What drives deforestation in the Brazilian Amazon? Evidence from satellite and socioeconomic data

This paper analyzes the determinants of deforestation in the Brazilian Amazon. From a model of optimal use, it derives and then estimates a deforestation equation on county-level data for the period 1978 to 1988. The data include a deforestation measure from satellite images, which is a great advance in that it allows improved within-county analysis. Evidence exists that: increased road density in a county leads to more deforestation in that county and in neighboring counties; development projects were associated with deforestation in the 1970s but not in the 1980s; greater distance from markets south of the Amazon leads to less deforestation; and better soil quality leads to more deforestation. The results for government provision of credit are mixed across specifications. The population density, although the primary explanatory variable in most previous empirical work, does not have a significant effect when all the variables motivated within the model are included. However, a quadratic specification yields a more robust population result: the first few people entering an empty county have significantly more impact than the same number of people added to a densely populated county. This result suggests the importance of the spatial distribution of population.Environmental Economics&Policies,Wetlands,Climate Change,Banks&Banking Reform,Water Conservation,Environmental Economics&Policies,Climate Change,Energy and Environment,Forestry,Banks&Banking Reform

Tropical Forest Protection, Uncertainty, and the Environmental Integrity of Carbon Mitigation Policies

Tropical forests are estimated to release approximately 1.7 PgC per year as a result of deforestation. Avoiding tropical deforestation could potentially play a significant role in carbon mitigation over the next 50 years if not longer. Many policymakers and negotiators are skeptical of our ability to reduce deforestation effectively. They fear that if credits for avoided deforestation are allowed to replace fossil fuel emission reductions for compliance with Kyoto, the environment will suffer because the credits will not reflect truly additional carbon storage. This paper considers the nature of the uncertainties involved in estimating carbon stocks and predicting deforestation. We build an empirically based stochastic model that combines data from field ecology, geographical information system (GIS) data from satellite imagery, economic analysis and ecological process modeling to simulate the effects of these uncertainties on the environmental integrity of credits for avoided deforestation. We find that land use change, and hence additionality of carbon, is extremely hard to predict accurately and errors in the numbers of credits given for avoiding deforestation are likely to be very large. We also find that errors in estimation of carbon storage could be large and could have significant impacts. We find that in Costa Rica, nearly 42% of all the loss of environmental integrity that would arise from poor carbon estimates arises in one life zone, tropical wet. This suggests that research effort might be focused in this life zone.climate, economics, carbon sequestration, uncertainty, policy, tropics

Will Buying Tropical Forest Carbon Benefit The Poor? Evidence from Costa Rica

We review claims about the potential for carbon markets that link both payments for carbon services and poverty levels to ongoing rates of tropical deforestation. We then examine these effects empirically for Costa Rica during the 20th century using an econometric approach that addresses the irreversibilities in deforestation. We find significant effects of the relative returns to forest on deforestation rates. Thus, carbon payments would induce conservation and also carbon sequestration, and if land users were poor could conserve forest while addressing rural poverty. However, we find poorer areas are less responsive to returns. This and transaction costs could lead carbon payments policies not to be focused upon the poor. Other practical considerations may also dampen an understandable enthusiasm for service-based payments addressing both environment and inequality. Nonetheless, as the poor live in areas with more forest, they may benefit most from payments

Will Buying Tropical Forest Carbon Benefit The Poor? Evidence from Costa Rica

We review claims about the potential for carbon markets that link both payments for carbon services and poverty levels to ongoing rates of tropical deforestation. We then examine these effects empirically for Costa Rica during the 20th century using an econometric approach that addresses the irreversibilities in deforestation. We find significant effects of the relative returns to forest on deforestation rates. Thus, carbon payments would induce conservation and also carbon sequestration, and if land users were poor could conserve forest while addressing rural poverty. However, we find poorer areas are less responsive to returns. This and transaction costs could lead carbon payments policies not to be focused upon the poor. Other practical considerations may also dampen an understandable enthusiasm for service-based payments addressing both environment and inequality. Nonetheless, as the poor live in areas with more forest, they may benefit most from payments.Carbon, Costa Rica, Deforestation, Forest products, Climate Change, Marketing, Poverty, Rural population, Tropical forests

Vorapaxar in the secondary prevention of atherothrombotic events

Item does not contain fulltextBACKGROUND: Thrombin potently activates platelets through the protease-activated receptor PAR-1. Vorapaxar is a novel antiplatelet agent that selectively inhibits the cellular actions of thrombin through antagonism of PAR-1. METHODS: We randomly assigned 26,449 patients who had a history of myocardial infarction, ischemic stroke, or peripheral arterial disease to receive vorapaxar (2.5 mg daily) or matching placebo and followed them for a median of 30 months. The primary efficacy end point was the composite of death from cardiovascular causes, myocardial infarction, or stroke. After 2 years, the data and safety monitoring board recommended discontinuation of the study treatment in patients with a history of stroke owing to the risk of intracranial hemorrhage. RESULTS: At 3 years, the primary end point had occurred in 1028 patients (9.3%) in the vorapaxar group and in 1176 patients (10.5%) in the placebo group (hazard ratio for the vorapaxar group, 0.87; 95% confidence interval [CI], 0.80 to 0.94; P<0.001). Cardiovascular death, myocardial infarction, stroke, or recurrent ischemia leading to revascularization occurred in 1259 patients (11.2%) in the vorapaxar group and 1417 patients (12.4%) in the placebo group (hazard ratio, 0.88; 95% CI, 0.82 to 0.95; P=0.001). Moderate or severe bleeding occurred in 4.2% of patients who received vorapaxar and 2.5% of those who received placebo (hazard ratio, 1.66; 95% CI, 1.43 to 1.93; P<0.001). There was an increase in the rate of intracranial hemorrhage in the vorapaxar group (1.0%, vs. 0.5% in the placebo group; P<0.001). CONCLUSIONS: Inhibition of PAR-1 with vorapaxar reduced the risk of cardiovascular death or ischemic events in patients with stable atherosclerosis who were receiving standard therapy. However, it increased the risk of moderate or severe bleeding, including intracranial hemorrhage. (Funded by Merck; TRA 2P-TIMI 50 ClinicalTrials.gov number, NCT00526474.)