Multidimensional smoothing by adaptive local kernel-weighted log-likelihood: Application to long-term care insurance

Tomas, Julien; Planchet, Frédéric

doi:10.1016/j.insmatheco.2013.03.009

Cited by 13 publications

(7 citation statements)

References 44 publications

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“…These methods have been used in a mortality context by Delwarde et al (2004), Debón et al (2006) and Tomas (2011) to graduate life tables with attained age. More recently, Tomas and Planchet (2013) have covered smoothing in two dimension and introduced adaptive parameters choice with an application to long-term care insurance. Local likelihood techniques have the ability to model relatively well the mortality patterns even in the presence of complex structures and avoid to rely on experts opinion.…”

Section: Local Likelihood Smoothing Methodsmentioning

confidence: 99%

Prospective mortality tables: Taking heterogeneity into account

Tomas

Planchet

2015

Insurance: Mathematics and Economics

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Section: Local Likelihood Smoothing Methodsmentioning

confidence: 99%

Prospective mortality tables: Taking heterogeneity into account

Tomas

Planchet

2015

Insurance: Mathematics and Economics

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“…Tomas & Planchet (2013) have shown that the construction of such table is a difficult exercise for the following reasons:…”

Section: Table Riskmentioning

confidence: 99%

“…For the numerical application, we use the fitted surface of the disabled lives mortality obtained in Tomas & Planchet (2013). The fitted disabled lives probability q u (x + υ), displayed in Figure 1(c), have been obtained by fitting the adaptive local bivariate likelihood model with local bandwidth factors methodology.…”

Section: Numerical Applicationmentioning

confidence: 99%

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Uncertainty on survival probabilities and solvency capital requirement: application to long-term care insurance

Planchet

Tomas

2014

Scandinavian Actuarial Journal

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In this paper, we focus on uncertainty issues on disabled lives survival probabilities of LTC insurance policyholders and its consequences on solvency capital requirement. Among the risks affecting long-term care portfolios, special attention is addressed to the table risk, i.e. the risk of unanticipated aggregate mortality, arising from the uncertainty in modeling LTC claimants survival law. The table risk can be thought as the risk of systematic deviations referring not only to a parameter risk but, as well, to any other sources leading to a misinterpretation of the life table resulting for example from an evolution of medical techniques or a change in rules of acceptance. In fine, the idea is to introduce the risk of systematic deviations arising from the uncertainty on the disabled lives death probabilities directly. We analyze the consequences of an error of appreciation on the disabled lives survival probabilities in terms of level of reserves and describe a framework in an Own Risk and Solvency Assessment perspective to measure the gap between the risk profile from the standard formula to the risk analysis specific to the organism.

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“…In this context, the most welldocumented pathologies regarding LTC dependence are dementia and Alzheimer's (Arrighi et al, 2010;Koroukian et al, 2016;Farias et al, 2017), heart failure, and high blood pressure (Kuo et al, 2005;Sinclair et al, 2008;Lesman-Leegte et al, 2009), and to some extent cancer (Goodwin, 1991;Avis & Deimling, 2008;Chavan et al, 2017). Therefore, individuals' pathology profiles affect the severity of the dependence and lead to diverse health outcomes and mortality patterns (Tomas & Planchet, 2013;Albarrán et al, 2019;Jennings et al, 2020). Finally, from a patient perspective, becoming care dependent means a change in lifestyle that is difficult to accept.…”

Section: Introductionmentioning

confidence: 99%

Modelling the burden of long-term care for institutionalised elderly based on care duration and intensity

Bladt

Fuino²,

Shemendyuk³

et al. 2022

Ann. actuar. sci.

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The financing of long-term care and the planning of care capacity are of increasing interest due to demographic changes and the ageing population in many countries. Since many care-intensive conditions begin to manifest at higher ages, a better understanding and assessment of the expected costs, required infrastructure, and number of qualified personnel are essential. To evaluate the overall burden of institutional care, we derive a model based on the duration of stay in dependence and the intensity of help provided to elderly individuals. This article aims to model both aspects using novel longitudinal data from nursing homes in the canton of Geneva in Switzerland. Our data contain comprehensive health and care information, including medical diagnoses, levels of dependence, and physical and psychological impairments on 21,758 individuals. We build an accelerated failure time model to study the influence of selected factors on the duration of care and a beta regression model to describe the intensity of care. We show that apart from age and gender, the duration of stay before death is mainly affected by the underlying diseases and the number of different diagnoses. Simultaneously, care intensity is driven by the individual level of dependence and specific limitations. Using both evaluations, we approximate the overall care severity for individual profiles. Our study sheds light on the relevant medical, physical, and psychological health indicators that need to be accounted for, not only by care providers but also by policy-makers and insurers.

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Multidimensional smoothing by adaptive local kernel-weighted log-likelihood: Application to long-term care insurance

Cited by 13 publications

References 44 publications

Prospective mortality tables: Taking heterogeneity into account

Prospective mortality tables: Taking heterogeneity into account

Uncertainty on survival probabilities and solvency capital requirement: application to long-term care insurance

Modelling the burden of long-term care for institutionalised elderly based on care duration and intensity

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