Abstract

This article highlights the problem of omitted variable bias in research on the causal effect of financial aid on college‑going. I first describe the problem of self‑selection and the resulting bias from omitted variables. I then assess and explore the strengths and weaknesses of random assignment, multivariate regression, proxy variables, fixed effects, difference‑in‑differences, regression discontinuity, and instrumental variables techniques in addressing the problem. I focus on the intuition, assumptions, and applications of each method in the context of the same research question, providing practical guidance for researchers interested in implementing these approaches.

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Additional Information

ISSN
1090-7009
Print ISSN
0162-5748
Pages
pp. 329-354
Launched on MUSE
2008-03-10
Open Access
No
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