This paper evaluates whether mangroves can mitigate the impact of hurricanes on economic activity. The paper assembles a regionwide panel dataset that measures local economic activity using nightlights, potential hurricane damages using a detailed wind field model, and mangrove protection by mapping the width of mangrove forests on the path to the coast. The results show that hurricanes have negative short-run effects on economic activity, with losses likely concentrated in coastal lowlands that are exposed to both wind and storm surge hazards. In these coastal lowlands, the estimates show that nightlights decrease by up to 24% in areas that are unprotected by mangroves. By comparison, the impact of the hurricanes observed in the sample is fully mitigated in areas protected by mangrove belts of 1 km or more.
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.
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 con-*
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