## 2 Experimental Section
### Modifications in GTAP Land Transformation Elasticities  
This section provides a framework to tune the GTAP land transformation elasticities with the historical observed land used patterns. As mentioned in section 3 the regional observed trends in land use patterns prior and after the boom in global biofuel industry are very similar, except that the area shares of maize and oilseeds tends to be higher since 2004. For this reason we tune the GTAP land transformation elasticities for the observed patterns during the time period of 2004-2010. We begin the tuning process with the regional land cover elasticities. The historical changes in total harvested area of a region is a good indication of changes in cropland cover over time, in particular when they are in line with historical changes in forest area. The GTAP-BIO model assumes \(\mathrm{ETL1=-0.2}\) everywhere across the world. As noted in the supporting documents of [PERSON] _et al._[7], this relatively small value had been selected from the [PERSON] _et al._[15] calibration process. These authors developed a calibration process to estimate aggregated cropland transformation elasticities as a function of time based on [PERSON] [19] who estimated land supply elasticities for the USA economy using county level data observed in 1982, 1987, 1992, and 1997. [PERSON] _et al._[15] have shown that the land cover transformation elasticity should be small for short to medium run time horizons. The choice \(\mathrm{ETL=-0.2}\) is clearly made based on observations on the historical land use changes in USA until 1997. While this figure fairly represents inflexibility in the USA land cover frontier, recent observations confirm more inflexibility in USA land cover frontier at the aggregate level in recent years. For example, recent evidence shows that cropland rent has increased faster than pasture rent in recent years in USA, but the area of cropland remained relatively unchanged. The ratio of cropland rent over pasture rent has increased gradually from about 8 in 2004 to 9.3 in 2010. This means that land owners/farmers had the incentive to move their land from pasture to cropland. However, recent observations indicate that the area of cropland has not increased in the USA in recent years. This confirms a very small land transformation elasticity for the USA land cover frontier. While data suggest very small land transformation elasticity for US, exiting evidence indicates major movements in land cover in other regions. This means that a uniform and small value of land transformation elasticity does not reflect actual regional observations. To tune this value to the observed changes in land cover of each region, the 19 regions of GTAP-BIO model are ranked based on their absolute value of annual average changes in harvested area since 2004. The results are reported in Table 1. The 19 regions are divided into four categories based on the following schedule:  
1. _Regions with very low rate of land transformation_: This category represents regions with very limited changes in land cover during the time period of 2004-2010. The absolute values of changes in the harvested areas of these regions were below 0.25% per year after 2004. To limit land conversion among forest, pasture, and cropland in these regions we assigned a value of \(\mathrm{ETL1=-0.02}\) to the lower level of the land supply nest. 2. _Regions with low rate of land transformation_: This category represents regions with relatively low annual rates of land transformation during the targeted time period. The absolute value of changes in the harvested areas of these region where higher than 0.25% and lower than 0.75% since 2004. For these regions we assigned a value ofETL1 = -0.1 (half of the original value of GTAP-BIO model) to the lower level of their land supply nest. * _Regions with high rate of land transformation_: This group represents regions with relatively large changes in their harvested areas.