Description: Abstracts of various papers published in ARCH 1983 Vol. 1

Description: Shows how to use personal information such as medical history, family characteristics, etc. in a logical statistical fashion for the purpose of modifying an existing mortality table to reflect the collected underwriting information.

Description: In this article, the authors introduce a new policy-making model for pension plan funding which openly represents the uncertainty. The word 'policy' is used here to indicate a strategy which is intended to be followed most [but not necessarily all] of the time. In unusual circumstances, the policy will have to be modified at the end of the year to retain qualification. However, the frequency with which this remedial action is needed is controllable by the actuary [unlike the method of using expected values]. The simple substitution of expected values of random quantities produces an unknown frequency of last minute remedial actions at possibly disastrous investment costs to the pension plan. However, with this paper's techniques, once the actuary acknowledges the uncertainty associated with the various aspects of the pension plan, he/she can explicitly trade off the costs associated with remedial actions, tax penalties, etc. with the investment returns in order to meet the pension plan goals. The method that this paper introduces is a new Chance-Constrained Programming approach to selecting annual contribution levels and asset allocation [holding other factors fixed] that the authors believe will better fit the employer's goals while recognizing the many risks and constraints associated with defined benefit plans. From Actuarial Research Clearing House 1993, Vol. 3.