An analysis of Stafford loan repayment burdens

Chapman, Bruce; Lounkaew, Kiatanantha

doi:10.1016/j.econedurev.2014.11.003

Cited by 20 publications

(13 citation statements)

References 17 publications

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“…However, when a customer manage to have good record of current assets, customers may be expected to have better capabilities to pay their loans. The results of this study are consistent with other existing studies in the literature (Behr & Sonnekalb, 2012;Hill & Sarangi, 2012;Chapman & Liu, 2013;Baland et al, 2013;Vu et al, 2015;Chapman & Lounkaew, 2015).…”

Section: The Results and Discussionsupporting

confidence: 93%

Credit reporting, relationship banking, and loan repayment

Kebria¹,

Aalikhani²

2015

10.5267/j.msl

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This paper presents an empirical investigation to determine factors influencing on loan repayment in one of Iranian banks named Sepah Bank over the period 2012-2013. The study selects a sample of 290 bank's customers who received loans and, using logistic regression technique, tries to find whether or not qualitative as well as quantitative characteristics of loan receivers influence on repayment of loans. The results indicate that history of outstanding debt as well as customers' past experiences with banks had meaningful relationships with having bad credit and non-payment of loans. In our survey, having a bad credit in the past had positive relationship with non-payment of loans but long-term customers had negative relationship with non-payment of loans. In addition, working capital turnover ratio, cash ratio, total liabilities, current assets and loan value had significant impact on non-repayment of the loan facilities.Growing Science Ltd. All rights reserved. 5

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Section: The Results and Discussionsupporting

confidence: 93%

Credit reporting, relationship banking, and loan repayment

Kebria¹,

Aalikhani²

2015

10.5267/j.msl

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“…Third, we are unsure of the extent to which social origin conditions the returns to graduate credentials by credential type. Due to repayment burdens, educational debt may reduce returns to investments for advanced degrees, even if labor market outcomes for advanced degree-holders are consistent across demographic groups (Chapman and Lounkaew 2015; College Board 2017a; Dynarski and Scott-Clayton 2013). The amount and proportion of debt that will overburden graduates depend on multiple factors, including age, family responsibilities, other concurrent debts, and cost of living (Baum and Schwartz 2006).…”

Section: Graduate Student Debt and Inequalitymentioning

confidence: 99%

Inequality and Opportunity in a Perfect Storm of Graduate Student Debt

Pyne

Grodsky

2019

Sociol Educ

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Recent efforts to understand aggregate student loan debt have shifted the focus away from undergraduate borrowing and toward dramatically rising debt among graduate and professional students. We suggest educational debt plays a key role in social stratification by either deterring bachelor’s degree holders from disadvantaged and underrepresented backgrounds from pursuing lucrative careers through advanced degree programs or imposing a high cost for entry. We speculate that the ongoing personal financing of advanced degrees, changes to funding in higher education, and increasing returns to and demand for postbaccalaureate degrees have created a perfect storm for those seeking degrees beyond college. We find that aggregate increases in borrowing among advanced degree students between 1996 and 2016 can be explained in part by increasing enrollment rates, particularly among master’s degree students, and large, secular increases in graduate and professional students’ undergraduate and graduate borrowing. In contrast to undergraduate debt alone, the burden of educational debt among graduate borrowers appears to have fallen on students from lower socioeconomic backgrounds and historically underserved students of color more so than their more advantaged counterparts and on women more so than men. However, we also find that median advanced degree wage premia over those of bachelor’s degree holders are substantial for many who graduate with advanced degrees but are particularly high for African American and low socioeconomic status graduates, complicating simple conclusions about the stratification of debt at the postgraduate level.

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“…To estimate the earnings equation we use unconditional quantile regression. As pointed out in Chapman and Lounkaew (2014) Women display on average lower earnings than men, and the gap is increasing along the income distribution, from slightly more than 5,000 euros a year when comparing men and women in the 25 th percentile, to more than 10,000 euros less per year when we compare men and women in the 75 th percentile ( Table 2). This result adds to previous Spanish evidence.…”

Section: Data and Estimated Modelmentioning

confidence: 60%

Estimating Taxpayer Subsidies and Individual Repayment Burdens of a Student Loan Program in Spain

Callado-Muñoz¹,

Rey²,

Utrero-González³

2017

HPE-RPE

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We study the program Préstamos Renta Universidad that provided loans to Master's students in Spain between 2007 and 2010. We estimate predicted income functions and calculate individual repayment burdens and government cost using unconditional quantile regression analysis. We exploit the changing conditions of the successive calls to illustrate three important lessons for the design of student loan schemes: fixed monthly repayments exert an excessive burden to graduates at the lower end of the income distribution; general interest rate subsidies are costly to the taxpayer and unfairly distributed; while the deferment of payments due in case of hardship protects low earners, general grace periods are costly and inequitable.

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An analysis of Stafford loan repayment burdens

Cited by 20 publications

References 17 publications

Credit reporting, relationship banking, and loan repayment

Credit reporting, relationship banking, and loan repayment

Inequality and Opportunity in a Perfect Storm of Graduate Student Debt

Estimating Taxpayer Subsidies and Individual Repayment Burdens of a Student Loan Program in Spain

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