Indexing Alumni Giving in the United States

By:
Dr. Eduardas Valaitis
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In the United States, most universities, colleges, and other degree granting institutions of higher learning are chartered as not for profit organizations. Thus, instead of maximizing profits, they seek to maximize prestige. To do so, institutions use the excess cash to offer deep discounts on tuition costs to draw higher quality students and pay higher salaries to instructors to attract the best. The excess cash available to each institution is heavily dependant on donative flows and alumni giving has historically been the biggest contributor to these flows. Hence, institutions would benefit greatly if they understood the dynamics of alumni giving and had access to tools that allow comparison of alumni giving rates across institutions. In the current study, proprietary time series data on more than 2,000 institutions of higher learning are used to construct two annual national alumni giving indices from 1968 to 2005 that can be used as tools for benchmarking alumni giving in any institution. The first index tracks the overall amount of money given to American colleges and universities by their alumni and it is highly correlated with the stock market returns. The second index measures the average giving per alumni in the United States. This index is useful when determining whether a given institution is beating the national average. In particular, per alumni giving is found to be highly correlated with the institutional prestige as measured by the U.S. News and World Report national quality ranking of the institution.


Keywords: Indexing, Alumni Giving, Institutional Prestige, Time Series Analysis
Stream: Economics and Management
Presentation Type: Paper Presentation in English
Paper: A paper has not yet been submitted.


Dr. Eduardas Valaitis

Assistant Professor, Department of Mathematics and Statistics, American University
Washington, DC, USA

Dr. Valaitis is an Assistant Professor of Statistics at American University. He holds a Ph.D. in Mathematical Statistics from Yale University. His research is in the area of economic and financial time series analysis, genetics, and classification. He is also a statistical consultant for various business organizations.

Ref: I07P0894