5,859 research outputs found

    Mortality modelling and forecasting: a review of methods

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    Linked lives: the utility of an agent-based approach to modelling partnership and household formation in the context of social care

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    The UK’s population is aging, which presents a challenge as older people are the primary users of health and social care services. We present an agent-based model of the basic demographic processes that impinge on the supply of, and demand for, social care: namely mortality, fertility, health-status transitions, internal migration, and the formation and dissolution of partnerships and households. Agent-based modeling is used to capture the idea of “linked lives” and thus to represent hypotheses that are impossible to express in alternative formalisms. Simulation runs suggest that the per-taxpayer cost of state-funded social care could double over the next forty years. A key benefit of the approach is that we can treat the average cost of state-funded care as an outcome variable, and examine the projected effect of different sets of assumptions about the relevant social processes

    China's uncertain demographic present and future

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    This paper applies methods of probabilistic population forecasting to assess the range of uncertainty of China’s future population trends. Unlike previous applications of probabilistic population projections that consider stochastic future fertility, mortality and migration, this paper will also account for the significant uncertainty of China’s current fertility level (with published figures ranging from 1.2 to 2.3) and the related uncertainties about the sex ratio at birth (with estimates from 1.06 to above 1.2) and the size of the youngest cohorts in the 2000 census. The model applied in this paper will be based on assumed uncertainty ranges for current conditions, in addition to the probabilistic treatment of future trends. Given the sheer size of China’s population, these significant uncertainties about current conditions are of high importance not only for the future population of China but also for considerations on a global scale.

    Longevity Basis Risk A methodology for assessing basis risk

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    This technical report details the methodology developed on behalf of the LBRWG to assess longevity basis risk. A user-guide which provides a high level summary of this report has also been produced. Together these documents form the key outputs of the first phase of a longevity basis risk project commissioned and funded by the IFoA and the LLMA, and undertaken on our behalf by Cass Business School and Hymans Robertson LLP

    A Fuzzy-Random Extension of the Lee-Carter Mortality Prediction Model

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    The Lee-Carter model is a useful dynamic stochastic model to represent the evolution of central mortality rates throughout time. This model only considers the uncertainty about the coefficient related to the mortality trend over time but not to the age-dependent coefficients. This paper proposes a fuzzy-random extension of the Lee-Carter model that allows quantifying the uncertainty of both kinds of parameters. As it is commonplace in actuarial literature, the variability of the time-dependent index is modeled as an ARIMA time series. Likewise, the uncertainty of the age-dependent coefficients is also quantified, but by using triangular fuzzy numbers. The consideration of this last hypothesis requires developing and solving a fuzzy regression model. Once the fuzzy-random extension has been introduced, it is also shown how to obtain some variables linked with central mortality rates such as death probabilities or life expectancies by using fuzzy numbers arithmetic. It is simultaneously shown the applicability of our developments with data of Spanish male population in the period 1970-2012. Finally, we make a comparative assessment of our method with alternative Lee-Carter model estimates on 16 Western Europe populations
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