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A simple benchmark for mesothelioma projection for Great Britain

Author

Listed:
  • Bent Nielsen

    (Nuffield College, Oxford)

  • María Dolores Martínez-Miranda

    (Department of Statistics and Operations Research, University of Granada, Granada, Spain)

  • Jens Perch Nielsen

    (Cass Business School, London)

Abstract

Background: It is of considerable interest to forecast the future burden of mesothelioma mortality. Data on deaths are available, whereas no measure of asbestos exposure is available. Methods. We compare two Poisson models: a response-only model with an age-cohort specification and a multinomial model with epidemiologically motivated frequencies. Results. The response-only model has 5% higher peak mortality than the dose-response model.The former performs slightly better in out-of-sample comparison. Conclusion. Mortality is predicted to peak at about 2100 deaths around 2017 among males in cohorts until 1966 and below 90 years of age. The response-only model is a simple benchmark that forecasts just as well as more complicated models.

Suggested Citation

  • Bent Nielsen & María Dolores Martínez-Miranda & Jens Perch Nielsen, 2016. "A simple benchmark for mesothelioma projection for Great Britain," Economics Papers 2016-W03, Economics Group, Nuffield College, University of Oxford.
    • Handle: RePEc:nuf:econwp:1603
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    File URL: https://www.nuffield.ox.ac.uk/economics/papers/2016/MartinezMirandaNielsenNielsen_AsbestosBenchmark.pdf
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    References listed on IDEAS

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    1. D. Kuang & B. Nielsen & J. P. Nielsen, 2008. "Forecasting with the age-period-cohort model and the extended chain-ladder model," Biometrika, Biometrika Trust, vol. 95(4), pages 987-991.
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    Cited by:

    1. Weidong Ji & Na Xie & Daihai He & Weiming Wang & Hui Li & Kai Wang, 2019. "Age-Period-Cohort Analysis on the Time Trend of Hepatitis B Incidence in Four Prefectures of Southern Xinjiang, China from 2005 to 2017," IJERPH, MDPI, vol. 16(20), pages 1-17, October.
    2. Mammen, Enno & Martínez-Miranda, María Dolores & Nielsen, Jens Perch & Vogt, Michael, 2021. "Calendar effect and in-sample forecasting," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 31-52.
    3. Bischofberger, Stephan M. & Hiabu, Munir & Mammen, Enno & Nielsen, Jens Perch, 2019. "A comparison of in-sample forecasting methods," Computational Statistics & Data Analysis, Elsevier, vol. 137(C), pages 133-154.

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