JOURNAL ARTICLE

The racial wealth gap, financial aid, and college access.

  • Published In: Journal of Policy Analysis & Management, 2024, v. 43, n. 2. P. 555 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Levine, Phillip B.; Ritter, Dubravka 3 of 3

Abstract

We examine how the racial wealth gap interacts with financial aid in American higher education to generate a disparate impact on college access and outcomes. Retirement savings and home equity are excluded from the formula used to estimate the amount a family can afford to pay. All else equal, omitting those assets mechanically increases the financial aid available to families that hold them. White families are more likely to own those assets and in larger amounts. We document this issue and explore its relationship with observed differences in college attendance, types of institutions attended, degrees attained, and education debt using data from the Survey of Consumer Finances (SCF), the National Postsecondary Student Aid Study (NPSAS), and the Panel Study of Income Dynamics (PSID). We show that this treatment of assets provides an implicit subsidy worth thousands of dollars annually to students from families with above‐median incomes. White students receive larger subsidies relative to Black students and Hispanic students with similar family incomes, and this gap in subsidies is associated with disadvantages in educational advancement and student loan levels. It may explain 10 percent to 15 percent of white students' advantage in these outcomes relative to Black students and Hispanic students. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Policy Analysis & Management. 2024/03, Vol. 43, Issue 2, p555
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2024
  • ISSN:0276-8739
  • DOI:10.1002/pam.22550
  • Accession Number:176497485
  • Copyright Statement:Copyright of Journal of Policy Analysis & Management is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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