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Probabilistic population forecasting: Short to very long-term.

Adrian E Raftery1, Hana Ševčíková2

  • 1Departments of Statistics and Sociology, Box 354322, University of Washington, Seattle, WA 98195-4322, USA.

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Summary
This summary is machine-generated.

Global population forecasts are extending to 2300. This study enhances United Nations probabilistic methods, projecting population stabilization in the 22nd century and a decline in the 23rd century.

Keywords:
Bayesian hierarchical modelCohort-component method of population projectionExpert elicitationScenarioSocial cost of carbon

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Area of Science:

  • Demography
  • Climate Change Economics
  • Bayesian Statistics

Background:

  • Population forecasts are crucial for governmental and private sector planning, traditionally using deterministic scenarios.
  • Probabilistic forecasts are increasingly desired for accuracy assessment and risk-based decision-making.
  • The United Nations has provided probabilistic population forecasts since 2015 using a Bayesian methodology.

Purpose of the Study:

  • To review the United Nations' Bayesian methodology for probabilistic population forecasts.
  • To extend existing methods for very-long range population forecasts up to 2300.
  • To inform long-term projections of carbon emissions and the social cost of carbon.

Main Methods:

  • Review of the United Nations' Bayesian probabilistic population forecasting methodology.
  • Extension of the UN method by integrating expert review and elicitation with statistical approaches.
  • Application to generate population forecasts beyond 2100 to 2300.

Main Results:

  • World population is projected to grow through the 21st century.
  • Population is expected to stabilize during the 22nd century.
  • A decline in global population is projected for the 23rd century.

Conclusions:

  • The enhanced methodology provides crucial long-term population projections necessary for climate change assessments.
  • Extending probabilistic forecasting to 2300 improves the accuracy of social cost of carbon calculations.
  • Probabilistic population forecasting is essential for informed long-range planning and risk assessment.