text: **Simulation of market price using GTAP.**The yield changes for maize from the DSSAT models under 
  1.5 °C and 2.0 °C temperature increase are used to carry out simulations using competitive market for changes 
  in production, market price, and self-sufficiency ratio of maize at national and global levels53,54. For this study, we 
  use a comparative static analysis approach to simulate the impact of climate changes on the prices and trade of 
  the major food crops under current economic conditions. Utilizing current economic conditions has the advan- 
  tage of minimizing assumptions and model uncertainties related to future economic conditions55,56. 
  
  The original GTAP database doesn’t include maize as a separate sector, rather it is combined with other coarse 
  grains to form an “other coarse grain” sector. For this study, we updated the GTAP database by splitting maize 
  from the original sector in the database, design an appropriate sectoral and regional aggregation scheme to the 
  original database. The detailed method is given as follows: 
  
  First, we improved the database by splitting maize from the existing sector “other coarse grain”, following 
  similar work using GTAP57–59 based on the routines from the Splitcom method60. In this procedure, the old flows 
  of data both at national and trade levels are allocated between the new flows using weights. The national weights 
  include the division of each unsplit user’s use of the original split commodity among the new commodities; the 
  division of unsplit inputs to the original industry between the new industries; the splitting of new industry’s use 
  of each new commodity. Maize use is mainly shared between feed, food, processing and others (seed, waste, etc.). 
  Trade shares allocate the original slice of the split commodity into the new commodity for all elements of 
  basic price value, tax, and margin. Finally, we used the RAS method for balancing the newly created database. 
  The values for the national shares matrix were obtained from FAOSTAT. The trade shares matrix was calculated 
  based on the data from UN Comtrade Database. 