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A relational technique for estimating the age-specific mortality pattern from grouped data

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  • Anastasia Kostaki

Abstract

This paper presents a new technique of expanding an abridged life table. This technique is a non-parametric one, which relates the probabilities of dying of the abridged table to those of a standard complete table. In order to evaluate the accuracy of the new technique we use it, as well as two other techniques, for expanding empirical abridged data sets. According to the results of our calculations the new method proves very efficient in producing complete life tables from grouped data, in many cases producing more accurate results than the other two methods in spite of its simplicity.

Suggested Citation

  • Anastasia Kostaki, 2000. "A relational technique for estimating the age-specific mortality pattern from grouped data," Mathematical Population Studies, Taylor & Francis Journals, vol. 9(1), pages 83-95.
    • Handle: RePEc:taf:mpopst:v:9:y:2000:i:1:p:83-95
    DOI: 10.1080/08898480009525496
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    Cited by:

    1. P. Baili & A. Micheli & A. Montanari & R. Capocaccia, 2005. "Comparison of Four Methods for Estimating Complete Life Tables from Abridged Life Tables Using Mortality Data Supplied to EUROCARE-3," Mathematical Population Studies, Taylor & Francis Journals, vol. 12(4), pages 183-198.
    2. Anastasia Kostaki & Vagelis Panousis, 2001. "Expanding an abridged life table," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 5(1), pages 1-22.
    3. Bošnjak Nikolina & Prorok Vesna, 2019. "Life tables estimation for pension system actuarial projection model with insufficient data: case of Republic of Srpska," Croatian Review of Economic, Business and Social Statistics, Sciendo, vol. 5(1), pages 21-32, May.

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