Document Detail


Bayesian probabilistic population projections for all countries.
MedLine Citation:
PMID:  22908249     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Projections of countries' future populations, broken down by age and sex, are widely used for planning and research. They are mostly done deterministically, but there is a widespread need for probabilistic projections. We propose a bayesian method for probabilistic population projections for all countries. The total fertility rate and female and male life expectancies at birth are projected probabilistically using bayesian hierarchical models estimated via Markov chain Monte Carlo using United Nations population data for all countries. These are then converted to age-specific rates and combined with a cohort component projection model. This yields probabilistic projections of any population quantity of interest. The method is illustrated for five countries of different demographic stages, continents and sizes. The method is validated by an out of sample experiment in which data from 1950-1990 are used for estimation, and applied to predict 1990-2010. The method appears reasonably accurate and well calibrated for this period. The results suggest that the current United Nations high and low variants greatly underestimate uncertainty about the number of oldest old from about 2050 and that they underestimate uncertainty for high fertility countries and overstate uncertainty for countries that have completed the demographic transition and whose fertility has started to recover towards replacement level, mostly in Europe. The results also indicate that the potential support ratio (persons aged 20-64 per person aged 65+) will almost certainly decline dramatically in most countries over the coming decades.
Authors:
Adrian E Raftery; Nan Li; Hana Ševčíková; Patrick Gerland; Gerhard K Heilig
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural     Date:  2012-08-20
Journal Detail:
Title:  Proceedings of the National Academy of Sciences of the United States of America     Volume:  109     ISSN:  1091-6490     ISO Abbreviation:  Proc. Natl. Acad. Sci. U.S.A.     Publication Date:  2012 Aug 
Date Detail:
Created Date:  2012-08-29     Completed Date:  2012-12-11     Revised Date:  2013-11-08    
Medline Journal Info:
Nlm Unique ID:  7505876     Medline TA:  Proc Natl Acad Sci U S A     Country:  United States    
Other Details:
Languages:  eng     Pagination:  13915-21     Citation Subset:  IM    
Affiliation:
Department of Statistics, University of Washington, Seattle, WA 98195-4322, USA. raftery@u.washington.edu
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MeSH Terms
Descriptor/Qualifier:
Adult
Age Distribution
Aged
Aged, 80 and over
Bayes Theorem
Birth Rate / trends*
Brazil / epidemiology
Censuses*
China / epidemiology
Demography / methods*
Female
Forecasting / methods*
Humans
India / epidemiology
Life Expectancy / trends
Logistic Models
Madagascar / epidemiology
Male
Middle Aged
Netherlands / epidemiology
Sex Distribution
United Nations / statistics & numerical data*
Young Adult
Grant Support
ID/Acronym/Agency:
R01 HD054511/HD/NICHD NIH HHS; R01 HD054511/HD/NICHD NIH HHS; R01 HD070936/HD/NICHD NIH HHS; R24 HD042828/HD/NICHD NIH HHS
Comments/Corrections

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