Land Use Change in Computable General Equilibrium Models
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Presentation of Joaquim Bento Ferreira for the "2nd Workshop on the Impact of New Technologies on the Sustainability of the Sugarcane/Bioethanol Production Cycle"...

Presentation of Joaquim Bento Ferreira for the "2nd Workshop on the Impact of New Technologies on the Sustainability of the Sugarcane/Bioethanol Production Cycle"

Apresentação de Joaquim Bento Ferreira realizada no "2nd Workshop on the Impact of New Technologies on the Sustainability of the Sugarcane/Bioethanol Production Cycle "

Date / Data : Novr 11th - 12th 2009/
11 e 12 de novembro de 2009
Place / Local: CTBE, Campinas, Brazil
Event Website / Website do evento: http://www.bioetanol.org.br/workshop5

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Land Use Change in Computable General Equilibrium Models Presentation Transcript

  • 1. Land Use Change in Computable General Equilibrium Models Joaquim Bento de Souza Ferreira Filho Escola Superior de Agricultura “Luiz de Queiroz” Universidade de São Paulo1
  • 2. Plan of presentation   Computable Equilibrium (CGE) Models in the evolution of applied economic models.   Illustrate the main applications and uses of CGE models.   Point to the main drivers of CGE models.   Show how CGE models treat Land Use Change   Point to the new directions and developments.2
  • 3. CGE models   The most recent development in a long tradition of economic multi-sector economic planning models   Initiated with the work of Leontief in the 30’s: Input-Output (IO) analysis.   Used when the complex interactions between economic variables must be taken into account for policy analysis.3
  • 4. IO table for Brazil – 2005 – MAKE MATRIX4
  • 5. IO table for Brazil – 2005 - USE5
  • 6. Input-Output models (IO)   Consists of explicitly modeling the inter-industry (or users) flows of products in an economy.   n linear equations, n unknowns. System solved by matrix inversion.   Solution: inputs requirements to satisfy a given vector of final demands.   General equilibrium in the production side of a economy.   Does not take into account restrictions about production capacity: a solution always exists.   Fix price models, no substitution in inputs space in production.6
  • 7. Linear Programming Models   Have an explicit objective function for optimization purposes: introduce choices.   Allow inequality restrictions (non used capacity).   Explicitly model maximum capacity.   Generate a dual price system, which represents the opportunity cost of any production factor (market prices).   Problem: cannot treat prices endogenously. Resource allocation in production is not compatible with income generated in the process. Prices does not change in response to resource scarcity or excess supply.7
  • 8. Computable General Equilibrium Models   Simultaneous solution for prices and quantities.   Simulates the interaction of many agents with optimizing behavior in the markets.   Explicitly model structural features of particular economies, with complete specification both from the supply and demand sides.   REPRODUCE THE CIRCULAR FLOW OF INCOME IN A GIVEN ECONOMY: incomes generated in the production side must be consistent with expenditures of agents.   First CGE model: 1960, Norwegian economy, Leif Johansen.8
  • 9. Equilibrium models   Equilibrium models solve a set of nonlinear equations that include market clearing conditions, efficiency or zero-profit conditions, and income balance equations.   Equations are paired with unknowns such as:   market prices   levels of output by production activity   Expenditures and savings, etc.9
  • 10. CGE models   Very data demanding models.   The IO matrix gives a large part of the information required, but not all.   Remaining information: National Accounts, Economic Censuses, Household Surveys, etc.   Circular flow and consistency: data organized in a Social Accounting Matrix (SAM). Double-keeping accounting method.   The model is calibrated based on one year picture of a given economy.10
  • 11. Real flows Money flows An illustrative SAM Primary Factors Institutions Produts Labor Capital Capital Stocks Rest of TOTAL Activities (Land) Household Governme Account the World Activities Domestic Exports Domestic Supply Productio n Value Produts Intermed. Househ Governme Investimen Stocks Supply in use Consump Consumpt the Domestic Market Factors Labor wages Labor Income Capital rents Capital (Land) Income Institution Household Wages Rents Transfers Household Income Governm Indirect Tariffs Direct Capital Governme taxes taxes nt Income Capital Savings Savings Capital Savings Account Stocks Stocks Stocks Rest of Imports Capital Income the World from Overseas Domestic Supply in Labor Capital Household Governme Capital Stocks Payments TOTAL Productio the Income Income Expenditu nt Account to11 n Value Domestic res Expenditu Overseas Market res
  • 12. Partial equilibrium analysis Demand Supply Primary Factors Institutions Produts Labor Capital Capital Stocks Rest of TOTAL Activities (Land) Household Governme Account the World Activities Domestic Exports Domestic Supply Productio n Value Produts Intermed. Househ Governme Investimen Stocks Supply in use Consump Consumpt the Domestic Market Factors Labor wages Labor Income Capital rents Capital (Land) Income Institution Household Wages Rents Transfers Household Income Governm Indirect Tariffs Direct Capital Governme taxes taxes nt Income Capital Savings Savings Capital Savings Account Stocks Stocks Stocks Rest of Imports Capital Income the World from Overseas Domestic Supply in Labor Capital Household Governme Capital Stocks Payments TOTAL Productio the Income Income Expenditu nt Account to12 n Value Domestic res Expenditu Overseas Market res
  • 13. How is land treated in these models?   Land is a primary factor of production, like labor and capital (and perhaps natural resources).   It’s a factor which limits the supply response of the economy.   In the SAM the amount of land is represented by it’s payments as a factor of production (or rentals), just like capital. Actually, land rentals must be disaggregated from capital rentals (Gross Operational Surplus in agricultural activities) in the National Accounts.   Two general formulations: labor demand and labor supply.13
  • 14. 14
  • 15. The Constant Elasticity of Transformation Production Frontier Land for corn Total land availability frontier Curvature of the frontier: easiness of land movement Relative prices Psoy/Pcorn15 Land for soybeans
  • 16. So, in a CGE model we have   A complete specification of the demand side of the economy;   A complete specification of the supply side of the economy;   CGE models: have the ability to capture the indirect land use effect caused by policies in a integrated framework:   For example, how the fall in trade barriers in USA would affect land use in Mato Grosso?   Partial equilibrium models, on the other hand, model spatial and land management in great detail, since the rest of the economy is not taken into account.16
  • 17. What about details in CGE models?   Increasing computer power capacity turned it possible to work even at a very fine grid cell level, watersheds or Agro Ecological Zone (AEZ), for example.   However, the level detail on data is the limitation: modeling at sub-national level requires estimation of input usage and production by spatial unit. We typically have it at national level (IO tables).   There are many different solutions in the literature, which is in the frontier of CGE modeling, linked now to the climate change literature.   A host of new issues arises from detailed land representation.17
  • 18. Mobility of land across uses at sub- national level grid   Why farms do not specialize if land is homogeneous?   Farms are often diversified. Two main considerations:   Risk aversion (not a market level phenomenon).   Non-homogenous land, even at very fine grid level. Some activities on hills and others on valleys, for example. Substitution not easy.   One possible solution: again, the CET framework with particular values for the elasticity of substitution at sub-national level.   In any case, the land supply function is nested, with decisions at different levels: first, decide how many land allocate for particular crops, than distribute this total at sub-national level.   Thousands of units of analysis? Size wouldn’t be the problem, but data…..18
  • 19. What about GHG emissions?   Once the economy is modeled the emissions tracking is straightforward.   Emissions either linked to:   Use of products (fuels, for example)   Level of activity of producing sectors (CH4 in livestock, for example).19
  • 20. And what about deforestation?   A major challenge in modeling, still immature.   CGE models are good for phenomena which are guided by prices.   This is not the case of deforestation as we know it in Brazil.   A range of non-market variables, like poorly defined property rights in Amazon and roads constructions, for example, have a determinant impact on deforestation.   There are attempts to link CGE models with specific forestry models. Forestry involve investment decisions, inter- temporal.   This is an issue difficult enough even in partial equilibrium.20
  • 21. 25 An illustration: ethanol export expansion in Brazil201510 Series1 5 0-5-10 21
  • 22. An illustration: distributive and poverty effects22
  • 23. Directions for future research in CGE and LUC in Brazil   Develop a CGE model of land use with the actual modeling technology: increase land use representation at sub-national level.   Presently models work at state (27 regions) level.   Work on estimation of parameters for this detailed land use model: elasticity of substitution between activities:   Initially by region   Maybe at sub-national unit level?   Integration with the general equilibrium framework.23
  • 24. Thank you   Email: jbsferre@esalq.usp.br24