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Age-Specific Mortality and Fertility Rates for Probabilistic Population Projections

  • Hana Ševčíková
  • Nan Li
  • Vladimíra Kantorová
  • Patrick Gerland
  • Adrian E. Raftery
Part of the The Springer Series on Demographic Methods and Population Analysis book series (PSDE, volume 39)

Abstract

The UN released official probabilistic population projections (PPP) for all countries for the first time in July 2014. These were obtained by projecting the period total fertility rate (TFR) and life expectancy at birth (e0) using Bayesian hierarchical models, yielding a large set of future trajectories of TFR and e0 for all countries and future time periods to 2100, sampled from their joint predictive distribution. Each trajectory was then converted to age-specific mortality and fertility rates, and population was projected using the cohort-component method. This yielded a large set of trajectories of future age- and sex-specific population counts and vital rates for all countries. In this chapter we describe the methodology used for deriving the age-specific mortality and fertility rates in the 2014 PPP, we identify limitations of these methods, and we propose several methodological improvements to overcome them. The methods presented in this chapter are implemented in the publicly available bayesPop R package.

Keywords

Bayesian hierarchical model Cohort-component method Life expectancy at birth Markov chain Monte Carlo Total fertility rate United Nations World Population Prospects 

Notes

Acknowledgements

This research was supported by NIH grants R01 HD054511 and R01 HD070936. The views expressed in this article are those of the authors and do not necessarily reflect those of NIH or the United Nations. The authors are grateful to the editor for very helpful comments.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Hana Ševčíková
    • 1
  • Nan Li
    • 2
  • Vladimíra Kantorová
    • 2
  • Patrick Gerland
    • 2
  • Adrian E. Raftery
    • 3
  1. 1.Center for Statistics and the Social SciencesUniversity of WashingtonSeattleUSA
  2. 2.United Nations Population DivisionUnited NationsNew YorkUSA
  3. 3.Departments of Statistics and SociologyUniversity of WashingtonSeattleUSA

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