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Calendar Effect and In-Sample Forecasting Applied to Mesothelioma Mortality Data

Isakson, A., Krummaker, S. ORCID: 0000-0003-2471-8175, Martinez-Miranda, M. D. & Rickayzen, B. D. ORCID: 0000-0002-0433-0870 (2021). Calendar Effect and In-Sample Forecasting Applied to Mesothelioma Mortality Data. Mathematics, 9(18), 2260. doi: 10.3390/math9182260


In this paper, we apply and further illustrate a recently developed extended continuous chain ladder model to forecast mesothelioma deaths. Making such a forecast has always been a challenge for insurance companies as exposure is difficult or impossible to measure, and the latency of the disease usually lasts several decades. While we compare three approaches to this problem, we show that the extended continuous chain ladder model is a promising benchmark candidate for asbestosis mortality forecasting due to its flexible and simple forecasting strategy. Furthermore, we demonstrate how the model can be used to provide an update for the forecast of the number of deaths due to mesothelioma in Great Britain using in recent Health and Safety Executive (HSE) data.

Publication Type: Article
Additional Information: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Publisher Keywords: continuous chain ladder; age-period-cohort model; backfitting; density estimation; kernel smoothing
Subjects: H Social Sciences > HG Finance
Q Science > QA Mathematics
Departments: Bayes Business School > Actuarial Science & Insurance
Text - Published Version
Available under License Creative Commons: Attribution International Public License 4.0.

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