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qlifetable: An R package for constructing quarterly life tables

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  • Jose M Pavía
  • Josep Lledó

Abstract

The big data revolution has greatly expanded the availability of microdata on vital statistics, providing researchers with unprecedented access to large and complex datasets on birth, death, migration, and population, sometimes even including exact dates of demographic events. This has led to the development of a novel methodology for estimating sub-annual life tables that offers new opportunities for the insurance industry, also potentially impacting on the management of pension funds and social security systems. This paper introduces the qlifetable package, an R implementation of this methodology. It begins by detailing how basic summary statistics are computed by the package from detailed individual records, including the length of age years, which should be observed as relative (subjective) to ensure congruency between age and calendar time when measuring exposure times and exact ages of individuals at events. This is a new result that compels the observation of time as relative in the disciplines of actuarial science, risk management and demography. Afterwards, the paper demonstrates the use of the package, which integrates a set of functions for estimating crude quarterly (and annual) death rates, calculating seasonal-ageing indexes (SAIs) and building quarterly life tables for a (general or insured) population by exploiting either microdata of dates of births and events or summary statistics.

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  • Jose M Pavía & Josep Lledó, 2025. "qlifetable: An R package for constructing quarterly life tables," PLOS ONE, Public Library of Science, vol. 20(2), pages 1-20, February.
    • Handle: RePEc:plo:pone00:0315937
    DOI: 10.1371/journal.pone.0315937
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    References listed on IDEAS

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    1. Josep Lledó & Jose M. Pavía & Francisco G. Morillas, 2017. "Assessing implicit hypotheses in life table construction," Scandinavian Actuarial Journal, Taylor & Francis Journals, vol. 2017(6), pages 495-518, July.
    2. Hyndman, Rob J. & Booth, Heather, 2008. "Stochastic population forecasts using functional data models for mortality, fertility and migration," International Journal of Forecasting, Elsevier, vol. 24(3), pages 323-342.
    3. Adrian Raftery & Jennifer Chunn & Patrick Gerland & Hana Ševčíková, 2013. "Bayesian Probabilistic Projections of Life Expectancy for All Countries," Demography, Springer;Population Association of America (PAA), vol. 50(3), pages 777-801, June.
    4. Pavía, Jose M. & Lledó, Josep, 2023. "Shortcuts for the construction of sub-annual life tables," ASTIN Bulletin, Cambridge University Press, vol. 53(2), pages 332-350, May.
    5. Lorenzo Rocco & Elena Fumagalli & Andrew J Mirelman & Marc Suhrcke, 2021. "Mortality, morbidity and economic growth," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-22, May.
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