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Social Dimensions of Student Debt: A Data Mining Analysis

Dirk Witteveen and Paul Attewell. Journal of Student Financial Aid. Vol 49, No 1. 2019.

Abstract

Media commentary on undergraduates’ loan debt portrays a crisis in which many students are unable to pay back their loans, having borrowed large sums and lacking sufficient post-college income to repay. Several scholars have questioned the media accounts, noting that indebtedness is highest among students from high income families, while defaults predominate among low debt students. Using a data mining technique known as CART, we analyze national data on the indebtedness of recent baccalaureate graduates, to uncover combinations of social characteristics that are associated with loan pressure: the ratio of indebtedness to post-college earnings. We find that students from lower income families who attend expensive institutions – especially for-profit colleges – accumulate high debt. In contrast to earlier scholarship, after controlling for the net cost of attending a college, we find that lower-income students face much higher loan pressure than students from more affluent families.

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