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When Not in the Best of Worlds: Uncertainty and Forest Carbon Sequestration

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Abstract

It is argued that the forest can provide low-cost options to reduce the atmospheric CO2 concentration. However, many dimensions of the future dynamics of the forest, and its interactions with climate change are still not well understood. This paper provides new insights into how these types of uncertainties affect the optimal climate policy. We model uncertainty over several key forest parameters by using the novel state-contingent approach. Our main results show that the importance of including optimal forest controls in climate policy increases when the dynamics of the forest are uncertain. Ignoring uncertainties concerning the forest will lead to biased estimates of the social costs of carbon and be misleading when evaluating climate policies. Conversely, recognizing forest uncertainties and its potential to mitigate climate change will lead to a robust policy where the cost of uncertainty to a large extent can be avoided.

Suggested Citation

  • Eriksson, Mathilda & Vesterberg, Anders, 2016. "When Not in the Best of Worlds: Uncertainty and Forest Carbon Sequestration," CERE Working Papers 2016:4, CERE - the Center for Environmental and Resource Economics.
    • Handle: RePEc:hhs:slucer:2016_004
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    File URL: http://www.cere.se/se/forskning/publikationer/743-when-not-in-the-best-of-worlds-uncertainty-and-forest-carbon-sequestration.html
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    Cited by:

    1. Eriksson, Mathilda, 2020. "Afforestation and avoided deforestation in a multi-regional integrated assessment model," Ecological Economics, Elsevier, vol. 169(C).
    2. Eriksson, Mathilda & Brännlund, Runar & Lundgren, Tommy, 2018. "Pricing forest carbon: Implications of asymmetry in climate policy," Journal of Forest Economics, Elsevier, vol. 32(C), pages 84-93.

    More about this item

    Keywords

    Keywords: Climate change; Integrated assessment; Uncertainty; Carbon sequestration;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • Q23 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Forestry
    • Q54 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Climate; Natural Disasters and their Management; Global Warming

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