A comprehensive merit aid allocation model

Paul K. Sugrue

International Journal of Operational Research, 2019, vol. 36, issue 4, 467-476

Abstract: This paper highlights the development of a merit-based financial aid allocation model for a large private university incorporating both yield rate prediction and optimal fund distributions. The objective used in the optimal allocation is the average SAT score of the incoming class. In the application, the allocation decision is bound only by the financial aid budget and the number of accepted applicants in homogeneous SAT score groupings. Required yield rates are estimated utilising logistic regression with SAT score and merit aid award levels as the exogenous variables. The parameter estimates are based upon data from the previous year. Comparing the actual result with the model result shows a 17.3 point increase in the mean SAT score, which is shown as equivalent to a 20% increase in the merit aid budget.

Keywords: financial aid; yield rates; binary logistic regression; merit-based aid; linear programming. (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:ids:ijores:v:36:y:2019:i:4:p:467-476

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