Period life expectancy by age and sex for the UK. Each national life table is based on population estimates, births and deaths for a period of three consecutive years. Tables are published annually.

This table contains mortality indicators by sex for Canada and all provinces except Prince Edward Island. These indicators are derived from three-year complete life tables. Mortality indicators derived from single-year life tables are also available (table 13-10-0837). For Prince Edward Island, Yukon, the Northwest Territories and Nunavut, mortality indicators derived from three-year abridged life tables are available (table 13-10-0140).

Period life expectancy by age and sex. Each life table is based on population estimates, births and deaths for a single year.

This table contains mortality indicators for Canada and provinces for the period 1980/1982 to 2013/2015. Complete mortality tables are available for men, women and both sexes combined.

Mortality experience data from 2010 through 2014 on private pension plans in the United States

ABSTRACT This study aimed to set upper and lower bounds for the expected present value of whole life annuities and whole life insurance policies from incomplete mortality data, generalizing previous results on life expectancy. Since its inception, in the 17th century, actuarial science has been devoted to the study of annuities and insurance plans. Thus, setting intervals that provide an initial idea about the cost of these products using incomplete mortality data represents a theoretical contribution to the area and this may have major applications in markets lacking historical records or those having little reliability of mortality data, as well as in new markets still poorly explored. For both the continuous and discrete cases, upper and lower bounds were constructed for the expected present value of whole life annuities and whole life insurance policies, contracted by a person currently aged x, based on information about the expected present value of these respective financial products subscribed to by a person of age x + n and the probability that an individual of age x survives to at least age x + n. Through the bounds of a continuous annuity, in an environment where the instantaneous interest rate is equal to zero, the results shown also set bounds for the complete life expectancy, which implies that the contribution of this research generalizes previous results in the literature. It was also found that, for both annuities and insurance plans, the length of constructed intervals increases as the data gap size increases and it decreases as the survival curve becomes more rectangular. Illustratively, bounds for life expectancy at 40 and 60 years of age, for the 10 municipalities showing the highest life expectancy at birth in Brazil in 2010, were constructed by using data available in the Atlas of Human Development in Brazil.

Mortality experience data from 2009 through 2013 on public pension plans in the United States

Mortality experience data from 2009 through 2013 on individual payout annuities

Period life expectancy by age and sex for Scotland. Each national life table is based on population estimates, births and deaths for a period of three consecutive years. Tables are published annually.

This table contains 2394 series, with data for years 1991 - 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 items: Canada ...), Population group (19 items: Entire cohort; Income adequacy quintile 1 (lowest);Income adequacy quintile 2;Income adequacy quintile 3 ...), Age (14 items: At 25 years; At 30 years; At 40 years; At 35 years ...), Sex (3 items: Both sexes; Females; Males ...), Characteristics (3 items: Life expectancy; High 95% confidence interval; life expectancy; Low 95% confidence interval; life expectancy ...).

Mortality and morbidity experience data from 2010 through 2013 on group insurance policies

ABSTRACT Life tables have been elaborated throughout much of human history. However, the first life table to use actuarial concepts was only constructed in 1815 by Milne for the city of Carlisle in England. Since then, numerous tables have been elaborated for different regions and countries, due to their crucial importance for analyzing various types of problems covering a vast range of possibilities, from actuarial studies to forecasting and evaluating demands in order to define public policies. The most common problem nowadays in an actuarial calculation is choosing a suitable table for a given population. Brazil has few specific tables for the pensions market and has been using imported tables that refer to other countries, with different cultures and different mortality experiences. Using data from the Integrated Human Resource Administration System, this table constructs life tables for Executive branch federal civil servants for the period from 1993 to 2014, disaggregated for sex, age, and educational level (high school and university). The international literature has recognized differences in mortality due to sex, socioeconomic differences, and occupation. The creation of the Complementary Pension Foundation for Federal Public Servants in 2013 requires specific mortality tables for this population to support actuarial studies, healthcare, and personnel policies. A mathematical equation is fitted to the data. This equation can be broken down into infant mortality (not present in the data), mortality from external causes, and mortality from senescence. Recent results acknowledging an upper limit for old age mortality are incorporated into the adjusted probabilities of death. Assuming a binomial distribution for deaths, the deviance was used as a figure of merit to evaluate the goodness of fit of the observed data both to a set of tables used by the insurance/pensions market and to the adjusted tables.

ABSTRACT This paper aims to estimate mortality and analyze its differentials by sex, age, and groups of beneficiaries of the Brazilian National Institute of Social Security (INSS) in 2015 and make comparisons with official estimates for the general population, assessing the distribution of deaths by age and of survival after 65 years old. The results reinforce the need for more studies on mortality differentials between beneficiary groups and for continuous investment to improve the quality of the data. Population aging, among other aspects, puts pressure on the Brazilian social security system, and there is real concern about its sustainability. Life tables by population subgroups are fundamental as a tool for analyzing the financial and actuarial equilibrium of the system. The results contribute to the debate on the mortality differentials between groups of beneficiaries of the general pension and social security system in Brazil. The death and population data derive from the administrative records of the INSS. We used Gompertz and Van de Maen models and Topals regression to estimate the mortality rates above the age of 65, according to the following beneficiary groups: retirees through age of the General Social Security Regime (Regime Geral de Previdência Social - RGPS) - disaggregated by urban and rural clienteles; retirees through period of contribution; and beneficiaries of welfare support for low income seniors. Among the main results, it was possible to minimize the crossover in the mortality rates of older ages, when the mortality of the less advantaged population becomes lower than the mortality of populations with better social indicators. Cross-checking the results with the official mortality estimates, it was observed that life expectancies for the 65 and 75 year old age groups of the target population of this study are higher than in the general population.

Mortality experience data from 2009 through 2013 on structured settlements

Mortality experience data from 2009 through 2015 on fully underwritten individual life insurance policies

Actuarial life-table estimates of HIV transmission hazard rates per breast feeding month in the control group (n = 365)

Post Level Term mortality and lapse experience data from 2000 through 2012 on fully underwritten individual life insurance policies