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


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.

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  1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 14.

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


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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.

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Correspondence to Peter M. Rich.

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Faber, J.W., Rich, P.M. Financially Overextended: College Attendance as a Contributor to Foreclosures During the Great Recession. Demography 55, 1727–1748 (2018).

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  • Higher education
  • College spending
  • Foreclosure
  • Great Recession
  • Parental investments