Very Long-Term Probabilistic Population Projections

Presented by Adrian Raftery (Université de Washington) ; speaker Giancarlo Camarda (Ined UR05 : mortalité, santé, épidémiologie)

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, to assess changes, and to make decisions involving risks. In a major 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 rely 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. We find that, while world population is projected to grow for most of the rest of this century, it is likely to stabilize in the 22nd century, and to decline in the 23rd century.This is joint work with Hana Ševčíková.