th This book is published to commemorate the 50 Anniversary of the S.S. Huebner Foundation for Insurance Education. Administered at the Wharton School of the University of Pennsylvania, the Huebner Foundation was established in 1941 to strengthen insurance education at the collegiate level by increasing the number of professors specializing in insurance and enriching the literature in the field. The financial support of leading life insurance companies has enabled the Foundation to provide post-graduate education for prospective insurance teachers and scholars. Through its fellowship program, the Foundation supports students in the Ph.D. program in Risk and Insurance at the Wharton School. The success of the Foundation is measured by the accomplishments of its alumni. Former Huebner Fellows play leading roles in every major area of insurance education. Fellows teach insurance to tens of thousands of undergraduate and MBA students each year and have written hundreds of books and thousands of articles on insurance. Fellows hold leadership positions at the American College, the Life Office Management Association, and the Certified Employee Benefit Specialist Program. The Foundation was created in honor of Dr. Solomon S. Huebner, a pioneer in insurance education. Dr. Huebner taught the first organized course on the economics of insurance ever offered at the collegiate level in 1904. An internationally recognized author and teacher, Dr. Huebner had a profound impact on both insurance education and the insurance industry. He served on the faculty of the Wharton School for more than nearly fifty years.

Two different applications have been considered, automobile claims from Massachusetts and health expenses from the Netherlands. We have fit 11 different distributions to these data. The distributions are conveniently nested within a single four parameter distribution, the generalized beta of the second type. This relationship facilitates analysis and comparisons. In both cases the GB2 provided the best fit and the Burr 3 is the best three parameter model. In the case of automobile claims, the flexibility of the GB2 provides a statistically siE;nificant improvement in fit over all other models. In the case of Dutch health expenses the improvement of the GB2 relative to several alternatives was not statistically significant. * The author appreciates the research assistance of Mark Bean, Young Yong Kim and Steve White. The data used were provided by Richard Derrig of The Massachusetts Automobile Rating and Accident Prevention Bureau and by Bob Van der Laan and The Silver Cross Foundation for the medical insurance claim data. 2~ REFERENCES Arnold, B. C. 1983. Pareto Distributions. Bartonsville: International Cooperative Publishing House. Cummins, J. D. and L. R. Freifelder. 1978. A comparative analysis of alternative maximum probable yearly aggregate loss estimators. Journal of Risk and Insurance 45:27-52. *Cummins, J. D., G. Dionne, and L. Maistre. 1987. Application of the GB2 family of distributions in collective risk theory. University of Pennsylvania: Mimeographed manuscript. Hogg, R. V. and S. A. Klugman. 1983. On the estimation of long tailed skewed distributions with actuarial applications.

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