Adam Wenqiang Shao

Product Pricing and Solvency Capital Requirements for Long-Term Care Insurance

This paper presents a comprehensive assessment of premiums, reserves and solvency capital requirements (SCRs) for long-term care (LTC) insurance policies using Activities of Daily Living and US data. We compare stand-alone policies, whole life insurance policies with LTC benefit riders (LTC insurance combined with whole life insurance), life care annuities (LTC insurance combined with annuities) and shared LTC insurance in terms of net premium cost and SCRs. Net premiums and best-estimate reserves for base LTC insurance policies are determined using Thiele’s differential equation. Product features such as the elimination period and the maximum benefit period are compared using a simulation-based model. We show how a maximum benefit period can reduce costs and risks for LTC insurance products. SCRs for longevity risk and disability risk are based on the Solvency II standard formula. We quantify the extent to which whole life insurance policies with LTC benefit riders and life care annuities provide lower S...

Disaggregated House Price Indices

This paper estimates and compares methods of constructing disaggregated house price indices from existing house price models using individual sales data for Sydney. Nine alternative house price models are selected to cover the most frequently used methods in the literature: the mean model, median models (standard and stratified), hedonic models (restricted and unrestricted hedonic), repeat-sales models (age-adjusted and Case-Shiller weighted), and a hybrid of the hedonic and repeat-sales model. The unrestricted hedonic model and the hybrid model have an advantage over the other seven models in that they do not require stratification of the data for estimating disaggregated indices. Both models employ the whole sample to estimate implicit prices of house characteristics that are used to construct disaggregated house price indices. These two models eliminate variability arising from small sample sizes and provide more efficient estimates of house price heterogeneity. In addition, house characteristics that are important drivers of the variability of individual house prices are identified in the two models. Disaggregated indices constructed from these two models provide more accurate comparisons with an aggregate house price index. We quantify the extent to which disaggregated house prices indices have significantly more variability than, and differing trends from, the aggregate index.

The Impact of Systematic Trend and Uncertainty on Mortality and Disability in a Multi-State Latent Factor Model for Transition Rates

Multiple state functional disability models do not generally include systematic trend and uncertainty. We develop and estimate a multi-state latent factor intensity model with transition and recovery rates depending on a stochastic frailty factor to capture trend and uncertainty. We estimate the model parameters using U.S. Health and Retirement Study (HRS) data between 1998 and 2012 with Monte Carlo maximum likelihood estimation method. The model shows significant reductions in disability and mortality rates during this period and allows us to quantify uncertainty in transition rates arising from the stochastic frailty factor. Recovery rates are very sensitive to the stochastic frailty. There is an increase in expected future lifetimes as well as an increase in future healthy life expectancy. The proportion of lifetime spent in disability on average remains stable with no strong support in the data for either morbidity compression or expansion. The model has widespread application in costing of government funded aged care and pricing and risk management of LTC insurance products.

Modeling Multi-State Health Transitions in China: A Generalized Linear Model with Time Trends

Rapid population aging in China has urged the need to understand health transitions of older Chinese to assist the development of social security programs and financial products aimed at funding long-term care. In this paper, we develop a new flexible approach to modeling health transitions in a multi-state Markov model that allows for age effects, time trends and age-time interactions. The model is implemented in the generalized linear modeling framework. We apply the model to evaluate health transitions of Chinese elderly using individual-level panel data from the Chinese Longitudinal Healthy Longevity Survey for the period 1998–2012. Our results confirm that time trends and age-time interactions are important factors explaining health transitions in addition to the more commonly used age effects. We document that differences in disability and mortality rates continue to persist between urban and rural older Chinese. We also compute life expectancies and healthy life expectancies based on the proposed model as inputs for the development of aged care and financial services for older Chinese.