Evaluating Financial Aid Effects on College Student Dropout Risks: A Causal Inference Approach

Rong Chen

The causal impact of financial aid on college student dropout cannot be completely understood without carefully considering the non-random nature of aid assignments and the longitudinal process of student dropout. Few existing studies have accounted for these issues, which could produce biases that undermine the precision of the estimates of financial aid effects. Building on the advances in causal inference research in social sciences, this study employs the combined use of propensity score techniques and multilevel event history methods to improve the validity of evaluating financial aid policies in higher education. Using two national datasets containing longitudinal information on students entering four-year institutions in 2004, this project examines patterns of college student dropout gaps, identifies via causal inference methods both the short-term and long-run effects of financial aid on student dropout. In addition, it also investigates how these effects may vary across students with different socioeconomic status and racial/ethnic backgrounds. The proposed study is highly significant for at least two reasons. First, it explores the longitudinal nexus between financial aid and college student dropout to shed light on how larger social structures, such as government, may play a role in equalizing educational opportunities. Second, it aims to tackle the causal inference about the effectiveness of educational interventions, an issue that has recently drawn increasing attention from academia and policymakers.

About Rong Chen

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