Analyzing the demographic coherence of selected US, Australian and Chinese biometric data sets used to price long-term care insurance and life care annuities

This paper examines the implicit healthy life expectancy used for actuarial calculations in some selected biometric data sets from the US, Australia and China. We are interested in checking the demographic/epidemiological coherence of these data sets because this health indicator is rarely presented when authors build their biometric data sets, nor when they are used to calculate long-term care insurance (LTCI) and life care annuity (LCAs) premiums, nor when they are employed in research articles to estimate the future demand for LTC services. We follow a methodology based on multistate life table methods that enables us to obtain a life expectancy matrix for individuals on the basis of their initial health state. We also present some additional indicators of longevity, mortality and morbidity, these being the median age at death, the interquartile range, the weighted modal age at death, the mortality ratio and the implicit LTC prevalence rates broken down by health state. We find several weaknesses that highlight the difficulty involved in building the biometric data sets needed to make an actuarially fair valuation of the premiums for LTCI and LCAs. We also verify the existence of the so-called “male–female health-survival paradox”. From the perspective of a potential purchaser of this type of insurance products, disclosing and explaining the summary measures of health and longevity would make it easier for them to understand the need to protect themselves against the cost of possible LTC services and also make the computation of the premiums more transparent.