Post-purchase Federal Financial Aid: How (in)Effective is the IRS’s Student Loan Interest Deduction (SLID) in Reaching Lower-Income Taxpayers and Students?

Abstract

Federal financial aid policies for higher education may be classified based on their “for-purchase” and “post-purchase” natures. The former include grants, loans, and workstudy and intend to help students finance or afford college attendance, persistence, and graduation. Post-purchase policies are designed to minimize financial burdens associated with having invested in college attendance and are granted as tax incentives/expenditures. One of these expenditures is the IRS’s Student Loan Interest Deduction (SLID)—which offers up to $2500 as an adjustment for taxable income based on having paid interest on student loans and has an annual cost of $12.81 billion—about 45.7% of the Pell grant cost. Despite this high cost, SLID has remained virtually unstudied. Accordingly, the study’s purpose is to assess how (in)effective SLID may be in reaching lower-income taxpayers. To address this purpose, we relied on an innovative analytic framework “multilevel modelling with spatial interaction effects” that allowed controlling for contextual and systemic observed and unobserved factors that may both affect college participation and may be related with SLID disbursements over and above income prospects. Data sources included the IRS, ACS, FBI, IPEDS, and the NPSAS:2015–2016. Findings revealed that SLID is regressive at the top, wealthier taxpayers and students attending more expensive colleges realize higher tax benefits than lower income taxpayers and students. Indeed, 75% of community college students were found to not be eligible to receive SLID—data and replication code ( https://cutt.ly/COyfdKC ) are provided. Is this the best use of this multibillion tax incentive? Is SLID designed to exclude the poorest, neediest students? A policy similar to Education Credits, focused on outstanding debt rather than on interest, that targets below-poverty line students with up to $5000 in debt, would represent a true commitment, and better use of public funds, to close socioeconomic gaps, by helping those more prone to default.

Becoming HOPEless in the 2-Year Sector

“…That is, despite the apparent affordability of this sector, in addition to tuition and fees charges, college cost of attendance also includes cost of living, books and supplies, and forgone earnings associated with not holding full-time employment due to college attendance (Baum et al, 2018), making tuition and fees only a subset of these costs. Accordingly, college cost of attendance may help explain that the average annual debt amount borrowed by community college students nationwide is around $5,000 (González Canché, 2022), which, as discussed below, doubles the amount of academic-performance-based aid received by students participating in the HOPE Grant award discussed in our study. 1 Another reason to justify the relevance of an analysis of financial aid based on academic performance in the public 2-year sector is that a significant proportion of these students may also qualify for need-based aid, which constitutes a subset of the financial aid literature that has received less attention (see Richburg-Hayes et al, 2009, e.g.).…”

“…It remains the entry point for 39% of first-time students and enrolls at least 41% of undergraduate attendees in the United States (American Association of Community Colleges [AACC], 2022). Despite the fact that the inflation-adjusted published tuition and fee prices at public 2-year institutions is 1.65 times as high in 2021–2022 as it was in 1991–1992 (Ma & Matea, 2021, p. 12), the public 2-year sector still remains the most affordable option in postsecondary education (González Canché, 2014, 2018, 2022). The tuition and fees of public 2-year colleges have historically been less than half of those charged by public 4-year institutions and only one-tenth of the tuition and fees charged by private 4-year colleges, on average (AACC, 2010, 2022).…”

“…Note, however, that the primary type of need-based aid evaluated in the 2-year sector is student loans. This research emphasis is based on the notion that 2-year students, who are typically more financially constrained than their 4-year peers (Doyle, 2009; González Canché, 2014, 2018, 2020, 2022; Hu et al, 2018; Long & Kurlaender, 2009; Stephan et al, 2009), could be greatly harmed if they receive loans but do not complete their degrees, thus not having well-paying jobs that would allow them to cover the debt burden (Field, 2010; Gladieux & Perna, 2005). Accordingly, authors have assessed the relationship between loan debt and attainment among community college students (DesJardins et al, 2002; Dowd & Coury, 2006; Gladieux & Perna, 2005) with results rendering inconclusive or negative effects of loans on completion.…”

The Geography of Mathematical (Dis)Advantage: An Application of Multilevel Simultaneous Autoregressive (MSAR) Models to Public Data in Education Research

“…The literature on school and neighborhood effects clearly states that school context influences students' academic performance (Carlson & Cowen, 2015;Goldstein, 1997;González Canché, 2019, 2022, 2023bKonstantopoulos & Borman, 2011) and that living in high-poverty neighborhoods is negatively associated with mathematical achievement (Anderson et al, 2014;Pearman, 2019), both of which pose significant barriers for children's upward social mobility (Chetty et al, 2016(Chetty et al, , 2020. Carlson and Cowen further noted that "analyses of neighborhood contributions to academic achievement that do not account for a student's schooling context may result in biased estimates of neighborhood contributions" (2015, p. 49).…”

“…Carlson and Cowen further noted that "analyses of neighborhood contributions to academic achievement that do not account for a student's schooling context may result in biased estimates of neighborhood contributions" (2015, p. 49). Heeding their cautionary note, and as indicated in the conceptual map shown in Figure 1, this study accounts for school-context indicators (e.g., percentages of English language learners, students with disabilities, and students receiving free and reducedprice lunch 3 ), schools' neighborhood socioeconomic and demographic characteristics (e.g., poverty and crime, academic attainment levels) employed in previous studies (see Carlson & Cowen, 2015;González Canché, 2022, 2023bJargowsky & El Komi, 2011;Pearman, 2019), and measurement of mathematics proficiency levels conditional on testtakers' economic disadvantage standing.…”