The double-gap life expectancy forecasting model

Life expectancy is highly correlated over time among countries and between males and females. These associations can be used to improve forecasts. Here we propose a method for forecasting female life expectancy based on analysis of the gap between female life expectancy in a country compared with the record level of female life expectancy in the world. Second, to forecast male life expectancy, the gap between male life expectancy and female life expectancy in a country is analysed. We present these results for various developed countries. We compare our results with forecasts based on the Lee&ndash;Carter approach and the Cairns&ndash;Blake&ndash;Dowd strategy. We focus on forecasting life expectancy at age 0 and remaining life expectancy at age 65.</p

The linear link: deriving age-specific death rates from life expectancy

The prediction of human longevity levels in the future by direct forecasting of life expectancy offers numerous advantages, compared to methods based on extrapolation of age-specific death rates. However, the reconstruction of accurate life tables starting from a given level of life expectancy at birth, or any other age, is not straightforward. Model life tables have been extensively used for estimating age patterns of mortality in poor-data countries. We propose a new model inspired by indirect estimation techniques applied in demography, which can be used to estimate full life tables at any point in time, based on a given value of life expectancy at birth. Our model relies on the existing high correlations between levels of life expectancy and death rates across ages. The methods presented in this paper are implemented in a publicly available R package

Preparation and characterization of PbTiO 3-epoxy resin compositionally graded thick films

The preparation and properties of compositionally graded PbTiO3 (PT)-epoxy resin (EPR) composite thick films are reported in this study. Various graded specimens were prepared using gravity casting method by embedding PT powders into the EPR matrix. The existence of a graded structure with two distinct phases, a good intermixing, some air pores, and different morphologies, was confirmed by scanning electron microscopy micrographs. The dielectric constants of these composites have values in the range 5-12 at the frequency of 3c104 Hz and about 3-13 at 3c5 7 108Hz. The composites with permittivity gradient act as a natural impedance match system in the frequency range 2-4 GHz, resulting in very low reflections. Therefore, the compositionally graded PT-EPR composite thick films are suitable as adapting impedance materials for microwave applications

Mortality Modeling

Mortality models approximate mortality patterns or dynamics over age and time. An age pattern of mortality can be any mathematical function of mortality, such as rates, probabilities, survivorship, or death distributions. Such functions may be modeled in the form of a life table or a simplified function with some parameters. Mortality models in general fall into three main categories: (i) models designed to help understand regularities in mortality patterns and dynamics, for example where population-level mortality patterns are modeled as an emergent property of dynamics at the individual level, (ii) those that aim to predict mortality patterns, for example for purposes of pension provisions, and (iii) those aimed at mortality measurement for purposes of mortality and health monitoring. In the following, mortality modeling refers to models of mortality measurement at the population level

Alternative Forecasts of Danish Life Expectancy

In the last three decades, considerable progress in mortality forecasting has been achieved, with new and more sophisticated models being introduced. Most of these forecasting models are based on the extrapolation of past trends, often assuming linear (or log-linear) development of mortality indicators, such as death rates or life expectancy. However, this assumption can be problematic in countries where mortality development has not been linear, such as in Denmark. Life expectancy in Denmark experienced stagnation from the 1980s until the mid-1990s. To avoid including the effect of the stagnation, Denmark’s official forecasts are based on data from 1990 only. This chapter is divided into three parts. First, we highlight and discuss some of the key methodological issues for mortality forecasting in Denmark. How many years of data are needed to forecast? Should linear extrapolation be used? Second, we compare the forecast performance of 11 models for Danish females and males and for period and cohort data. Finally, we assess the implications of the various forecasts for Danish society, and, in particular, their implications for future lifespan variability and age at retirement