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Mortality rate forecasting: can recurrent neural networks beat the Lee-Carter model?

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  • G'abor Petneh'azi
  • J'ozsef G'all

Abstract

This article applies a long short-term memory recurrent neural network to mortality rate forecasting. The model can be trained jointly on the mortality rate history of different countries, ages, and sexes. The RNN-based method seems to outperform the popular Lee-Carter model.

Suggested Citation

  • G'abor Petneh'azi & J'ozsef G'all, 2019. "Mortality rate forecasting: can recurrent neural networks beat the Lee-Carter model?," Papers 1909.05501, arXiv.org, revised Oct 2019.
    • Handle: RePEc:arx:papers:1909.05501
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    File URL: http://arxiv.org/pdf/1909.05501
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    References listed on IDEAS

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    1. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
    2. Andrea Nigri & Susanna Levantesi & Mario Marino & Salvatore Scognamiglio & Francesca Perla, 2019. "A Deep Learning Integrated Lee–Carter Model," Risks, MDPI, vol. 7(1), pages 1-16, March.
    3. Hainaut, Donatien, 2018. "A Neural-Network Analyzer For Mortality Forecast," ASTIN Bulletin, Cambridge University Press, vol. 48(2), pages 481-508, May.
    4. Angus S. Deaton & Christina Paxson, 2004. "Mortality, Income, and Income Inequality over Time in Britain and the United States," NBER Chapters, in: Perspectives on the Economics of Aging, pages 247-286, National Bureau of Economic Research, Inc.
    5. Hainaut, Donatien, 2018. "A Neural-Network Analyzer for Mortality Forecast," LIDAM Reprints ISBA 2018027, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    6. Paras Shah & Allon Guez, 2009. "Mortality forecasting using neural networks and an application to cause-specific data for insurance purposes," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(6), pages 535-548.
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