Whither human survival and longevity or the shape of things to come

With the continuing increases in life expectancy, populations are ageing rapidly. Governments are concerned for the future of pensions and health care for which population forecasts are an important component for planning purposes. In this paper we focus on human survival rather than mortality rates which are the more usual starting point when estimating future populations. Using a simple model we link basic measures of life expectancy to the shape of the human survival function and consider its various forms. We then use the simple model as the basis for investigating actual survival in England and Wales from 1841 onwards and investigate the concept of a ‘maximum age’. We show how the model can be used in a predictive sense and demonstrate in two tests that show our model would have given more accurate results than comparable government forecasts using the same base information. We then go on to show that, based on trends in life expectancy, official population forecasts could undershoot the population at age 50+ by 0.6m, with consequent financial implications for pensions, health and social care

On a semiparametric survival model with flexible covariate effect.

A semiparametric hazard model with parametrized time but general covariate dependency is formulated and analyzed inside the framework of counting process theory. A profile likelihood principle is introduced for estimation of the parameters: the resulting estimator is n1/2-consistent, asymptotically normal and achieves the semiparametric efficiency bound. An estimation procedure for the nonparametric part is also given and its asymptotic properties are derived. We provide an application to mortality data.

On the distribution of life annuities with stochastic interest rates.

In the traditional approach to life contingencies only decrements are assumed to be stochastic. In this contribution we consider the distribution of a life annuity (and a portfolio of life annuities) when also the stochastic nature of interest rates is taken into account. Although the literature concerning this topic is already quite rich, the authors usually restrict themselves to the computation of the first two or three moments. However, if one wants to determine e.g. capital requirements using more sofisticated risk measures like Value-at-Risk or Tail Value-at-Risk, more detailed knowledge about underlying distributions is required. For this purpose, we propose to use the theory of comonotonic risks developed in Dhaene et al. (2002a and 2002b), which has to be slightly adjusted to the case of scalar products. This methodology allows to obtain reliable approximations of the underlying distribution functions, in particular very accurate estimates of upper quantiles and stop-loss premiums. Several numerical illustrations confirm the very high accuracy of the methodology.Comonotonicity; Life annuity; Stochastic interest rates; Stop-loss premium;

Multi-locus homozygosity promotes actuarial senescence in a wild mammal.

This is the final version. Available from Wiley via the DOI in this record. DATA AVAILABILITY STATEMENT: Data available from the Dryad Digital Repository https://doi. org/10.5061/dryad.bk3j9kdg6 (Hudson, 2023)Genome-wide homozygosity, caused for example by inbreeding, is expected to have deleterious effects on survival and/or reproduction. Evolutionary theory predicts that any fitness costs are likely to be detected in late life because natural selection will filter out negative impacts on younger individuals with greater reproductive value. Here we infer associations between multi-locus homozygosity (MLH), sex, disease and age-dependent mortality risks using Bayesian analysis of the life histories of wild European badgers Meles meles in a population naturally infected with Mycobacterium bovis (the causative agent of bovine tuberculosis [bTB]). We find important effects of MLH on all parameters of the Gompertz-Makeham mortality hazard function, but particularly in later life. Our findings confirm the predicted association between genomic homozygosity and actuarial senescence. Increased homozygosity is particularly associated with an earlier onset, and greater rates of actuarial senescence, regardless of sex. The association between homozygosity and actuarial senescence is further amplified among badgers putatively infected with bTB. These results recommend further investigation into the ecological and behavioural processes that result in genome-wide homozygosity, and focused work on whether homozygosity is harmful or beneficial during early life-stages.Natural Environment Research Council (NERC)Natural Environment Research Council (NERC)Animal and Plant Health AgencyExpanding Excellence in EnglandUniversity of Exete

On simulation-based approaches to risk measurement in mortality with specific reference to Poisson Lee-Carter modelling

This paper provides a comparative study of simulation strategies for assessing risk in mortality rate predictions and associated estimates of life expectancy and annuity values in both period and cohort frameworks

Organizational Mortality of Small Firms: The Effects of Entrepreneurial Age and Human Capital

This paper addresses the issue of internal determination of organizational outcomes. It is argued that in small and simply structured organizations a considerable proportion of the variance in organizational activities and outcomes is associated with individuals. In particular, the paper uses human capital theory to derive hypotheses about individual determinants of organizational mortality. These hypotheses are tested with event-history data of firm registrations and de-registrations in a West German region. The hypotheses are corroborated by the data, but the effects may nonetheless be due to processes linking individual characteristics with organizational performance other than those suggested by the human capital approach

Forecasting drug overdose mortality by age in the United States at the national and county levels

The drug overdose crisis in the United States continues to intensify. Fatalities have increased five-fold since 1999 reaching a record high of 108,000 deaths in 2021. The epidemic has unfolded through distinct waves of different drug types, uniquely impacting various age, gender, race and ethnic groups in specific geographical areas. One major challenge in designing effective interventions is the forecasting of age-specific overdose patterns at the local level so that prevention and preparedness can be effectively delivered. We develop a forecasting method that assimilates observational data obtained from the CDC WONDER database with an age-structured model of addiction and overdose mortality. We apply our method nationwide and to three select areas: Los Angeles County, Cook County and the five boroughs of New York City, providing forecasts of drug-overdose mortality and estimates of relevant epidemiological quantities, such as mortality and age-specific addiction rates.Comment: 18 pages, 7 figure