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Land Use Modeling in Recursively-Dynamic GTAP Framework

Author

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  • Golub, Alla
  • Hertel, Thomas
  • Sohngen, Brent

Abstract

*Chapter 10 of the forthcoming book "Economic Analysis of Land Use in Global Climate Change Policy," edited by Thomas W. Hertel, Steven Rose, and Richard S.J. Tol. The goal of this work is to investigate land-use change at the global scale over the long run - particularly in the context of analyzing the fundamental drivers behind land-use related GHG emissions. For this purpose, we identify the most important drivers of supply and demand for land. On the demand side, we begin with a dynamic general equilibrium (GE) model that predicts economic growth in each region of the world, based on exogenous projections of population, skilled and unskilled labor and technical change. Economy-wide growth is, in turn, translated into consumer demand for specific products using an econometrically estimated, international cross-section, demand system that permits us to predict the pattern of future consumer demands across the development spectrum. This is particularly important in the fast-growing, developing countries, where the composition of consumer demand is changing rapidly. These countries also account for an increasing share of global economic growth and greenhouse gas emissions. Consumer demand is translated into derived demands for land through a set of sectoral production functions that differentiate the demand for land by Agro-Ecological Zone (AEZ).

Suggested Citation

  • Golub, Alla & Hertel, Thomas & Sohngen, Brent, 2008. "Land Use Modeling in Recursively-Dynamic GTAP Framework," GTAP Working Papers 2609, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University.
  • Handle: RePEc:gta:workpp:2609
    Note: GTAP Working Paper No. 48
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    File URL: https://www.gtap.agecon.purdue.edu/resources/res_display.asp?RecordID=2609
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    Citations

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    Cited by:

    1. Ruslana Rachel PALATNIK, 2008. "Climate Change Assessment and Agriculture in General Equilibrium Models: Alternative Modeling Strategies," EcoMod2008 23800101, EcoMod.
    2. Taran Faehn & Gabriel Bachner & Robert Beach & Jean Chateau & Shinichiro Fujimori & Madanmohan Ghosh & Meriem Hamdi-Cherif & Elisa Lanzi & Sergey Paltsev & Toon Vandyck & Bruno Cunha & Rafael Garaffa , 2020. "Capturing Key Energy and Emission Trends in CGE models: Assessment of Status and Remaining Challenges," Journal of Global Economic Analysis, Center for Global Trade Analysis, Department of Agricultural Economics, Purdue University, vol. 5(1), pages 196-272, June.
    3. Lima, José E. Durán & Ludeña, Carlos & Alvarez, Mariano & de Miguel, Carlos J., 2009. "Central American - European Union Association Agreement: Assessment using General and Partial Equilibrium," Conference papers 331857, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    4. Hertel, Thomas, 2013. "Global Applied General Equilibrium Analysis Using the Global Trade Analysis Project Framework," Handbook of Computable General Equilibrium Modeling, in: Peter B. Dixon & Dale Jorgenson (ed.), Handbook of Computable General Equilibrium Modeling, edition 1, volume 1, chapter 0, pages 815-876, Elsevier.
    5. Tian, Xiaohui & Sohngen, Brent & Sands, Ronald, 2013. "Modeling a Dynamic Forest Sector in a General Equilibrium Framework," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149990, Agricultural and Applied Economics Association.
    6. Antoine BOUËT & HUGO VALIN & Betina DIMARANAN, 2009. "Biofuels in the world markets: A Computable General Equilibrium assessment of environmental costs related to land use changes," Working Papers 6, CATT - UPPA - Université de Pau et des Pays de l'Adour, revised Nov 2009.
    7. Ujjayant Chakravorty & Marie‐Hélène Hubert & Beyza Ural Marchand, 2019. "Food for fuel: The effect of the US biofuel mandate on poverty in India," Quantitative Economics, Econometric Society, vol. 10(3), pages 1153-1193, July.
    8. Thierry Brunelle & Patrice Dumas, 2012. "Can Numerical Models Estimate Indirect Land-use Change?," Working Papers 2012.65, Fondazione Eni Enrico Mattei.
    9. Meiyappan, Prasanth & Dalton, Michael & O’Neill, Brian C. & Jain, Atul K., 2014. "Spatial modeling of agricultural land use change at global scale," Ecological Modelling, Elsevier, vol. 291(C), pages 152-174.
    10. Jevgenijs Steinbuks & Thomas Hertel, 2016. "Confronting the Food–Energy–Environment Trilemma: Global Land Use in the Long Run," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 63(3), pages 545-570, March.
    11. Hugo Valin & Betina Dimaranan & Antoine Bouet, 2009. "Biofuels in the world markets: A Computable General Equilibrium assessment of environmental costs related to land use changes," Working Papers hal-03550775, HAL.
    12. Panichelli, Luis & Gnansounou, Edgard, 2015. "Impact of agricultural-based biofuel production on greenhouse gas emissions from land-use change: Key modelling choices," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 344-360.
    13. Michetti, Melania & Parrado, Ramiro, 2012. "Improving Land-use modelling within CGE to assess Forest-based Mitigation Potential and Costs," Climate Change and Sustainable Development 122862, Fondazione Eni Enrico Mattei (FEEM).
    14. F. Souty & T. Brunelle & P. Dumas & B. Dorin, & P. Ciais & R. Crassous, 2012. "The Nexus Land-Use Model, an Approach Articulating Biophysical Potentials and Economic Dynamics to Model Competition for Land-Uses," Working Papers 2012.16, Fondazione Eni Enrico Mattei.
    15. Calzadilla, Alvaro & Delzeit, Ruth & Klepper, Gernot, 2014. "DART-BIO: Modelling the interplay of food, feed and fuels in a global CGE model," Kiel Working Papers 1896, Kiel Institute for the World Economy (IfW Kiel).
    16. Ujjayant Chakravorty & Marie-Hélène Hubert & Michel Moreaux & Linda Nøstbakken, 2012. "Do Biofuel Mandates Raise Food Prices?," Economics Working Paper Archive (University of Rennes 1 & University of Caen) 201214, Center for Research in Economics and Management (CREM), University of Rennes 1, University of Caen and CNRS.
    17. Onno Kuik, 2014. "REDD+ and international leakage via food and timber markets: a CGE analysis," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 19(6), pages 641-655, August.
    18. Melania Michetti & Matteo Zampieri, 2014. "Climate–Human–Land Interactions: A Review of Major Modelling Approaches," Land, MDPI, vol. 3(3), pages 1-41, July.
    19. Ruslana Palatnik & Roberto Roson, 2012. "Climate change and agriculture in computable general equilibrium models: alternative modeling strategies and data needs," Climatic Change, Springer, vol. 112(3), pages 1085-1100, June.

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