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: 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: 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 methods using data from a large CCRC. It is assumed that residents make transitions among a number of states that represent the levels of care required by residents. There is randomness associated with both the transition times and the states entered at these times. The model is conveniently characterized in terms of transition intensity functions, which represent the instantaneous rates of transition between pairs of states.

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: This paper presents a multi-state stochastic model for analyzing continuing care retirement community CCRC populations. The model considers CCRCs with a number of independent living units and a skilled nursing facility. Residents may transfer temporarily or permanently to this facility. It is assumed that units vacated by deaths, withdrawals or permanent transfers are immediately occupied by new residents. Transfers are modeled using a time-homogeneous Markov process. The paper provides some probabilistic results and some numerical results obtained using this model. Some important generalizations of the model are also briefly discussed.