Calendar Effect and In-Sample Forecasting Applied to Mesothelioma Mortality Data

In this paper, we apply and further illustrate a recently developed extended continuous chain ladder model to forecast mesothelioma deaths. Making such a forecast has always been a challenge for insurance companies as exposure is difficult or impossible to measure, and the latency of the disease usually lasts several decades. While we compare three approaches to this problem, we show that the extended continuous chain ladder model is a promising benchmark candidate for asbestosis mortality forecasting due to its flexible and simple forecasting strategy. Furthermore, we demonstrate how the model can be used to provide an update for the forecast of the number of deaths due to mesothelioma in Great Britain using in recent Health and Safety Executive (HSE) data.Spanish Ministry of Economy and Competitiveness, through grant numbers MTM2016-76969P and PID2020-116587GBI00European Regional Development Fund (ERDF)

Decomposition of changes to disease and disability life expectancy in england

Research findings report ofETHNIC RESIDENTIAL SEGREGATION OVER TIME AND AGE COHORTS IN ENGLAND AND WALES project. A project in the ESRC Understanding Population Trends and Processes Programme, maintained by the ReStore repository and archived to NCRM Eprints 2022

The Role of Heterogeneous Parameters for the Detection of Selection in Insurance Contracts

This study re-examines standard econometric approaches for detecting adverse and advantageous selection in insurance contracts based on variables that are not used for calculating the insurance premium. We formally demonstrate that existing strategies for detecting selection based on such ‘unused characteristics’ can lead to incorrect conclusions if the estimated coefficients of interest are driven by different parts of the population. We show that this issue can empirically be accounted for by allowing for heterogeneous parameters. We compare existing approaches by using simulated data with different selection regimes and test for parameter heterogeneity within the data. We further provide empirical evidence about selection into the market for private health insurance in England. Both our simulations, and the findings using real data, suggest that parameter heterogeneity is a relevant issue that can confound the interpretation of standard ‘unused characteristics’ approaches. Our findings are important for analysing the efficiency of insurance markets. They are of interest to both the insurance industry and policymakers, and should be accounted for when selection based on specific characteristics needs to be detected or the effects of structural changes of insurance policies/markets are to be predicted

Waist-to-Height Ratio Is More Predictive of Years of Life Lost than Body Mass Index

Objective: Our aim was to compare the effect of central obesity (measured by waist-to-height ratio, WHtR) and total obesity (measured by body mass index, BMI) on life expectancy expressed as years of life lost (YLL), using data on British adults. Methods: A Cox proportional hazards model was applied to data from the prospective Health and Lifestyle Survey (HALS) and the cross sectional Health Survey for England (HSE). The number of years of life lost (YLL) at three ages (30, 50, 70 years) was found by comparing the life expectancies of obese lives with those of lives at optimum levels of BMI and WHtR. Results: Mortality risk associated with BMI in the British HALS survey was similar to that found in US studies. However, WHtR was a better predictor of mortality risk. For the first time, YLL have been quantified for different values of WHtR. This has been done for both sexes separately and for three representative ages. Conclusion: This study supports the simple message ‘‘Keep your waist circumference to less than half your height’’. The use of WHtR in public health screening, with appropriate action, could help add years to life

A Sensitivity Analysis of the Premiums for a Permanent Health Insurance (PHI) Model

This paper presents an analysis of the parameters used in a multi-state model for permanent health insurance (PHI). The model is a simplification of that used in the United Kingdom. To avoid using duration dependent probabilities, the model splits the sick state into several sub-states to act as a proxy for duration spent in a particular state. This enables a Markov approach to be adopted. Lapses are incorporated within the model, and the net premium for a particular policy is tested for sensitivity to the various parameters used, including their interaction with the lapse rate. One of our conclusions is that the net premium is insensitive to changes in the lapse rate