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• W2917016598 abstract "Missing data is a problem that may be faced by actuaries when analysing mortality data. In this paper we deal with pension scheme data, where the future lifetime of each member is modelled by means of parametric survival models incorporating covariates, which may be missing for some individuals. Parameters are estimated by likelihood-based techniques. We analyse statistical issues, such as parameter identifiability, and propose an algorithm to handle the estimation task. Finally, we analyse the financial impact of including covariates maximally, compared with excluding parts of the mortality experience where data are missing; in particular we consider annuity factors and mis-estimation risk capital requirements." @default.
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• W2917016598 date "2019-02-27" @default.
• W2917016598 modified "2023-10-14" @default.
• W2917016598 title "Survival analysis of pension scheme mortality when data are missing" @default.
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• W2917016598 doi "https://doi.org/10.1080/03461238.2019.1580610" @default.
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