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• W2022164941 abstract "Abstract This paper shows that recent published mortality projections with unobserved exposure can be understood as structured density estimation. The structured density is only observed on a sub-sample corresponding to historical calendar times. The mortality forecast is obtained by extrapolating the structured density to future calendar times using that the components of the density are identified within sample. The new method is illustrated on the important practical problem of forecasting mesothelioma for the UK population. Full asymptotic theory is provided. The theory is given in such generality that it also introduces mathematical statistical theory for the recent continuous chain ladder model. This allows a modern approach to classical reserving techniques used every day in any non-life insurance company around the globe. Applications to mortality data and non-life insurance data are provided along with relevant small sample simulation studies." @default.
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• W2022164941 date "2015-03-01" @default.
• W2022164941 modified "2023-10-12" @default.
• W2022164941 title "In-sample forecasting applied to reserving and mesothelioma mortality" @default.
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• W2022164941 doi "https://doi.org/10.1016/j.insmatheco.2014.12.001" @default.
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