Description: This predictive modeling paper, “Household Life Insurance Demand – A Multivariate Two-Part Model is one of a collection of essays that examine how existing or new methods or models can be applied to the life insurance industry.

Description: The projection methods used by the Social Security Administration's Office of the Chief Actuary are important. The resulting projections are cited regularly by policy-makers, academics and others interested in the long-term financial solvency of the OASDI system. However, a complete description of this projection methodology that is vital for serious policy discussions is not available to the general public. This summary was constructed in connection with the Social Security Advisory Board's 1999 Technical Panel on Methods and Assumptions. A goal of the Methods and Modeling working group of the Technical Panel was to 'work to ensure that the projection methods used by the Office of the Chief Actuary become more public.' From Actuarial Research Clearing House 2000, Vol. 1.

Description: This paper provides an overview of deductible ratemaking , and the pros and cons of various approaches under different parametric models are compared

Description: The purpose of this paper is to understand characteristics of a household that drive life insurance demand with more sophisticated analytical techniques. The analysis is based on the Survey of Consumer Finances data, a probability sample of the U.S. population. Household demand of two types of insurance, term life insurance and whole life insurance, is examined jointly. We model both the frequency and the severity of demand for insurance building on the work of Lin and Grace 2007 by using covariates that they developed.

Description: This paper provides an overview of deductible ratemaking , and the pros and cons of various approaches under different parametric models are compared

Description: This study summarizes the results of the the Society of Actuaries' Non-Mortality Decrement Task Force data collection effort of plan turnover data for years 1994-2000. Service, by itself, seems not to be a good predictor of retirement. Service and age are each good predictors for termination it is found. The report is designed to offer actuaries information about turnover as it pertains to defined benefit plans.