overall academic stature of the incoming class and therefore the institution.
Achievement of this objective is limited by the size of the class to be recruited,
the availability of merit aid funds, and the availability of qualified applicants.
For example, recruiting a class of 1,000 students by offering full tuition
scholarships to all applicants with SAT scores above 1500 is most likely not
feasible. In the first place, there probably would not be a sufficient number of
applicants with SAT scores in that range. In the second place, there would most
likely be insufficient funds to support this strategy, since the financial aid budget
is normally derived from tuition revenue.
This article applies to the aid allocation decision the technique of constrained
optimization. The approach is to formulate the problem as a mathematical
programming problem that can be readily solved on a personal computer.
Although the problem formulation is simple and straightforward, the challenge
is in extracting the data required for the model and in interpreting the results.
This study uses a subset of actual admissions data, which provides a clear
example of how such a model could be successfully implemented at any
university faced with merit aid allocation decisions.