## 1 Introduction
This global CGE model, developed at the Center for Global Trade Analyses, has played a leading role in estimating biofuel induced land use changes. Several studies have used this model to evaluate iLUC emissions due to biofuels [7, 10, 11, 12, 17, 18]. This model uses two different land transformation elasticities to govern the supply of land in each region. The first transformation elasticity (named ETL1) governs land allocation among managed forest, cropland, and pasture land. The second transformation elasticity (named ETL2) distributes available croplands among alternative crops. In the absence of regional empirical estimates for these elasticities, the model uses the same value for each of these parameters for all regions presented in the model. Using similar land transformation elasticities for all regions presented in the model cannot be justified based on actual observations. As explained later on in this paper, historical observations confirm that regional land use changes followed different patterns during the past two decades. For example, historical data confirms the area of USA cropland remained constant during the past two decades, but its distribution among crops has changed significantly during the same time period. This indicates that no movement along land cover frontier has accrued in the USA during the past two decades, but movement along the cropland frontier occurred frequently in this economy. On the other hand, the area of cropland has expanded significantly in Sub Saharan Africa with relatively minor changes in its distribution among crops over the past two decades. Clearly these two patterns are not consistent with using the same land transformation elasticities for these two regions. Furthermore, as shown in the top panel of Figure 1, the GTAP-BIO model puts three types of land cover items (forest, pasture, and cropland) in one nest and implicitly assumes that the economic costs of converting one hectare of forest to cropland is similar to the economic costs of converting one hectare of pasture land to cropland and _vice versa_. This set up is another key deficiency of the GTAP-BIO model. Including cropland, forest, and pasture land in the same nest could cause systematic bias in land conversion processes among land cover types due to biofuel production. In general this is not the case and often the opportunity costs of converting forest to cropland is higher than the economic costs of converting pastureland to cropland. In this paper we remove these two deficiencies. We tune the regional land transformation elasticities based on actual historical observations on changes in land cover and distribution of cropland among alternative crops during the past two decades. To accomplish this task we use published data on cropland use around the world by the Food and Agricultural Organization (FAO) of the United Nation over the period 1990-2010. We alters the land cover component of the land supply tree, see the bottom panel of Figure 1, to have forest and pasture land in two different nests as described later in this paper. Then we re-evaluate the global land use impacts due to the USA ethanol program using the improved model tuned with actual observations. Finally, we show that compared to the old model the new model projects: (1) less expansion in global cropland; (2) lower share for the USA economy in global cropland expansion; (3) and lower forest share in global cropland expansion. In what follows, we first review the regional historical observations on cropland changes to distinguish regional land allocation patterns. Then we use the distinguished regional land allocation patterns to tune the GTAP-BIO land transformation elasticities based on actual observations. In the next step we alter the land cover frontier of the model. The next section defines our experiments to evaluate iLUC due to ethanol expansion using the new and old model. Then we present the simulation results. The last section provides conclusions.