Human mortality beyond age 110

Gampe, Jutta

doi:10.1007/978-3-642-11520-2_13

Cited by 74 publications

(75 citation statements)

References 2 publications

(2 reference statements)

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“…This is well in line with Gampe (2010) who reports an annual mortality rate of around 0:5 for persons past age 110 using data for a series of OECD countries on mortality rates of supercentenarians.…”

Section: Objective Cohort Datasupporting

confidence: 90%

A life-cycle model with ambiguous survival beliefs

Groneck

Ludwig

Zimper

2016

Journal of Economic Theory

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Optimal tax and transfer systems are key for the design of modern economics. One of the workhorse models used by economists to evaluate the welfare benefits of (reforms to) these systems is the life-cycle model of consumption and savings. The model can, e.g., be used to investigate the reactions of households to savings subsidies or any other kind of reform to old-age insurance, or, more general, any institutional feature of the tax-transfer system.Yet, from a quantitative perspective, it is well known that the standard model produces several "puzzles" in a sense that the standard model cannot match certain facts in the data. It is well established that, relative to an optimal saving rate according to the model, households save too little in the data. Furthermore, the decumulation speed of assets in old-age is much lower in the data than predicted by the standard model. Finally, households behave dynamically inconsistent, in a sense that they generally save less during working life for retirement than they originally planned. Such inconsistencies cannot be accommodated by the standard model.In order to generate correct quantitative predictions it is therefore important to modify the standard model in order to account for these three empirical regularities. This is the aim of the present paper.The specific model element under investigation is the life-expectancy of households which is one of the most important ingredients of the model. Obviously, survival beliefs are of high relevance for savings behavior. The standard model uses objective data on survival beliefs, traced out from population wide survival tables. However, in several datasets that explicitly ask for subjective survival beliefs, substantial biases in survival beliefs relative to such objective data can be observed. E.g., young people strongly underestimate whereas old people (after retirement) strongly overestimate their chances to survive into the future. This paper addresses the question how these biases in survival beliefs may alter model savings behavior, thereby bringing model predictions closer to the data on household savings. On the one hand, underestimation of survival beliefs may lead to lower savings than in the standard model. On the other hand, overestimation in old-age may lead to the fact that households hold on to their assets longer in life than predicted by the standard model.To test whether the observed biases in survival beliefs have quantitatively important implications for the household model, we proceed in two steps. First, we develop a model of survival belief formation. We base our model on a decision theoretic framework which enables us to be explicit about psychological effects such as optimism, pessimism and doubt. A parsimonious representation of survival beliefs enables us to match pessimism with regard to survival for young and optimism for old households, as in the data on subjective survival beliefs. Furthermore, households continuously update their survival beliefs as they age in light of objective information towa...

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Section: Objective Cohort Datasupporting

confidence: 90%

A life-cycle model with ambiguous survival beliefs

Groneck

Ludwig

Zimper

2016

Journal of Economic Theory

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“…The non-ageing interpretation, the empirical observations, and simplicity of the exponential distribution, justify the tentative conclusion concerning the approximate constant death rates in the age interval 110-115, but it does not convince me concerning the death rates in the extrapolation age range of say 120-130 years. Observe also that the approach to handle the selection bias in (Gampe 2010) is similar, and that the exponential distribution conclusion is indicated already in this publication, as properly pointed out by the authors.…”

supporting

confidence: 77%

“…Ideally this requires life spans measured on at least monthly precision level, which might be a problem. I think that this should result in a natural refinement of the analysis in (Gampe 2010).…”

mentioning

confidence: 99%

Discussion of “human life is unlimited-but short” by H Rootzén and D Zholud

Nerman

2018

Extremes

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The statistical paper human life is short-but unlimited is briefly discussed. The possibilities and limitations of statistical inference concerning very long human life spans are considered. The restricted models of tail distributions that arise from assumption of renormalized convergence of max-or conditional peaks over thresholdsdistributions are questioned in the application context of the reviewed paper. The restrictions of natural systems designs on possibilities of extreme life spans, and the potential to adopt modified extreme value models, allowing seasonal variation of death rates, are also pointed out. Keywords Long human life lengths . Supercentenarians . Limit of human life spansIs there a bound for the potential of human life spans? And, if so, can we estimate this bound from empirical data? The first question is not primarily statistical, but rather biological. And, in the era of quick development of organ transplantations, of stem cell therapies and regenerative medicine, and of technical medical spare parts, it is certainly not clear how to generalize life span statistics from the past to predict life spans of the future. Moreover, on a cellular level it is known that self-renewal is a fundamental part of life, although single cell organisms may survive in dormitory phases (e.g. as seeds or in sporulated forms) for very long times.For multi-cellular organisms there are controversial indications that stem cells in some circumstances have the potential for indefinite self-renewal, an example is freshwater polyps of the genus Hydra which are thought to have stem cells with this ability and to age at a negligible rate. However, evolutionary theories of ageing that are widely accepted, would claim that the evolution of life spans is governed by a balance Extremes (2018) 21:411-413 https://doi

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“…A starting point was the non-parametric analysis of Gampe (2010) which concluded that "The analysis confirms that human mortality after age 110 is at at a level corresponding to an annual probability of death of 50%. No sex-specific differences in mortality could be found, and no time trend in supercentenarian mortality between earlier and later cohorts could be detected.…”

Section: Discussionmentioning

confidence: 99%

“…However, the particular truncation setting above does not seem to be considered explicitly in these books. Instead, the formulas are contained in Gampe (2010).…”

Section: F (X I ) F (E − T I )mentioning

confidence: 99%

Human life is unlimited – but short

Rootzén

Zholud

2017

Extremes

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Does the human lifespan have an impenetrable biological upper limit which ultimately will stop further increase in life lengths? This question is important for understanding aging, and for society, and has led to intense controversies. Demographic data for humans has been interpreted as showing existence of a limit, or even as an indication of a decreasing limit, but also as evidence that a limit does not exist. This paper studies what can be inferred from data about human mortality at extreme age. We find that in western countries and Japan and after age 110 the risk of dying is constant and is about 47% per year. Hence data does not support that there is a finite upper limit to the human lifespan. Still, given the present stage of biotechnology, it is unlikely that during the next 25 years anyone will live longer than 128 years in these countries. Data, remarkably, shows no difference in mortality after age 110 between sexes, between ages, or between different lifestyles or genetic backgrounds. These results, and the analysis methods developed in this paper, can help testing biological theories of aging and aid confirmation of success of efforts to find a cure for aging.A discussion of this paper will follow in a later issue of Extremes Electronic supplementary material The online version of this article (https://doi

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Human mortality beyond age 110

Cited by 74 publications

References 2 publications

A life-cycle model with ambiguous survival beliefs

A life-cycle model with ambiguous survival beliefs

Discussion of “human life is unlimited-but short” by H Rootzén and D Zholud

Human life is unlimited – but short

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