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Managing the Insolvency Risk of Insurance Companies - Proceedings of the Second International Conference on Insurance Solvency (Paperback, Softcover reprint of the original 1st ed. 1991)
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Managing the Insolvency Risk of Insurance Companies - Proceedings of the Second International Conference on Insurance Solvency (Paperback, Softcover reprint of the original 1st ed. 1991)
Series: Huebner International Series on Risk, Insurance and Economic Security, 12
Expected to ship within 10 - 15 working days
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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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