The forecasting performance of mortality models

Hansen, Hendrik

doi:10.1007/s10182-011-0186-x

Cited by 2 publications

(2 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, use of MAFE is demonstrated in the modelling comparison study ofShang et al (2011), while RMSFE inHansen (2013) andVan Berkum et al (2016).…”

mentioning

confidence: 99%

Credible Regression Approaches to Forecast Mortality for Populations with Limited Data

Bozikas

Pitselis

2019

Risks

View full text Add to dashboard Cite

In this paper, we propose a credible regression approach with random coefficients to model and forecast the mortality dynamics of a given population with limited data. Age-specific mortality rates are modelled and extrapolation methods are utilized to estimate future mortality rates. The results on Greek mortality data indicate that credibility regression contributed to more accurate forecasts than those produced from the Lee–Carter and Cairns–Blake–Dowd models. An application on pricing insurance-related products is also provided.

show abstract

“…For instance, use of MAFE is demonstrated in the modelling comparison study ofShang et al (2011), while RMSFE inHansen (2013) andVan Berkum et al (2016).…”

mentioning

confidence: 99%

Credible Regression Approaches to Forecast Mortality for Populations with Limited Data

Bozikas

Pitselis

2019

Risks

View full text Add to dashboard Cite

show abstract

“…Neither study considered the accuracy of the methods. Another example is a study by (Hansen, 2013), where the accuracy of the LC, Geometric and Brass methods were compared based on simulated life tables. Booth, Hyndman, Tickle, and de Jong (2006) assessed the accuracy of death rates forecasted by the original LC method and four variants or extensions.…”

Section: Projected Very Elderly Population Numbersmentioning

confidence: 99%

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

Terblanche¹

View full text Add to dashboard Cite

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,...

show abstract

The forecasting performance of mortality models

Cited by 2 publications

References 25 publications

Credible Regression Approaches to Forecast Mortality for Populations with Limited Data

Credible Regression Approaches to Forecast Mortality for Populations with Limited Data

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

Contact Info

Product

Resources

About