Comparing Theoretical Age Patterns of Mortality Beyond the Age of 80

Bolesławski, Lech; Tabeau, Ewa

doi:10.1007/0-306-47562-6_6

Cited by 5 publications

(5 citation statements)

References 9 publications

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“…1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 Badania wykazują, że dobrze dopasowanym modelem dla prawdopodobieństwa zgonu i intensywności zgonów osób starszych są funkcje logistyczne i odpowiednio zmodyfikowane logistyczne, mające co najmniej 3 parametry 3 (por. [Bolesławski, Tabeau 2001;Jackowska 2013;Thatcher, Kannisto, Vaupel 1998]).…”

Section: Istota Analizy Przekrojowej I Kohortowej W Badaniu Umieralnościunclassified

Cross-Sectional and Cohort Analyses in Mortality Studies in Life Insurance Calculations

Jackowska¹

2017

Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu

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Streszczenie: W ubezpieczeniach na życie przyjęcie modelu umieralności ma kluczowe znaczenie dla wyników kalkulacji aktuarialnych. Modele umieralności najczęściej konstruuje się w postaci tablic trwania życia. Ze względu na sposób badania umieralności, wyróżnia się tablice przekrojowe i kohortowe. W Polsce ze względów historycznych nie można jeszcze zbudować pełnych tablic kohortowych. Możliwe jest jednak odtworzenie odpowiednio długich fragmentów historii niektórych generacji. Celem artykułu jest analiza retrospektywna kształtowania się jednorazowych składek netto skalkulowanych na podstawie tablic kohortowych i przekrojowych. Dane demograficzne dla Polski posłużyły do wyznaczenia ex post poziomu jednorazowych składek netto dla nieżyjących już kohort rzeczywistych. Następnie porównano otrzymane wyniki z analogicznymi, wyznaczonymi na podstawie tablic przekrojowych aktualnych w danym roku.Słowa kluczowe: tablice trwania życia, analiza kohortowa, analiza przekrojowa, ubezpieczenia na życie, jednorazowa składka netto. Summary:The assumption of a particular model of mortality made in life insurance has crucial importance to the actuarial calculations. Mortality models are usually constructed as life tables. Considering the methods of mortality analysis, the period and cohort life tables can be distinguished. For historical reasons there is no possibility of constructing full cohort life tables in Poland. Nevertheless, it is possible to reconstruct a long enough history of some generations' lifetime. The aim of this paper is a retrospective analysis of volatility of net single premiums based both on period and cohort life tables. As a source of data analysis, Polish demographic data has been used. Net single premiums have been calculated ex post for the real extinct cohorts. Therefore, the results have been compared to the corresponding outcomes calculated on the basis of period life tables from the current year.

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Section: Istota Analizy Przekrojowej I Kohortowej W Badaniu Umieralnościunclassified

Cross-Sectional and Cohort Analyses in Mortality Studies in Life Insurance Calculations

Jackowska¹

2017

Prace Naukowe Uniwersytetu Ekonomicznego we Wrocławiu

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“…The first relates to large stochastic variations in mortality rates resulting from small numbers at the highest ages (Boleslawski & Tabeau, 2001;Condran, Himes, & Preston, 1991;Horiuchi & Coale, 1990;Wilmoth, 1995). The second relates to the empirically observed decelerating pattern of mortality rates at high ages.…”

Section: Age Profile Of Mortality Ratesmentioning

confidence: 99%

“…Apart from forecasting, they may also be used for life table construction, to smooth data, eliminate errors and aid inferences from incomplete data (Keyfitz, 1982). Over the last two centuries, researchers have experimented with fitting various mathematical functions to the observed age profile of mortality rates (Boleslawski & Tabeau, 2001;Bongaarts, 2005;Keyfitz, 1991;Tabeau, 2001;Thatcher, 1999b;Thatcher et al, 1998). What follows is a description of mathematical functions found to describe mortality at older ages well.…”

Section: Mathematical Functions Fitted To the Age Profile Of Mortalitmentioning

confidence: 99%

“…The logistic and exponential quadratic functions were found to produce the best estimates for age-specific mortality rates at very elderly ages (Boleslawski & Tabeau, 2001;Horiuchi & Coale, 1990;Robine, 2006;Thatcher, 1999b;Thatcher et al, 1998;Wilmoth, 1995;Yi & Vaupel, 2003). Horiuchi and Coale (1990) (Thatcher, 1999b;Thatcher et al, 1998).…”

Section: Which Mathematical Function Best Describes This Pattern?mentioning

confidence: 99%

“…Different threshold ages have been mentioned in the literature e.g. age 75 (Boleslawski & Tabeau, 2001;Horiuchi & Coale, 1990), age 80 (Thatcher, 1999b;Vaupel, 1997b) and 85 (Coale & Kisker, 1990;Robine, 2006;Robine & Vaupel, 2002;Wilmoth, 1995). Horiuchi and Wilmoth (1998: 393) argued that the age at which mortality deceleration starts may be expected to shift to older ages as the level of adult mortality declines.…”

Section: Which Mathematical Function Best Describes This Pattern?mentioning

confidence: 99%

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Population estimates and projections for Australia’s very elderly population at state and national level

Terblanche¹

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As in many developed countries, the very elderly population (ages 85+) is the fastest growing age group in Australia, with far-reaching economic and social consequences. To effectively plan and budget for the income, aged care and health care needs of the very elderly, accurate estimates and projections are required. There are, however, several obstacles relating to the availability and accuracy of very elderly data. Official population estimates at very high ages in Australia have been found to be too high and fluctuate implausibly over time. International and local studies have found large errors in projected very elderly populations, stemming from inaccurate mortality rate forecasts.This thesis aims to create accurate estimates and projections for Australia's very elderly population at a state and national level. Various methods for estimating very elderly populations from death counts were assessed for accuracy at both a national and state level.While the Human Mortality Database uses such methods to create estimates for many countries, their accuracy has never been assessed for Australia. Furthermore, little is known, locally or internationally, about their performance at a sub-national scale. In this study, the accuracy of various nearly-extinct-cohort methods were assessed at the Australian national and state level by retrospectively applying them to extinct cohorts and comparing the results against those obtained from applying the Extinct Cohort method. Suitable methods were applied to create very elderly population estimates and death rates for Australia from 1972-2012 by sex, state and at single ages 85-110+. The growth, changes in the age-sex composition and the demographic drivers of growth of Australia's very elderly population were analysed. Based on these estimates, more reliable death rates were calculated, allowing a detailed study of the changing patterns and trends in Australian adult mortality. Finally, a number of mortality forecasting methods were retrospectively evaluated for their accuracy in projecting adult death rates for Australia over 10 and 20 years ending in 2012. An appropriate method was applied to create projections for the next three decades.It was found that, compared to the official census-based estimates, more plausible and accurate estimates, especially for ages 95+, could be derived from death counts. The Survivor Ratio (SR) method with results constrained to official estimates for ages 85+ produced accurate very elderly population estimates for Australia across the sexes and ages at both a national and state level. Internal migration is sufficiently minor to be ignored. Very accurate state-level estimates could also be derived using a simpler method of apportioning national single-age estimates between the states. Adult death rates in Australia were found to show consistent and regular patterns of decline since the 1970s, with rates of decline decreasing with age. These patterns support the use of simple direct extrapolation methods for forecasting. The Geometric,...

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Aging in Advanced Industrial States

Tuljapurkar¹,

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Gauthier³

2010

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The IUSSP is an international association of researchers, teachers, policy makers and others from diverse disciplines set up to advance the field of demography and promote scientific exchange. It also seeks to foster relations between persons engaged in the study of demography and population trends in all countries of the world and to disseminate knowledge about their determinants and consequences. The members of the IUSSP scientific group responsible for this book were chosen for their scientific expertise. This book was reviewed by a group other than the authors. While the IUSSP endeavors to assure the accuracy and objectivity of its scientific work, the conclusions and interpretations in IUSSP publications are those of the authors. International Studies in Population

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Comparing Theoretical Age Patterns of Mortality Beyond the Age of 80

Cited by 5 publications

References 9 publications

Cross-Sectional and Cohort Analyses in Mortality Studies in Life Insurance Calculations

Cross-Sectional and Cohort Analyses in Mortality Studies in Life Insurance Calculations

Population estimates and projections for Australia’s very elderly population at state and national level

Aging in Advanced Industrial States

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