Understanding the factors that drive land-use change, and developing better methods for projecting future land-use change, become vitally important in the climate change context. The 3rd Assessment Report of the UN Intergovernmental Panel on Climate Change (IPCC) noted that "the emissions scenarios considered in future climate change studies need to integrate high resolution representations of land use change" and that increased coupling among the various relevant components—such as mitigation and adaptation responses to climate change, and climate response to land use—should be included in a consistent framework for integrated assessment (Jones et al. AR-3 2001, Chapter 3). While much work has been done to include global forecasts of natural land cover types such as forests and deserts at high spatial resolutions, little has been done to incorporate into these forecasts the socioeconomic drivers of land-use change, such as agriculture, forestry, and urbanization on a global scale. To address this urgent need for improved global land-use forecasts, we are developing a versatile high-resolution companion to the CIM-EARTH computable general equilibrium (CGE) global economics framework. The Partial-Equilibrium Economic Landuse (PEEL) model generates consistent forecasts of the land-use change (LUC) that results from changing growing conditions, technology, resource availability, and demands. We illustrate the usefulness of the model by applying the prototype to the important and highly topical question of the implications of an aggressive biofuels policy on LUC and soil carbon.