Probabilistic population forecasting: Short to very long-term

Adrian E. Raftery and Hana Ševčíková

International Journal of Forecasting, 2023, vol. 39, issue 1, 73-97

Abstract: 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.

Keywords: Bayesian hierarchical model; Cohort-component method of population projection; Expert elicitation; Scenario; Social cost of carbon (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:intfor:v:39:y:2023:i:1:p:73-97

DOI: 10.1016/j.ijforecast.2021.09.001

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