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Using population projections in climate change analysis

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  • Daniel Rozell

    (Stony Brook University)

Abstract

The two leading sources of long-range population projections, the United Nations (UN) and the International Institute for Applied Systems Analysis (IIASA), currently disagree on the most likely end-of-the-century world population by over two billion people. Because climate change policy models are influenced by population uncertainty, this poses an underappreciated problem for analysts. Furthermore, long-range population projections have not been predictably stable over time and climate change policy models have not consistently used one set of population projections. This only increases the difficulty of comparing research results. Comparing the UN and IIASA population projections, the UN’s probabilistic population projections should be used with caution as they tend to understate the uncertainty in long-range population forecasts. Currently, the IIASA scenario projections are better suited to long-range climate change policy analysis. As a final recommendation, a simple demographic sub-model is proposed for use in cost-benefit climate change integrated assessment models that performs better than current alternatives.

Suggested Citation

  • Daniel Rozell, 2017. "Using population projections in climate change analysis," Climatic Change, Springer, vol. 142(3), pages 521-529, June.
    • Handle: RePEc:spr:climat:v:142:y:2017:i:3:d:10.1007_s10584-017-1968-2
    DOI: 10.1007/s10584-017-1968-2
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    Cited by:

    1. Gerlagh, Reyer & Jaimes, Richard & Motavasseli, Ali, 2017. "Global Demographic Change and Climate Policies," Other publications TiSEM 7a4ee2a9-e025-4ec0-8bc8-f, Tilburg University, School of Economics and Management.
    2. Jacques, Pierre & Delannoy, Louis & Andrieu, Baptiste & Yilmaz, Devrim & Jeanmart, Hervé & Godin, Antoine, 2023. "Assessing the economic consequences of an energy transition through a biophysical stock-flow consistent model," Ecological Economics, Elsevier, vol. 209(C).
    3. Guillaume Rohat, 2018. "Projecting Drivers of Human Vulnerability under the Shared Socioeconomic Pathways," IJERPH, MDPI, vol. 15(3), pages 1-23, March.

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