Global Land Use Impacts of U.S. Ethanol: Revised Analysis Using GDyn-BIO Framework

  • Alla A. GolubEmail author
  • Thomas W. Hertel
  • Steven K. Rose
Part of the Natural Resource Management and Policy book series (NRMP, volume 40)


This paper describes dynamic extension of the comparative static computable general equilibrium (CGE) GTAP-BIO model—framework employed in assessments of biofuel policies. In the dynamic extension, called GDyn-BIO, several structural components of the static model, including food demand responses to higher incomes and intensification options in land-based sectors and food processing, were revised to better capture changes in derived demand for land under pressure of growing population and per capita incomes. The impact of 15-billion gallon biofuel mandate on land use, analyzed with the GDyn-BIO model, evolves significantly over time. In particular, net global cropland brought into production due to the mandate declines over time, which is in sharp contrast to the results of static analysis where policy impacts are pictured as fixed for the next 30 years. Despite the fact that land use change impacts of this policy are transitory, environmental impacts and the global warming implications of such policies should not be underestimated. The policy causes earlier conversion of forest and pasture lands to cropland, resulting in earlier GHG emissions and lost carbon sequestration that contribute to global warming.


Biofuels Dynamic general equilibrium model Land use change 


  1. Ahammad, H., and R. Mi., 2005. Land Use Change Modeling in GTEM: Accounting for forest sinks. Australian Bureau of Agricultural and Resource Economics. Presented at EMF 22: Climate Change Control Scenarios, Stanford University, California, 25–27 May.Google Scholar
  2. Ahmed, A., T.W. Hertel, and R. Lubowski. 2008. “Calibration of a Land Cover Supply Function using Transition Probabilities”, GTAP Research Memorandum, Center for Global Trade Analysis, Purdue University,
  3. Anderson, S.T. 2012. The Demand for Ethanol as a Gasoline Substitute. Journal of Environmental Economics and Management 63: 151–168.CrossRefGoogle Scholar
  4. Anderson, K. and A. Strutt. 2012. “Growth in Emerging Economies: Implications for Resource-Rich Countries by 2030.” Paper prepared for the 15th Annual Conference on Global Economic Analysis, Geneva, 27–29 June 2012.Google Scholar
  5. Berry, S., and W. Schlenker. 2011. Technical Report for the ICCT: Empirical Evidence on Crop Yield Elasticities.
  6. Birur, D., T. Hertel, and W. Tyner. 2008. “Impact of Biofuel Production on World Agricultural Markets: A Computable General Equilibrium Analysis.” GTAP working paper 53. Center for Global Trade Analysis, Purdue University, West Lafayette, IN, USA.Google Scholar
  7. Burniaux, J., and T. Truong. 2002. “GTAP-E: An Energy-Environmental Version of the GTAP Model”, GTAP Technical Paper No. 16, Center for Global Trade Analysis. Purdue University, West Lafayette, IN, USA.Google Scholar
  8. Carter, C., Rausser, G., and Smith A. 2012. “The Effect of the U.S. Ethanol Mandate on Corn Prices”. Working paper.
  9. Chappuis, T., and T. Walmsley. 2011. “Projections for World CGE Model Baselines”. GTAP Research Memorandum No. 22, Center for Global Trade Analysis. Purdue University, West Lafayette, IN, USA.Google Scholar
  10. Darwin, R., M. Tsigas, J. Lewandrowski, and A. Raneses. 1995. World Agriculture and Climate Change: Economic Adaptations. Agricultural Economic Report no. 703, Economic Research Service, US Department of Agriculture, Washington DC.Google Scholar
  11. Economic Research Service, US Department of Agriculture, Briefing Rooms, 2006. “Food Marketing and Farm Spreads: USDA Marketing Bill”, available on line at
  12. Emvalomatis, G., S.E. Stefanou, and A.O. Lansink. 2009. “Dynamic Decomposition of Total Factor Productivity Change in the EU Food, Beverages, and Tobacco Industry: The Effect of R&D.” A resilient European food industry and food chain in a challenging world. Presented at the 113th European Association of Agricultural Economists Seminar, Chania, Crete, Greece.Google Scholar
  13. FAOSTAT. Retrieved April 2013 from
  14. Fuglie, K. 2010. Total Factor Productivity in the Global Agricultural Economy: Evidence from FAO Data. The Shifting Patterns of Agricultural Production and Productivity Worldwide, 63–93. Ames, Iowa: The Midwest Agribusiness Trade Research and Information Center, Iowa State University.Google Scholar
  15. Gibbs, H.K., S. Yui, and R. Plevin. 2014. New Estimates of Soil and Biomass Carbon Stocks for Global Economic Models. GTAP Technical Paper 33. Center for Global trade Analysis, Purdue University, West Lafayette, IN.Google Scholar
  16. Gitiaux, X., S. Paltsev, J. Reilly and S. Rausch. 2009. “Biofuels, Climate Policy and the European Vehicle Fleet”. Report No. 176. The MIT Joint Program on the Science and Policy of Global Change, available online
  17. Golub, A., and T.W. Hertel. 2008. Global economic integration and land use change. Journal of Economic Integration 23 (3): 463–488.CrossRefGoogle Scholar
  18. Golub, A., T. Hertel, and B. Sohngen. 2009. Land Use Modelling in Recursively-Dynamic GTAP Framework. In Economic Analysis of Land Use in Global Climate Change Policy, eds. Hertel, T., S. Rose, and R. Tol. Routledge, 235–278.Google Scholar
  19. Golub, A., and T. Hertel. 2012. “Modeling Land Use Change Impacts of Biofuels in the GTAP-BIO Framework.” Climate Change Economics, Volume 03, Issue 03.Google Scholar
  20. Hanoch, G. 1975. Production and demand models with direct or indirect implicit additivity. Econometrica 43: 395–419.CrossRefGoogle Scholar
  21. Hertel, T.W. (1997). Global Trade Analysis, Modeling and Applications. Cambridge, Cambridge University Press.Google Scholar
  22. Hertel, T., R. McDougall, Narayanan, B.G. and A.H. Aguiar. 2008. “Behavioral Parameters”. Chapter 14 in Narayanan and Walmsley, Ed. Global Trade, Assistance, and Production: The GTAP 7 Data Base, Center for Global Trade Analysis, Purdue University.Google Scholar
  23. Hertel, T., H.-L. Lee, S. Rose, and B. Sohngen, 2009. “Modeling Land-use Related Greenhouse Gas Sources and Sinks and their Mitigation Potential”. In Economic Analysis of Land Use in Global Climate Change Policy, eds. T. Hertel, S. Rose, R. Tol, Routledge Publishing.Google Scholar
  24. Hertel, T.W., A. Golub, A.D. Jones, M. O’Hare, R.J. Plevin, and D.M. Kammen. 2010a. Global land use and greenhouse gas emissions impacts of U.S. maize ethanol: Estimating market-mediated responses. BioScience 60 (3): 223–231.CrossRefGoogle Scholar
  25. Hertel, T.W., W.E. Tyner, and D.K. Birur. 2010b. The global impacts of biofuel mandates. The Energy Journal 31 (1): 75–100.CrossRefGoogle Scholar
  26. Huang, H., and M. Khanna. 2010. An econometric analysis for U.S. crop yield and cropland acreage. Discussion paper: University of Illinois, Urbana - Champaign.Google Scholar
  27. Holland, S.P., C.R. Knittel, and J.E. Hughes. 2008. Greenhouse gas reductions under low carbon fuel standards? American Economic Journal: Economic Policy 1 (1): 106–146.Google Scholar
  28. Ianchovichina, E., and R. McDougall, 2001. “Structure of Dynamic GTAP.” GTAP Technical Paper 17, Center for Global Trade Analysis, available on line at
  29. Keeney, R., and T. W. Hertel. 2009. The Indirect Land Use Impacts of United States Biofuel. Policies: The Importance of Acreage, Yield, and Bilateral Trade Responses. American Journal of Agricultural Economics 91(4): 895–909.Google Scholar
  30. Kets, W., and A.M. Lejour. 2003. Sectoral TFP growth in the OECD, CPB Memorandum 58.Google Scholar
  31. Khanna, M., and C. Crago. 2012. “Measuring Indirect Land Use Change with Biofuels: Implications for Policy”. Annual Review of Resource Economics 2012. 4:161–184.Google Scholar
  32. Kløverpris, J.H., and Steffen M. 2013. “Baseline time accounting: Considering global land use dynamics when estimating the climate impact of indirect land use change caused by biofuels.” The International Journal of Life Cycle Assessment 18(2): 319–330.Google Scholar
  33. Krichene, N. 2002. World crude oil and natural gas: A demand and supply model. Energy Economics 24 (6): 557–576.CrossRefGoogle Scholar
  34. Laborde, D. 2011. “Assessing the Land Use Change Consequences of European Biofuel Policies”. Final Report. ALTASS Consortium.
  35. Lee, H-L., T.W. Hertel, B. Sohngen and N. Ramankutty, 2005. Towards an Integrated Land Use Data Base for Assessing the Potential for Greenhouse Gas Mitigation. GTAP Technical Paper No. 25, Center for Global Trade Analysis, Purdue University, available on line at
  36. Lubowski, R (2002) “Determinants of Land Use Transitions in the United States: Econometrics Analysis of Changes among the Major Land-Use Categories”. PhD Dissertation, Harvard University: Cambridge, MA.Google Scholar
  37. Ludena, C.E., T.W. Hertel, P.V. Preckel, K. Foster and A. Nin. 2006. “Productivity Growth and Convergence in Crop, Ruminant and Non-Ruminant Production: Measurement and Forecasts.” GTAP Working Paper 35. Center for Global Trade Analysis. Purdue University, West Lafayette, IN, USA.Google Scholar
  38. McDougall, R., and A. Golub. 2007. “GTAP-E Release 6: A Revised Energy-Environmental Version of the GTAP Model”, GTAP Research Memorandum No. 15, Center for Global Trade Analysis. Purdue University, West Lafayette, IN, USA.Google Scholar
  39. Muhammad, A., Seale Jr., J. L., Meade, B., and Regmi, A. 2011. International Evidence on Food Consumption Patterns: An Update Using 2005 International Comparison Program Data (Technical Bulletin No. TB-1929). Washington, D.C., USA: Economic Research Service, U.S. Department of Agriculture. Retrieved from
  40. O’Hare, M., R.J. Plevin, J.I. Martin, A.D. Jones, A. Kendall, and E. Hopson. 2009. Proper accounting for time increases crop-based biofuels’ greenhouse gas deficit versus petroleum. Environ Research Letters 4: 024001. doi: 10.1088/1748-9326/4/2/024001.CrossRefGoogle Scholar
  41. Plevin, R.J., H.K. Gibbs, J. Duffy, Y. Sahoko, and S. Yeh. 2014. “Agro-Ecological Zone Emission Factor Model.” GTAP Technical Paper 34. Center for Global Tarde Analysis, Purdue University, West Lafayette, IN.Google Scholar
  42. Searchinger, T., R. Heimlich, R. A. Houghton, F. Dong, A. Elobeid, J. Fabiosa, S. Tokgoz, D. Hayes and T.-H. Yu. 2008. “Use of U.S. Croplands for Biofuels Increases Greenhouse Gases Through Emissions from Land-Use Change.” Science 319: 1238–1240.Google Scholar
  43. Sohngen, B., and R. Mendelsohn, 2007. “A Sensitivity Analysis of Carbon Sequestration”. In Human-Induced Climate Change: An Interdisciplinary Assessment. ed. M. Schlezinger. Cambridge University Press.Google Scholar
  44. Taheripour, F., and W.E. Tyner. 2008. Ethanol policy analysis—What have we learned so far? Choices 23 (3): 6–11.Google Scholar
  45. Taheripour, F., A. Golub, and W. Tyner. 2011a. “Calculation of Indirect Land Use Change (ILUC) Values for Low Carbon Fuel Standard (LCSF) Fuel Pathways.” Interim report prepared for California Air Resource Board.
  46. Taheripour, F., T. Hertel, and W. Tyner. 2011b. Implications of biofuels mandates for the global livestock industry: A computable general equilibrium analysis. Agricultural Economics 42 (3): 325–342.CrossRefGoogle Scholar
  47. Tyner, W., F. Taheripour, Q. Zhuang, D. Birur and U. Baldos. 2010. Land use changes and consequent CO2 emissions due to US corn ethanol production: A comprehensive analysis. Department of Agricultural Economics, Purdue University, IN, USA.Google Scholar
  48. Wise, M.A., J.J. Dooley, P. Luckow, K.V. Calvin, and G.P. Kyle. 2014. Agriculture, land use, energy and carbon emission impacts of global biofuel mandates to mid-century. Applied Energy 114: 763–773. doi: 10.1016/j.apenergy.2013.08.042.CrossRefGoogle Scholar
  49. Wohlgenant, M.K. 1989. Demand in farm output in a complete system of demand functions. American Journal of Agricultural Economics 71 (2): 241–252.CrossRefGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Alla A. Golub
    • 1
    Email author
  • Thomas W. Hertel
    • 1
  • Steven K. Rose
    • 2
  1. 1.Department of Agricultural Economics, Center for Global Trade AnalysisPurdue UniversityWest LafayetteUSA
  2. 2.Electric Power Research InstituteWashingtonUSA

Personalised recommendations