Skip to main content
SpringerLink
Log in

Financially Overextended: College Attendance as a Contributor to Foreclosures During the Great Recession

  • Published:
Demography

Abstract

Although subprime mortgage lending and unemployment were largely responsible for the wave of foreclosures during the Great Recession, additional sources of financial risk may have exacerbated the crisis. We hypothesize that many parents sending children to college were financially overextended and vulnerable to foreclosure as the economy contracted. With commuting zone panel data from 2006 to 2011, we show that increasing rates of college attendance across the income distribution in one year predict a foreclosure rate increase in subsequent years, net of fixed characteristics and changes in employment, refinance debt, house prices, and 19-year-old population size. We find similar evidence of college-related foreclosure risk using longitudinal household data from the Panel Study of Income Dynamics. Our findings uncover a previously overlooked dimension of the foreclosure crisis, and highlight mortgage insecurity as an inadvertent consequence of parental investment in higher education.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Notes

  1. We draw from data sources sampling housing units, households, and families; for exposition, we use the terms “households” and “families” interchangeably. Additionally, our use of the term “parent” refers to an adult parent or guardian who was financially responsible for a child between the ages of 15 and 19.

  2. CZs differ from metropolitan statistical areas (MSAs) because they include rural counties. The entire area of the United States is covered by 741 CZs.

  3. The analytical sample covers 84.8 % of the total U.S. population, as of 2000. CZs with fewer than 100,000 persons have low annual counts of 19-year-olds, leading to potentially unreliable estimates of annual college attendance by income percentile (Chetty et al. 2014a); CZs with small populations are also prone to higher rates of missing foreclosure data via RealtyTrac. A list of all sample CZs is available from the authors by request.

  4. We highlight households at the median of the income distribution for parsimony. Point estimates are largest at the median but are not significantly different from estimates at the 10th, 25th, 75th, and 90th income percentiles.

  5. The state-level measure of HPI introduces imprecision into our estimates because they do not capture housing market variation between CZs within states. Unfortunately, we are limited by data availability.

  6. CZs with populations smaller than 100,000 suffer from missing data. Findings are substantively identical when we include an unbalanced sample of CZs missing some years of covariate data.

  7. For example, Mian et al. (2015) showed that the foreclosure timeline is significantly longer in states with a judicial requirement as part of the foreclosure process.

  8. An annual count of 19-year-olds in each CZ is provided in the EO data set (Chetty et al. 2014a). We include this measure to account for general financial strain imposed on parents as their children transition to adulthood. Robustness checks that exclude this measure produce larger positive coefficients for college attendance but lead to substantively similar conclusions.

  9. We calculated within-CZ standard deviations of both foreclosure rate and college attendance. When we estimated models excluding CZs in the top 5 % of either measure, coefficients had similar direction, magnitude, and significance as in models with the full sample.

  10. Foreclosure questions about second or third homes do not identify who within the household experienced the foreclosure. The unit could have been a former home of any household member (including one lost to foreclosure), a vacation home, or a property for rent.

  11. Bayesian information criterion fit statistics confirm that the inclusion of a quadratic income percentile term is preferred to just the linear term or, alternatively, to the natural log of family income. Models fit with these alternative income specifications do not change the magnitude or direction of the coefficient presented for college attendance, but do increase standard errors slightly.

  12. We present results weighted by baseline year. The coefficient of interest is slightly stronger and still significant when weighted by the year when the outcome variable was measured (i.e., t + 4).

  13. We also assessed whether the Current Population Survey (CPS) or the Health and Retirement Survey (HRS) could provide appropriate tests. The measurement of foreclosure in the CPS is imprecise, based on whether a person’s most recent move was due to eviction or foreclosure. And although the HRS provides a more precise measure of foreclosure, it is limited to an early birth cohort sample with very few respondents who were parents of college-age children during the Great Recession.

  14. Educational expenses in the PSID are not reported separately for children in K–12 schools versus those attending college.

References

  • Allen, R. T. (2011). Who experiences foreclosures? The characteristics of households experiencing a foreclosure in Minneapolis, Minnesota. Housing Studies, 26, 845–866.

    Article  Google Scholar 

  • Anacker, K. B., & Carr, J. H. (2011). Analysing determinants of foreclosure among high-income African-American and Hispanic borrowers in the Washington, DC metropolitan area. International Journal of Housing Policy, 11, 195–220.

    Article  Google Scholar 

  • Anacker, K. B., Carr, J. H., & Pradhan, A. (2012). Analyzing foreclosures among high-income black/African American and Hispanic/Latino borrowers in Prince George’s County, Maryland. Housing and Society, 39, 1–28.

    Article  Google Scholar 

  • Autor, D. H., Katz, L. F., & Kearney, M. S. (2008). Trends in U.S. wage inequality: Revising the revisionists. Review of Economics and Statistics, 90, 300–323.

    Article  Google Scholar 

  • Barr, A., & Turner, S. E. (2013). Expanding enrollments and contracting state budgets: The effect of the Great Recession on higher education. Annals of the American Academy of Political and Social Science, 650, 168–193.

    Article  Google Scholar 

  • Been, V., Chan, S., Ellen, I. G., & Madar, J. R. (2011). Decoding the foreclosure crisis: Causes, responses, and consequences. Journal of Policy Analysis and Management, 30, 381–400.

    Article  Google Scholar 

  • Betts, J. R., & McFarland, L. L. (1995). Safe port in a storm: The impact of labor market conditions on community college enrollments. Journal of Human Resources, 30, 741–765.

    Article  Google Scholar 

  • Bhutta, N., Dokko, J. K., & Shan, H. (2017). Consumer ruthlessness and mortgage default during the 2007–2009 housing bust. Journal of Finance, 72, 2433–2466.

    Article  Google Scholar 

  • Bocian, D. G., Li, W., Reid, C., & Quercia, R. G. (2011). Lost ground, 2011: Disparities in mortgage lending and foreclosures (Report). Durham, NC: Center for Responsible Lending.

    Google Scholar 

  • Chan, S., Gedal, M., Been, V., & Haughwout, A. (2013). The role of neighborhood characteristics in mortgage default risk: Evidence from New York City. Journal of Housing Economics, 22, 100–118.

    Article  Google Scholar 

  • Charles, K. K., Hurst, E., & Notowidigdo, M. J. (2015). Housing booms and busts, labor market opportunities, and college attendance (NBER Working Paper No. 21587). Cambridge, MA: National Bureau of Economic Research.

  • Chetty, R., Hendren, N., Kline, P., & Saez, E. (2014a). Where is the land of opportunity? The geography of intergenerational mobility in the United States (NBER Working Paper No. 19843). Cambridge, MA: National Bureau of Economic Research.

  • Chetty, R., Hendren, N., Kline, P., Saez, E., & Turner, N. (2014b). Is the United States still a land of opportunity? Recent trends in intergenerational mobility (NBER Working Paper No. 19844). Cambridge, MA: National Bureau of Economic Research.

  • College InSight. (2015). Higher education data for researchers and the public [Data files]. Retrieved from. http://college-insight.org/

  • Conley, D. (2001). Capital for college: Parental assets and postsecondary schooling. Sociology of Education, 74, 59–72.

    Article  Google Scholar 

  • Cooper, M. (2014). Cut adrift: Families in insecure times. Berkeley: University of California Press.

    Google Scholar 

  • Cordell, L., Dynan, K., Lehnert, A., Liang, N., & Mauskopf, E. (2008). The incentives of mortgage servicers: Myths and realities (Finance and Economics Discussion Series No. 46). Washington, DC: Federal Reserve Board.

  • Dunbar, A., Hossler, D, Shapiro, D., Chen, J., Martin, S., Torres, V., . . . Ziskin, M. (2011). National postsecondary enrollment trends: Before, during, and after the Great Recession (Signature Report No. 1). Herndon, VA: National Student Clearinghouse Research Center.

  • Dynarski, S., & Scott-Clayton, J. (2013). Financial aid policy: Lessons from research (NBER Working Paper No. 18710). Cambridge, MA: National Bureau of Economic Research.

  • Faber, J. W. (2013). Racial dynamics of subprime mortgage lending at the peak. Housing Policy Debate, 23, 328–249.

    Article  Google Scholar 

  • Faber, J. W., & Ellen, I. G. (2016). Race and the housing cycle: Differences in home equity trends among long-term homeowners. Housing Policy Debate, 26, 456–473.

    Article  Google Scholar 

  • Fry, R. (2010). Minorities and the recession-era college enrollment boom (Social & Demographic Trends Report). Washington, DC: Pew Research Center.

  • Gerardi, K., Ross, S. L., & Willen, P. (2011). Understanding the foreclosure crisis. Journal of Policy Analysis and Management, 30, 381–400.

    Article  Google Scholar 

  • Goldrick-Rab, S. (2016). Paying the price: College costs, financial aid, and the betrayal of the American Dream. Chicago, IL: University of Chicago Press.

    Book  Google Scholar 

  • Gramlich, E. M. (2007). Subprime mortgages: America’s latest boom and bust. Washington, DC: Urban Institute Press.

    Google Scholar 

  • Hall, M., Crowder, K., & Spring, A. (2015). Variations in housing foreclosures by race and place, 2005–2012. Annals of the American Academy of Political and Social Science, 660, 217–237.

    Article  Google Scholar 

  • Hanlon, B. (2009). Once the American Dream: Inner-ring suburbs of the metropolitan United States. Philadelphia, PA: Temple University Press.

    Google Scholar 

  • Heeringa, S. G., Berglund, P. A., & Khan, A. (2011). Sampling error estimation in design-based analysis of the PSID data (Technical Series Paper #11-05). Ann Arbor: Survey Research Center, Institute for Social Research, University of Michigan.

  • Houle, J. N. (2013). Disparities in debt: Parents’ socioeconomic resources and young adult student loan debt. Sociology of Education, 87, 53–69.

    Article  Google Scholar 

  • Hout, M., Levanon, A., & Cumberworth, E. (2011). Job loss and unemployment during the Great Recession. In D. B. Grusky, B. Western, & C. Wimer (Eds.), The Great Recession (pp. 59–91). New York, NY: Russell Sage Foundation.

    Google Scholar 

  • Hwang, J., Hankinson, M., & Brown, K. S. (2015). Racial and spatial targeting: Segregation and subprime lending within and across metropolitan areas. Social Forces, 93, 1081–1108.

    Article  Google Scholar 

  • Immergluck, D. (2009). Foreclosed: High-risk lending, deregulation, and the undermining of America’s mortgage market. Ithaca, NY: Cornell University Press.

    Book  Google Scholar 

  • Immergluck, D. (2013). Too little, too late, and too timid: The federal response to the foreclosure crisis at the five-year mark. Housing Policy Debate, 23, 199–232.

    Article  Google Scholar 

  • Immergluck, D. (2015). Preventing the next mortgage crisis: The meltdown, the federal response, and the future of housing in America. New York, NY: Rowman & Littlefield.

    Google Scholar 

  • Kane, T. (2004). College-going and inequality. In K. Neckerman (Ed.), Social inequality (pp. 319–353). New York, NY: Russell Sage Foundation.

    Google Scholar 

  • Lanza, A. (2015, December 16). Decide whether to use home equity, parent PLUS loans to pay for college. U.S. News and World Report. Retrieved from https://www.usnews.com/education/blogs/student-loan-ranger/articles/2015-12-16/decide-whether-to-use-home-equity-parent-plus-loans-to-pay-for-college

  • Lee, D. (2013). Household debt and credit: Student debt [PowerPoint slides] . New York: Federal Reserve Bank of New York. Retrieved from https://www.newyorkfed.org/medialibrary/media/newsevents/mediaadvisory/2013/Lee022813.pdf

  • Levine, P. B. (2014). Transparency in college costs (Brookings Economic Studies working paper). Washington, DC: Brookings Institution.

  • Lieber, R. (2016, September 23). How to pay for college with less stress. The New York Times, p. B1.

  • Long, B. T. (2014). The financial crisis and college enrollment: How have students and their families responded? In J. Brown & C. Hoxby (Eds.), How the financial crisis and Great Recession affected higher education (pp. 209–233). Cambridge, MA: National Bureau of Economic Research.

    Google Scholar 

  • Lovenheim, M. F. (2011). The effect of liquid housing wealth on college enrollment. Journal of Labor Economics, 29, 741–771.

    Article  Google Scholar 

  • Lovenheim, M. F., & Reynolds, C. L. (2013). The effect of housing wealth on college choice: Evidence from the housing boom. Journal of Human Resources, 48, 1–35.

    Article  Google Scholar 

  • Lucy, W. H. (2010). Foreclosing the dream: How America’s housing crisis is reshaping our cities and suburbs. Chicago, IL: American Planning Association.

    Google Scholar 

  • Ma, J., Baum, S., Pender, M., & Bell, D. (2015). Trends in college pricing 2015 (Report). New York, NY: College Board.

  • Martin, I. W., & Niedt, C. (2015). Foreclosed America. Stanford, CA: Stanford University Press.

    Google Scholar 

  • Mayer, C., Pence, K., & Sherlund, S. M. (2009). The rise in mortgage defaults. Journal of Economic Perspectives, 23(1), 27–50.

    Article  Google Scholar 

  • Mian, A., Sufi, A., & Trebbi, F. (2015). Foreclosures, house prices, and the real economy. Journal of Finance, 70, 2587–2634.

    Article  Google Scholar 

  • Mortgage Bankers Association. (2010). Delinquencies and foreclosure starts decrease in latest MBA National Delinquency Survey. Washington, DC: Mortgage Bankers Association. Retrieved from http://www.mortgagebankers.org/NewsandMedia/PressCenter/73799.htm

  • Murphy, R. J., Scott-Clayton, J., & Wyness, G. (2017). Lessons from the end of free college in England (Brookings Economic Studies Working Paper). Washington, DC: Brookings Institution.

  • Pfeffer, F. T., Danziger, S., & Schoeni, R. F. (2013). Wealth disparities before and after the Great Recession. Annals of the American Academy of Political and Social Science, 650, 98–123.

    Article  Google Scholar 

  • Pfeffer, F. T., & Killewald, A. (2016). Intergenerational correlations in wealth. In Economic mobility. Research & ideas on strengthening families, communities & the economy (pp. 175–201). St. Louis, MO: Federal Reserve Bank of St. Louis.

  • Rajan, R. G. (2010). Fault lines: How hidden fractures still threaten the world economy. Princeton, NJ: Princeton University Press.

    Google Scholar 

  • RealtyTrac. (2011). Foreclosure overview & foreclosure process. Retrieved from http://www.realtytrac.com/foreclosure/overview.html

  • Rugh, J., Albright, L., & Massey, D. S. (2015). Race, space, and cumulative disadvantage: A case study of the subprime lending collapse. Social Problems, 62, 186–218.

    Article  Google Scholar 

  • Rugh, J., & Massey, D. S. (2010). Racial segregation and the American foreclosure crisis. American Sociological Review, 75, 629–651.

    Article  Google Scholar 

  • Sallie Mae, & Gallup. (2009). How America pays for college: Sallie Mae’s National Study of College Students and Parents (Report). Reston, VA, and Washington, DC: Sallie Mae and Gallup. Retrieved from https://www.salliemae.com/assets/Core/how-America-pays/GCR1979_2009_PAYS_survey_final_091609.pdf

  • Satter, B. (2009). Family properties: Race, real estate, and the exploitation of black urban America. New York, NY: Metropolitan Books.

    Google Scholar 

  • Schloemer, E., Li, W., Ernst, K., & Keest, K. (2006). Losing ground: Foreclosures in the subprime market and their cost to homeowners (Report). Washington, DC: Center for Responsible Lending.

    Google Scholar 

  • Shapiro, T. M. (2004). The hidden cost of being African American: How wealth perpetuates inequality. Oxford, UK: Oxford University Press.

    Google Scholar 

  • Snyder, T. D., de Brey, C., & Dillow, S. A. (2016). Digest of education statistics 2015 (NCES Report 2016-014). Washington, DC: National Center for Education Statistics, Institute of Education Sciences, U.S. Department of Education.

  • Taylor, P., Kochhar, R., Fry, R., Velasco, G., & Motel, S. (2011). Twenty-to-one: Wealth gaps rise to record highs between whites, blacks and Hispanics (Pew Social & Demographic Trends report). Washington, DC: Pew Research Trends. Retrieved from http://www.pewsocialtrends.org/files/2011/07/SDT-Wealth-Report_7-26-11_FINAL.pdf

  • Tolbert, C. M., & Sizer, M. (1996). U.S. commuting zones and labor market areas: A 1990 update (Economic Research Service Staff Paper No. 9614). Washington, DC: U.S. Department of Agriculture.

  • U.S. Department of the Treasury, & U.S. Department of Education. (2012). The economics of higher education (Report). Washington, DC: U.S. Department of the Treasury and U.S. Department of Education. Retrieved from https://www.treasury.gov/connect/blog/Documents/20121212_Economics%20of%20Higher%20Ed_vFINAL.pdf

Download references

Acknowledgments

Both authors contributed equally to the production of this article. Our work was supported by the Russell Sage Foundation (Award 83-14-09). We thank Richard Arum, Dalton Conley, Ingrid Gould Ellen, Matt Hall, Mike Hout, Pat Sharkey, Florencia Torche, Chris Wildeman, and participants at the May 2015 Russell Sage Foundation conference on Intergenerational Mobility in the United States. We also thank the editors and anonymous reviewers for their helpful comments and suggestions.

Author information

Authors and Affiliations

  1. Robert F. Wagner School of Public Service, New York University, 295 Lafayette St., New York, 10012, NY, USA

    Jacob W. Faber

  2. Department of Policy Analysis and Management, Cornell University, 186 Martha van Rensselaer Hall, Ithaca, NY, 14853, USA

    Peter M. Rich

Authors
  1. Jacob W. Faber
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Peter M. Rich
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peter M. Rich.

Electronic supplementary material

ESM 1

(DOCX 121 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Faber, J.W., Rich, P.M. Financially Overextended: College Attendance as a Contributor to Foreclosures During the Great Recession. Demography 55, 1727–1748 (2018). https://doi.org/10.1007/s13524-018-0702-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13524-018-0702-7

Keywords

Search

Navigation