@article{Baldos:330176,
      recid = {330176},
      author = {Baldos, Uris Lantz},
      title = {Food and environmental security in 2050: An application of  gridded agricultural economic modelling},
      address = {2017},
      pages = {3},
      year = {2017},
      note = {Presented at the 20th Annual Conference on Global Economic  Analysis, West Lafayette, IN, USA},
      abstract = {Agricultural economic models are indispensable in the  analysis of broad issues affecting the  farm-food-environment nexus. Many of these models have been  designed accordingly to accommodate country and/or  regional-level data – for example trade and economic data  from the GTAP database as well as agricultural production  data from UN FAO. However, it is becoming evident that  agricultural economic models are far too aggregated for the  analysis of localized agro-climatic issues that have broad  consequences on the global farm and food system. This is  particularly true for climate change. Climate-driven crop  yield projections from gridded crop and climate models are  quite heterogeneous within and across countries but instead  of using these refined projections researchers are  constrained to impose weighting methods to accommodate  aggregations in existing agricultural economic models (1)  (see Figure 1). This problem is also evident in the  assessment of land use change impacts from agriculture  wherein regional land supply elasticities are imposed and  detailed biomass and soil carbon from gridded global  potential vegetation models are aggregated.   In this  paper, we illustrate the advantages of using downscaled  global model of agriculture using the gridded SIMPLE model.  SIMPLE has been designed to capture the key drivers and  economic responses at work in driving long run changes in  the global farm and food system. The model has been  validated by looking at the historical experience (2) and  has been used in the assessment of food security (3) and  climate change adaptation (4). We take advantage of  SIMPLE’s flexibility and develop a gridded version of the  model wherein crop production activities are defined at the  geo-spatial level using agricultural production, area and  yield data from Monfreda et al. (5). This allows us to  downscale crop production from 16 regions to ~50,000  half-degree grid cells.},
      url = {http://ageconsearch.umn.edu/record/330176},
}