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Abstract
This paper utilizes principal component regression analysis to examine the relative contributions of 11 ranking criteria used to construct the U.S. News & World Report (USNWR) tier rankings of national universities. The main finding of this study is that the actual contributions of the 11 ranking criteria examined differ substantially from the explicit USNWR weighting scheme because of severe and pervasive multicollinearity among the ranking criteria. USNWR assigns the greatest weight to academic reputation. However, generated first principal component eigenvalues of tier rankings indicate that the most significant ranking criterion is the average SAT scores of enrolled students. This result is significant since admission requirements are policy variables that indirectly affect, for example, admission applications, yields, enrollment, retention, tuition-based revenues, and alumni contributions.
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