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Drivers of Mortality Dynamics: Identifying Age/Period/Cohort Components of Historical U.S. Mortality Improvements

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Listed:
  • Johnny S.-H. Li
  • Rui Zhou
  • Yanxin Liu
  • George Graziani
  • R. Dale Hall
  • Jennifer Haid
  • Andrew Peterson
  • Laurence Pinzur

Abstract

The goal of this article is to obtain an age/period/cohort (A/P/C) decomposition of historical U.S. mortality improvement. Two different routes to achieving this goal are considered. In the first route, the desired components are obtained by fitting an A/P/C model directly to historical mortality improvement rates. In the second route, an A/P/C model is estimated to historical crude death rates and the desired components are then obtained by differencing the estimated model parameters. For each route, various possible A/P/C model structures are tested and evaluated on the basis of their robustness to several factors (e.g., changes in the calibration window) and their ability to explain historical changes in mortality improvement. Based on the evaluation results, an A/P/C decomposition for each gender is recommended. The decomposition will be examined in a follow-up project, in which the linkages between the A/P/C components and certain intrinsic factors will be identified.

Suggested Citation

  • Johnny S.-H. Li & Rui Zhou & Yanxin Liu & George Graziani & R. Dale Hall & Jennifer Haid & Andrew Peterson & Laurence Pinzur, 2020. "Drivers of Mortality Dynamics: Identifying Age/Period/Cohort Components of Historical U.S. Mortality Improvements," North American Actuarial Journal, Taylor & Francis Journals, vol. 24(2), pages 228-250, April.
  • Handle: RePEc:taf:uaajxx:v:24:y:2020:i:2:p:228-250
    DOI: 10.1080/10920277.2020.1716808
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    Cited by:

    1. Feng, Ben Mingbin & Li, Johnny Siu-Hang & Zhou, Kenneth Q., 2022. "Green nested simulation via likelihood ratio: Applications to longevity risk management," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 285-301.

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