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This paper develops the FOR-DICE model to explore the potential role of the global forest in reducing climate change. It presents a basic framework for assessing the boreal, tropical, and temperate forests as both a source of renewable energy and a resource to sequester and store carbon. The focus of the paper is to explore whether climate policies should focus on increasing the forest biomass, to sequester and store carbon, or on increasing the use of the forest biomass as a source of energy, to substitute fossil fuels. The paper shows that the global forest can play an important role in reducing atmospheric carbon. The main finding at the global level is that it is better to increase the forest biomass rather than increase the use of forest bioenergy. The reason for this is that the decrease in forest carbon stock created by increased bioenergy harvests is not offset by avoided fossil fuel emissions. This finding suggests that setting high bioenergy targets, without considering the dynamics of the forest stock and the efficiency of bioenergy, will be detrimental to climate change mitigation.

This paper develops the FRICE, a framework that determines optimal levels of forest climate tools in the context of global climate policy. The paper integrates afforestation and avoided deforestation into the well-known global multi-regional integrated assessment model, RICE-2010. The paper finds that climate forest tools can play an essential role in global climate policy and that this role is increasingly important under stringent temperature targets. Under a 2_C temperature target, the model reveals that emission reductions from avoided deforestation are quickly exhausted whereas afforestation is capable of substantially reducing emission reductions in both the medium and long run. The model also indicates that the most significant reductions in emissions from avoided deforestation and afforestation can be achieved by focusing policy efforts on tropical forests.

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.

In this paper, we use an integrated assessment model to examine the implications of not recognizing, and partially recognizing forest carbon in climate policy. Specifically, we investigate the impact of an asymmetric carbon policy that recognizes emissions from fossil fuels while ignoring emissions from forests. We additionally investigate the relative importance of not recognizing positive emissions from a reduction in the stock of forest biomass, or of not recognizing negative emissions from the growth of forest biomass. We show that asymmetric carbon policies lead to lower levels of welfare, as well as higher emissions and carbon prices. This occurs because the forest resource will be allocated inefficiently under these carbon policies. Broadly, we find that when the social planner does not account for neither positive or negative forest emissions, the planner will set bioenergy levels that are too high and afforestation and avoided deforestation levels that are too low. Our results further reveal that not recognizing forest emissions leads to larger welfare losses than not recognizing sequestration.