In-sample forecasting applied to reserving and mesothelioma mortality

Enno Mammen, María Dolores Martínez Miranda and Jens Perch Nielsen

Insurance: Mathematics and Economics, 2015, vol. 61, issue C, 76-86

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.

Keywords: Non-parametric; Kernel density estimation; Reserve risk; Multiplicative; Chain ladder (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:61:y:2015:i:c:p:76-86

DOI: 10.1016/j.insmatheco.2014.12.001

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