Description: This is the abstract of a paper that presents a model for examining the effect of various relationships between mortality rates and lapse rates on the mortality experience of a cohort of insured lives. It takes an individual approach rather than the aggregate approach used in traditional methods of analyzing selective lapsation. The model assumes that insured lives are healthy at policy issue, but may later move to an impaired state from which the lapse rate is zero. Associated with each insured is an unobservable 'risk level' random variable, which reflects the heterogeneity of the insured group. Individual mortality and lapse rates are functions of the risk level. A numerical illustration provides some interesting results obtained using this model.

Description: This paper presents some preliminary results of an analysis of data from a regional municipality in Ontario to assess long term care risks. The data includes information on the optimal level of care at one or more points in time for each individual under study modelled using a Markov process.

Description: This paper presents an approach to analyzing continuing care retirement community CCRC data and demonstrates the methodology by using data from a CCRC. From The Old-Age Crisis - Actuarial Opportunities - The 1996 Bowles Symposium, M-RS99-1.

Description: In this paper, the authors show how probabilities and actuarial values may be calculated using a time-homogeneous Markov model. Piecewise constant transition intensities are suggested as a way to extend the approach to the inhomogeneous case. From Actuarial Research Clearing House 1993, VOL. 1.

Description: Panelists at this session of the SOA 1998 Annual Meeting discuss the results of two SOA research projects. One study looks at mortality rates as a function of lapse rates. The other study develops a model for relating mortality and lapse rates.

Description: This is the abstract of the paper entitled 'On Simulating the Total Claims Distribution' by Bruce L. Jones. From ACTUARIAL RESEARCH CLEARING HOUSE, 1994 VOL. 1.

Description: This paper presents an analysis of mortality in a sample of 441adults aged 55 to 85 at baseline, who were observed for eight years. The study was initiated for the purpose of analyzing age-related changes in a variety of physical variables and their impact on functional independence. The modeling approach is discussed and the factors which were most significantly related to mortality.

Description: This is an abstract of a 1998 presentation from the 33rd Annual Actuarial Research Conference that introduces a family of fractional age assumptions and discusses its usefulness in estimating mortality rates and calculating actuarial present values. Members of the family include the familiar uniform distribution of deaths, constant force, and Balducci assumptions.

Description: Many quantities arising in non-life insurance depend on claim severity distributions, which are usually modeled assuming a parametric form. Obtaining good estimates of the quantities, therefore, reduces to having good estimates of the model parameters. However, the notion of 'good estimate' depends on the problem at hand. For example, the maximum likelihood estimators [MLE] are efficient, but they generally lack robustness. Since outliers are common in insurance loss data, it is therefore important to have a method that allows one to balance between efficiency and robustness. This presentation suggests a general estimation method that we call the method of trimmed moments [MTM]. This method is appropriate for various model fitting situations including those for which a close fit in one or both tails of the distribution is not required. The MTM estimators can achieve various degrees of robustness, and they also allow the decision maker to easily see the actions of the estimators on the data, which makes them particularly appealing.