Description: In this paper the author proposes a proof for new formulas that derive exposure formulas of the valuation-schedule type on the basis of the Balducci assumption. In addition he provides a short cut for the coefficients of the terms involving deaths. Then he derives a general exposure formula of the valuation-schedule type that may be used for all mortality studies with an observation period covering an integral number of consecutive years. From ACTUARIAL RESEARCH CLEARING HOUSE, 1980 VOL. 2.

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: Demography is a very exciting subject. With a simple mathematical model, students can project a country's population forward 25, 59, 75 even 100 years. This paper will focus on six ideas from demography. They all can be useful to an actuary, yet none of them would be considered at any length if the actuary didn’t study demography.

Description: This is a letter from Jan M. Hoem to Arnold F. Shapiro about Exposed-to-risk considerations based on the Balducci assumption and other assumptions in the analysis of mortality.

Description: This paper investigates the use of models of dependent mortality for determining annuity values. We discuss a broad class of parametric models using a bivariate survivorship function called a copula. Using data from a large insurance company to illustrate our methods, we calculate maximum likelihood estimates to calibrate the rnodel.

Description: The purpose of this note is to show how certain formulas of life contingencies can be derived almost painlessly under the uniform distribution of deaths assumption.

Description: Presents a theoretical basis for a computerized methodology for estimating biological age - a measure of time to death.

Description: This article investigates the simplicity of the Balducci hypothesis, and compares the fractional-age death probability given by three widely used assumptions: uniform distribution of deaths, the Balducci hypothesis, and constant force of mortality [1, 2].

Description: In this paper, we study a survival regression model known as Cox's proportional Hazards model. We assume that the data available are already grouped and develop a minimum distance estimation procedure that is also applicable when the data are also left or right censored. Asymptotic properties of the estimators are established and the numerical implementation of the method based on an iterated reweighted least squares algorithm is discussed.

Description: The purpose of this paper is to introduce the use of least squares for estimating parameters of mortality curves and discuss the advantages of this method.