A Principal Component Analysis of the "U.S. News & World Report" Tier Rankings of Colleges and Universities.

作者: Thomas J. Webster

DOI: 10.1016/S0272-7757(99)00066-7

关键词: EconometricsStandardized testMathematicsReputationMulticollinearityHigher educationRegression analysisRankingRevenueWeighting

摘要: This paper utilizes principal component regression analysis to examine the relative contributions of 11 ranking criteria used construct U.S. News & World Report(USNWR) tier rankings national universities. The main finding this study is that actual examined differ substantially from explicit USNWR weighting scheme because severe and pervasive multicollinearity among criteria. assigns greatest weight academic reputation. However, generated first eigenvalues indicate most significant criterion average SAT scores enrolled students. result since admission requirements are policy variables indirectly affect, for example, applications, yields, enrollment, retention, tuition-based revenues, alumni contributions. © 2001 Elsevier Science Ltd. All rights reserved. JEL classification:A22; I29

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