Decision Aids for MBA Program Admissions: Predicting Academic Performance

An approach for aiding and strengthening the MBA admissions process is proposed. The approach derives from the empirical finding that actuarial models outpredict clinical judgments. Multiple-regression models are used to make predictions of the academic performance of an applicant, if admitted to the MBA program. Applicants who are predicted to have a “substantial chance” of an inadequate academic performance are considered further only if a detailed reading of the application indicates exceptional circumstances or characteristics not adequately captured by the models. From the remaining applicants, selection is made by the admissions officer(s) based mainly on predicted “management potential.” The present paper focuses on the first phase of the approach, i.e., the prediction of academic performance. We discuss in detail the development of criterion variables, the specification of predictor variables, and the development, estimation and validation of models to predict academic performance as well as issues associated with the implementation of the proposed approach.