BeschreibungDeforestation is the most profound manifestation of changing land use patterns in the southern Amazon and is an important determinant of a variety of environmental issues, including biodiversity loss, carbon emissions and climate change. The extraction of natural resources has been widely discussed as a driver of deforestation. Previous studies investigated the roles of different drivers of forest loss, such as mining, pasture and cropland expansion and advancing infrastructure.
However, employed models disregard the spatial dimension and do not simultaneously take mining and agricultural activities into consideration, which can lead to bias due to omitted variables and/or inefficient estimates. In this work we integrate agricultural land use with mineral extraction panel data for the state of Mato Grosso, Brazil. Our spatial econometric model accounts for unobserved individual heterogeneity and spatial autocorrelation.
Our modelling approach enables a spatially explicit assessment of the various socio-economic drivers of deforestation, hence providing the means for more informed policy decisions and achieving improved sustainability of supply chains. Besides providing novel insights into the environmental impacts of resource extraction, the model can be used for forecasting future deforestation under different scenarios.
|Zeitraum||13 Mai 2019 → 15 Mai 2019|