | Office of Policy Development and Research ...»

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A number of socioeconomic trends could result in much higher or lower rates of homeownership than those predicted purely based on demographic changes. Positive changes in fundamentals such as income, employment, and mobility could contribute to stabilization or even rebound of the homeownership rate. If income increases faster than it has during the past decades, and particularly if income increases faster than rents and home prices for the marginal buyer, that will increase the demand for housing and homeownership. This scenario, together with financial changes that return borrowing constraints to where they were in the 1990-to-2000 period could contribute to an increase in homeownership rates to rates beyond the predicted level of 61 percent under the fast scenario. The change in the homeownership rate among Hispanic households will be particularly impactful because of their projected contribution to household formation (Goodman, Pendall, and Zhu, 2015). The transition from most Hispanic individuals being foreign born to most being native born has the potential to result in substantially higher homeownership rates among Hispanic households than has been observed in the past (Coulson, 1999) and a higher aggregate homeownership rate. To some extent, this change is captured through the transition rates used for these scenarios, because homeownership rates have already increased for Hispanic households in the last decades, but this increase would accelerate with greater income gains.

Other factors might accentuate the decline of homeownership by contributing to a discouraged renter effect and the realization of the California scenario discussed previously. In the United States, household growth has exceeded the construction of new housing units, driving up both rents and home prices. These trends also may herald a long-term shift away from an elastic housing supply for the United States as a whole. We develop the California scenario to incorporate this long-term outcome. Moreover, the areas that have experienced higher population and job growth are also areas that have experienced a higher increase in housing costs (Diamond, 2015; Moretti, 2012). As central cities, in which homeownership is lower and the stock more adapted to renting, experience a renewal (Capperis, Ellen, and Karfunkel, 2015), we should expect faster population growth rates in cities relative to suburban areas, which, in turn, has the potential to raise housing costs and decrease homeownership rates as well. Regional divergence, with metropolitan areas having high housing costs growing faster than elsewhere, could contribute to a further decline in the homeownership rate. Costs of housing may continue to increase relative to incomes in these 154 Point of Contention: Declining Homeownership A Renter or Homeowner Nation?

desirable markets, without necessarily reaching California levels. A scenario in which rents increase somewhat faster than inflation, however, is likely. With an increase in supply inelasticity, the outcome is likely to be somewhere in between the slower long-term rent increase and California cost scenarios, an outcome, which as shown in exhibit 5 under the slow scenario, would yield a homeownership rate of roughly 50 percent.

Conclusion This article performs an exercise in which we identify the potential impact of key drivers of homeownership rates on future homeownership rate outcomes. We take no position on whether these key determinants in fact will come about. Rather we perform an exercise in which we test for their impact.

We demonstrate the result of shifts in three key drivers for homeownership forecasts: demographics (projected from the census), credit conditions (reflected in the fast and slow scenarios), and rents and housing cost increases (based on California). Our base case average scenario forecasts a decrease in homeownership to 57.9 percent by 2050, but alternate simulations show that it is possible for the homeownership rate to decline to around 50 percent by 2050, 20 percentage points less than at its peak in 2004. This projected level of homeownership is not substantially different from the situation experienced by California or a number of high-income European countries today.

To undertake these simulations, we use a methodology based on demographic forecasts, differing credit conditions, and an economic forecast of rising housing costs resulting from supply inelasticity that reflects recent trends. Projected declines in homeownership are about equally due to demographic shifts, continuation of recent credit conditions, and potential rent and house price increases over the long term.

The current and post-WWII normal of two out of three households owning may also be in our future if credit conditions improve, if (as we move to a majority-minority nation) minorities’ economic endowments move toward replicating those of majority households, and if recent rent growth relative to income stabilizes. A drop in the homeownership rate to around 50 percent is most likely to occur if increasing housing costs relative to income discourage household saving for downpayments. Limited income growth, constrained credit, and persistent rent and housing cost increases over the long term may result in a new economics of housing and less attainable homeownership.

Authors Arthur Acolin is a doctoral student at the Price School of Public Policy at the University of Southern California.





Laurie S. Goodman is the Director of the Housing Finance Policy Center at the Urban Institute.

Susan M. Wachter is the Albert Sussman Professor of Real Estate and Finance at The Wharton School and Co-Director of the Penn Institute for Urban Research at the University of Pennsylvania.

–  –  –

References Acolin, Arthur, Raphael W. Bostic, Xudong An, and Susan M. Wachter. 2015a. Credit Market Innovations and Sustainable Homeownership: The Case of Non-Traditional Mortgage Products.

Working paper. https://www.stlouisfed.org/~/media/Files/PDFs/ Community%20Development/ Econ%20Mobility/Sessions/BosticPaper508.pdf.

Acolin, Arthur, Jesse Bricker, Paul Calem, and Susan M. Wachter. 2015b. Borrowing Constraints and Homeownership. Working paper. http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2720313.

Acolin, Arthur, and Susan Wachter. 2015. “Housing Finance in Retrospect.” In 50 Years of HUD:

Creating Pathways to Opportunity. Washington, DC: U.S. Department of Housing and Urban Development: 156–183.

Barakova, Irina, Paul S. Calem, and Susan M. Wachter. 2014. “Borrowing Constraints During the Housing Bubble,” Journal of Housing Economics 24 (C): 4–20.

Baum-Snow, Nathaniel. 2007. “Did Highways Cause Suburbanization?” The Quarterly Journal of Economics 122 (2): 775–805.

Brevoort, Kenneth P., and Cheryl R. Cooper. 2013. “Foreclosure’s Wake: The Credit Experiences of Individuals Following Foreclosure,” Real Estate Economics 41 (4): 747–792.

Bureau of Labor Statistics (BLS). 2015. “Consumer Price Index Detailed Report: Data for September 2015.” http://www.bls.gov/cpi/cpid1509.pdf.

Capperis, Sean, Ingrid Gould Ellen, and Brian Karfunkel. 2015. Renting in America’s Largest Cities.

Working paper. New York: New York University, Furman Center for Real Estate and Urban Policy.

Coulson, N. Edward. 2002. “Regional and State Variation in Homeownership Rates: Or if California’s Home Prices Were as Low as Pennsylvania’s Would Its Ownership Rate Be as High?” The Journal of Real Estate Finance and Economics 24 (3): 261–276.

———. 1999. “Why Are Hispanic and Asian-American Homeownership Rates so Low? Immigration and Other Factors,” Journal of Urban Economics 45 (2): 209–227.

Diamond, Rebecca. 2015. The Determinants and Welfare Implications of US Workers’ Diverging Location Choices by Skill: 1980–2000. Working paper. http://web.stanford.edu/~diamondr/ jmp_final_all_files.pdf.

Fetter, Daniel K. 2013. “How Do Mortgage Subsidies Affect Home Ownership? Evidence From the Mid-Century GI Bills,” American Economic Journal: Economic Policy 5 (2): 111–147.

Gabriel, Stuart A., and Stuart S. Rosenthal. 2015. “The Boom, the Bust and the Future of Homeownership,” Real Estate Economics 43 (2): 334–374.

———. 2005. “Homeownership in the 1980s and 1990s: Aggregate Trends and Racial Gaps,” Journal of Urban Economics 57 (1): 101–127.

–  –  –

Goodman, Allen C. 1988. “An Econometric Model of Housing Price, Permanent Income, Tenure Choice, and Housing Demand,” Journal of Urban Economics 23 (3): 327–353.

Goodman, Laurie, Rolf Pendall, and Jun Zhu. 2015. Headship and Homeownership: What Does the Future Hold? Washington, DC: Urban Institute. http://www.urban.org/sites/default/files/2000257headship-and-homeownership-what-does-the-future-hold.pdf.

Green, Richard K. 1996. “Should the Stagnant Homeownership Rate Be a Source of Concern?” Regional Science and Urban Economics 26 (3): 337–368.

Gyourko, Joseph, Peter Linneman, and Susan Wachter. 1999. “Analyzing the Relationships Among Race, Wealth, and Home Ownership in America,” Journal of Housing Economics 8 (2): 63–89.

Henderson, J. Vernon, and Yannis M. Ioannides. 1983. “A Model of Housing Tenure Choice,” The American Economic Review 73 (1): 98–113.

HOPE NOW. 2015. “Data Report.” http://www.hopenow.com/industry-data.php.

Kolko, Jed. 2013. “Sorry, Mom and Dad: The Kids Aren’t Moving Out Yet.” http://www.trulia.com/ blog/trends/kids-arent-moving-out-yet/.

Linneman, Peter, and Susan Wachter. 1989. “The Impacts of Borrowing Constraints on Homeownership,” Real Estate Economics 17 (4): 389–402.

Moretti, Enrico. 2012. The New Geography of Jobs. New York: Houghton Mifflin Harcourt.

Ruggles, Steven, J. Trent Alexander, Katie Genadek, Ronald Goeken, Matthew B. Schroeder, and Matthew Sobek. 2010. Integrated Public Use Microdata Series: Version 5.0 [Machine-readable database]. Minneapolis: University of Minnesota.

U.S. Census Bureau. 2015a. “Housing Vacancies and Homeownership (CPS/HVS): Historical Tables.” http://www.census.gov/housing/hvs/data/histtabs.html.

———. 2015b. “Historical Census of Housing Tables.” http://www.census.gov/hhes/www/housing/ census/historic/owner.html.

———. 2015c. “2014 National Population Projections.” http://www.census.gov/population/ projections/data/national/2014.html.

———. 2015d. “Projections of the Size and Composition of the U.S. Population: 2014 to 2060.” https://www.census.gov/content/dam/Census/library/publications/2015/demo/p25-1143.pdf.

Wachter, Susan. 1990. “The Limits of the Housing Finance System,” Journal of Housing Research 1 (1): 163–174.

Wachter, Susan M., and Isaac F. Megbolugbe. 1992. “Impacts of Housing and Mortgage Market

Discrimination: Racial and Ethnic Disparities in Homeownership,” Housing Policy Debate 3 (2):

332–370.

–  –  –

The U.S. homeownership rate fell from 69.2 percent in the second quarter of 2004 to 63.4 percent in the second quarter of 2015, reversing the rise from 63.8 percent in the second quarter of 1994 (U.S. Department of Commerce, 2015). The question for this article is whether the rate will plunge another 20 percentage points, or by nearly one-third, by 2050. The largest previous recorded U.S.

decline was a bit less than one-tenth during the Great Depression (from 1930 to 1940).

Cross-sectionally, the homeownership rate varies substantially among developed countries (2013 data), ranging from 83.5 percent in Norway to 77.7 percent in Spain, 64.6 percent in the United Kingdom, and 53.3 percent in Germany. Similar substantial variation among U.S. states (2015 data) ranges from 74.9 percent in Michigan to 51.2 percent in New York. Thus, a lower rate is not infeasible, but a 20-point fall is implausible.

During the period from 2015 to 2050, the main drivers of the U.S. homeownership rate will include changes in the age distribution of the population, age-specific cohorts’ ownership rates, and the tenure decisions of future new households. Changes in the supply of mortgage funds, public policies related to homeownership, rents, and household formation are also likely to have an effect.

I argue that a 20-point decline would require a combination of plunging housing rents, surging user costs of ownership, and adverse demographic changes. None of these changes appears likely.

Some of these factors can be forecast with substantial accuracy. The U.S. population is aging and will continue to do so. Assuming lifetimes are not substantially extended, the Census Bureau projects the U.S. population will grow from 321 to 398 million in 2050. Compared with now, the cohort of adults who are younger than age 64 will fall 8.2 percentage points, while that for seniors will rise by that amount, including a 3.4-percentage-point rise in the 85-and-older population.

Homeownership rates rise with age. These two facts yield a predicted increase in U.S. homeownership of about 2 percentage points, assuming the 85-and-older cohort retains a high ownership rate. If not, then the changing age distribution will raise the ownership rate by about 1 percentage point.

Age-specific homeownership rates are listed for three time periods in exhibit 1. Data columns one and two are the peak rate and year, columns three and four are the rates in the fourth quarter of 2012, and columns five and six are the rates in the second quarter of 2015. A boom in homeownership corresponded to the boom in house prices. After the peak, age-adjusted rates fell rapidly through 2012 and rates continued to decline through 2015.

–  –  –

The total reductions by age group are 10.2, 12.8, and 12.1 percentage points for the cohorts ages 25 through 29, 30 through 34, and 35 through 44, respectively, followed by 7.5 and 7.0 percent for the middle-aged cohort and by 3.3 percentage points for the senior cohort. These large decreases in homeownership of households age 44 and younger have recently reduced the U.S. rate, and they will reduce the future rate if the cohort rates remain below the typical age-homeownership profile. I estimate the result will be a further reduction in the U.S. ownership rate by 4.1 percentage points. The total effect of these two demographic factors will yield a reduction in the aggregate ownership rate of about 2 to 3 percentage points.



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