There is a continuing debate over the role that woody bioenergy plays in climate mitigation. This paper clarifies this controversy and illustrates the impacts of woody biomass demand on forest harvests, prices, timber management investments and intensity, forest area, and the resulting carbon balance under different climate mitigation policies. Increased bioenergy demand increases forest carbon stocks thanks to afforestation activities and more intensive management relative to a no-bioenergy case. Some natural forests, however, are converted to more intensive management, with potential biodiversity losses. Incentivizing both wood-based bioenergy and forest sequestration could increase carbon sequestration and conserve natural forests simultaneously. We conclude that the expanded use of wood for bioenergy will result in net carbon benefits, but an efficient policy also needs to regulate forest carbon sequestration.

There is widespread concern that biomass energy policy that promotes forests as a supply source will cause net carbon emissions. Most of the analyses that have been done to date, however, are biological, ignoring the effects of market adaptations through substitution, net imports, and timber investments. This paper uses a dynamic model of forest and land use management to estimate the impact of United States energy policies that emphasize the utilization of forest biomass on global timber production and carbon stocks over the next 50 years. We show that when market factors are included in the analysis, expanded demand for biomass energy increases timber prices and harvests, but reduces net global carbon emissions because higher wood prices lead to new investments in forest stocks. Estimates are sensitive to assumptions about whether harvest residues and new forestland can be used for biomass energy and the demand for biomass. Restricting biomass energy to being sourced only from roundwood on existing forestland can transform the policy from a net sink to a net source of emissions. These results illustrate the importance of capturing market adjustments and a large geographic scope when measuring the carbon implications of biomass energy policies.

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Forests are critical for stabilizing our climate, but costs of mitigation over space, time, and stakeholder group remain uncertain. Using the Global Timber Model, we project mitigation potential and costs for four abatement activities across 16 regions for carbon price scenarios of $5–$100/tCO2. We project 0.6–6.0 GtCO2 yr−1 in global mitigation by 2055 at costs of 2–393 billion USD yr−1, with avoided tropical deforestation comprising 30–54% of total mitigation. Higher prices incentivize larger mitigation proportions via rotation and forest management activities in temperate and boreal biomes. Forest area increases 415–875 Mha relative to the baseline by 2055 at prices $35–$100/tCO2, with intensive plantations comprising <7% of this increase. Mitigation costs borne by private land managers comprise less than one-quarter of total costs. For forests to contribute ~10% of mitigation needed to limit global warming to 1.5 °C, carbon prices will need to reach $281/tCO2 in 2055.

Natural disasters give rise to loss and damage and may affect subjective expectations about the prevalence and severity of future disasters. These expectations might then in turn shape individuals’ investment behaviors, potentially affecting their incomes in subsequent years. As part of an emerging literature on endogenous preferences, economists have begun studying the consequences that exposure to natural disasters have on risk attitudes, perceptions, and behavior. We add to this field by studying the impact of being struck by the December 2012 Cyclone Evan on Fijian households’ risk attitudes and subjective expectations about the likelihood and severity of natural disasters over the next 20 years. The randomness of the cyclone’s path allows us to estimate the causal effects of exposure on both risk attitudes and risk perceptions. Our results show that being struck by an extreme event substantially changes individuals’ risk perceptions as well as their beliefs about the frequency and magnitude of future shocks. However, we find sharply distinct results for the two ethnicities in our sample, indigenous Fijians and Indo-Fijians; the impact of the natural disaster aligns with previous results in the literature on risk attitudes and risk perceptions for Indo-Fijians, whereas they have little to no impact on those same measures for indigenous Fijians. To provide welfare implications for our results, we compare households’ risk perceptions to climate and hydrological models of future disaster risk, and find that both ethnic groups over-infer the risk of future disasters relative to the model predictions. If such distorted beliefs encourage over-investment in preventative measures at the cost of other productive investments, these biases could have negative welfare impacts. Understanding belief biases and how they vary across social contexts may thus help decision makers design policy instruments to reduce such inefficiencies, particularly in the face of climate change.