ECONOMIC IMPACTS AND LAND USE CHANGE FROM A POLICY TO CONTROL DEFORESTATION IN THE BRAZILIAN AMAZON

The Brazilian Amazon region was the target of several development policies in the twentieth century which aimed at integrating the region into the rest of the Brazilian economy. With different structural features from the rest of Brazil and housing the largest rainforest in the world, the results of these policies were economic growth and deforestation. The deforestation in the Brazilian Amazon has attracted the attention of researchers and government around measures and policies that involve both its measurement and control. Besides maintaining a high level of biodiversity, the Amazon forest has also been discussion agenda of the international community, especially on the growing debate about the causes and consequences of global climate change. In the National Plan on Climate Change (NPCC) in 2008, Brazil has confirmed voluntary national targets for reducing emissions of greenhouse gases (GHG) that includes an 80% reduction in Amazon deforestation by 2020. The limited supply of land restricts the expansion of the agricultural frontier, which is one of the most important economic activities in the region. Thus, it seems relevant to investigate aspects of a possible trade-off between the goals of environmental conservation (reducing deforestation) and economic growth in the region. The main goal of this paper is to project the economic losses resulting from a policy to control deforestation in the Amazon. In methodological terms, this study advances in developing a Dynamic Interregional Computable General Equilibrium Model for 30 regions in Amazon, and include an ILUC model (indirect land use change) that allows conversion of land in different uses. With the model, it is also projected an economic growth scenario of the Amazon regions between 2006 and 2030. The results showed that the regions that present a higher GDP growth would be those that are on the deforestation frontier, mainly the producing regions of soybean and cattle. The most affected regions w...