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Probabilistic population forecasting: Short to very long-term()

Population forecasts are used by governments and the private sector for planning, with horizons up to about three generations (around 2100) for different purposes. The traditional methods are deterministic using scenarios, but probabilistic forecasts are desired to get an idea of accuracy, assess ch...

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Detalles Bibliográficos
Autores principales: Raftery, Adrian E., Ševčíková, Hana
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783793/
https://www.ncbi.nlm.nih.gov/pubmed/36568848
http://dx.doi.org/10.1016/j.ijforecast.2021.09.001
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author Raftery, Adrian E.
Ševčíková, Hana
author_facet Raftery, Adrian E.
Ševčíková, Hana
author_sort Raftery, Adrian E.
collection PubMed
description Population forecasts are used by governments and the private sector for planning, with horizons up to about three generations (around 2100) for different purposes. The traditional methods are deterministic using scenarios, but probabilistic forecasts are desired to get an idea of accuracy, assess changes, and make decisions involving risks. In a significant breakthrough, since 2015, the United Nations has issued probabilistic population forecasts for all countries using a Bayesian methodology that we review here. Assessment of the social cost of carbon relies on long-term forecasts of carbon emissions, which in turn depend on even longer-range population and economic forecasts, to 2300. We extend the UN method to very-long range population forecasts by combining the statistical approach with expert review and elicitation. While the world population is projected to grow for the rest of this century, it will likely stabilize in the 22nd century and decline in the 23rd century.
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spelling pubmed-97837932023-01-01 Probabilistic population forecasting: Short to very long-term() Raftery, Adrian E. Ševčíková, Hana Int J Forecast Article Population forecasts are used by governments and the private sector for planning, with horizons up to about three generations (around 2100) for different purposes. The traditional methods are deterministic using scenarios, but probabilistic forecasts are desired to get an idea of accuracy, assess changes, and make decisions involving risks. In a significant breakthrough, since 2015, the United Nations has issued probabilistic population forecasts for all countries using a Bayesian methodology that we review here. Assessment of the social cost of carbon relies on long-term forecasts of carbon emissions, which in turn depend on even longer-range population and economic forecasts, to 2300. We extend the UN method to very-long range population forecasts by combining the statistical approach with expert review and elicitation. While the world population is projected to grow for the rest of this century, it will likely stabilize in the 22nd century and decline in the 23rd century. 2023 2021-10-07 /pmc/articles/PMC9783793/ /pubmed/36568848 http://dx.doi.org/10.1016/j.ijforecast.2021.09.001 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license.
spellingShingle Article
Raftery, Adrian E.
Ševčíková, Hana
Probabilistic population forecasting: Short to very long-term()
title Probabilistic population forecasting: Short to very long-term()
title_full Probabilistic population forecasting: Short to very long-term()
title_fullStr Probabilistic population forecasting: Short to very long-term()
title_full_unstemmed Probabilistic population forecasting: Short to very long-term()
title_short Probabilistic population forecasting: Short to very long-term()
title_sort probabilistic population forecasting: short to very long-term()
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9783793/
https://www.ncbi.nlm.nih.gov/pubmed/36568848
http://dx.doi.org/10.1016/j.ijforecast.2021.09.001
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