This paper analyzes the impact of expansion in biofuels on the global economy, income distribution and poverty. It utilizes simulation results of two World Bank models: a global computable general equilibrium (CGE) model integrated with biofuels, land-use, and climate change modules, and a global income distribution model that utilizes household survey data of 116 countries. The first model simulates the effects over time of large scale expansion of biofuels on resource allocation, output prices, commodity prices, factor prices, and household income of the different countries and regions in the world. The second model uses these results recursively to calculate the impact on global income distribution and poverty. The results from the CGE model indicate that large scale expansion of biofuels lead to higher world prices of sugar, corn, oilseeds, wheat, and other grains, which lead to higher food prices. The increase in food inflation is higher in developing countries than in developed countries. The expansion of biofuels results in higher wages of unskilled rural labor relative to wages of the other labor types which are skilled urban, skilled rural, and unskilled urban, especially in developing countries. These positive wage effects on unskilled rural labor trigger movement of unskilled urban labor towards rural and agriculture. This is because production of feedstock in developing countries is relatively intensive in the use of unskilled rural labor. The effects of large scale expansion of biofuels on poverty vary across regions. But overall there is a slight increase in global poverty. The increase largely comes from South Asia (particularly India) and Sub-Saharan Africa. Significant number of countries in Sub-Saharan Africa show higher poverty with large scale expansion of biofuels. However, poverty declines in East Asia and Latin America regions. Overall, there is a slight increase in the GINI coefficient. There is a slight increase in the GINI coefficient in Sub-Saharan Africa and East Asia. There is a small reduction in the GINI coefficient in the rest of the regions.


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