The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Bayesian Probabilistic Projections of Life Expectancy for All Countries
Open accessAbstract
We propose a Bayesian hierarchical model for producing probabilistic forecasts of male period life expectancy at birth for all the countries of the world to 2100. Such forecasts would be an input to the production of probabilistic population projections for all countries, which is currently being considered by the United Nations. To evaluate the method, we conducted an out-of-sample cross-validation experiment, fitting the model to the data from 1950–1995 and using the estimated model to forecast for the subsequent 10 years. The 10-year predictions had a mean absolute error of about 1 year, about 40 % less than the current UN methodology. The probabilistic forecasts were calibrated in the sense that, for example, the 80 % prediction intervals contained the truth about 80 % of the time. We illustrate our method with results from Madagascar (a typical country with steadily improving life expectancy), Latvia (a country that has had a mortality crisis), and Japan (a leading country). We also show aggregated results for South Asia, a region with eight countries. Free, publicly available R software packages called bayesLife and bayesDem are available to implement the method.
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Cites
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A Potential Decline in Life Expectancy in the United States in the 21st Century
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Probabilistic Forecasts, Calibration and Sharpness
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Self-citationIn Search of Methuselah: Estimating the Upper Limits to Human Longevity
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Cited by
Bayesian probabilistic population projections for all countries
Raftery, A. E., Li, N., Ševčíková, H., Gerland, P., & Heilig, G. K. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1211452109 · Cited by 298
Self-citationThe Future Prevalence of Sarcopenia in Europe: A Claim for Public Health Action
Ethgen, O., Beaudart, C., Buckinx, F., Bruyère, O., & Reginster, J. Y. (2017) · Calcified Tissue International · doi:10.1007/s00223-016-0220-9 · Cited by 280
Probabilistic population projections with migration uncertainty
Azose, J. J., Ševčíková, H., & Raftery, A. E. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1606119113 · Cited by 77
Self-citationSingh, A., Allen, D., Fracassi, A., Tumurbaatar, B., Natarajan, C., Scaduto, P., Woltjer, R., Kayed, R., Limon, A., Krishnan, B., et al. (2020) · Journal of Alzheimer's Disease · doi:10.3233/jad-200716 · Cited by 56
Metadata
- Authors
- Raftery, A. E., Chunn, J. L., Gerland, P., & Ševčíková, H.
- Venue
- Demography
- Publisher
- Duke University Press
- Published
- 2013-03-15
- Volume
- 50
- Issue
- 3
- Pages
- 777-801
- ISSN
- 0070-3370 (ISSN-L)
- 1533-7790
- OpenAlex
- W2109692581
- Cited by
- 203
- References
- 6
- FWCI
- 56.89
- Type
- journal article
- Language
- en
- Open access
- hybrid
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