1. Land Use Change in Brazil: A macro-regional perspective Andrea Cattaneo Seminar presented at: Center for International Development January 30, 2003

2. Overview Briefly discuss the issue of scale Potential issues/drivers linked to land use change in Brazil Entry points to discuss economy-environment links Compare the order of magnitude of impact on deforestation of a subset of “drivers” of land use change

3. Choosing the Appropriate Scale Key theme to modeling across scale: The relationship between what we see and the scale at which we measure it. Leaf Branch Tree Forest New properties emerge when data are aggregated: Operational scale - the scale at which a process operates different research questions require different scales of measurement In fact, many models are scale dependent

4. Brazil: A Multi-Regional Approach Issues u u Crisis of Brazilian Currency u u Subsidies & Taxes u u Reduction in Amazon transportation costs u u Tenure Regimes u u Technological Innovation Method u u Regional CGE model for Brazil

5. Producers ProductMarkets FactorMarkets Institutions FactorCosts Wages & Rents Demand for Intermediate Inputs SalesRevenues Final Demand Waste Sink Amenities Energy + Materials Land/Water ? ? Economy-Environment Links

6. Regional Disaggregation of Model

7. Structural Model Characteristics Detailed representation of regional agricultural technologies: small and large farms Segmented capital markets Model allows for excess supply in factor markets Econometrically estimated migration functions

8. Structural Model… (continued) Regional trade and transportation margins Deforestation Sector: produces arable land Biophysical processes affect land use

9. Process/DriverScenarioSub-cases% change in deforestation Tenure Regimes in Amazon Remove speculative incentives to deforest -23% Technological ChangeInnovation in agriculture: 1985-1995 Amazon Innovation +48% Extra-Amazon-27% Combined effect +2% Transportation Costs 20% reduction in costs for Amazon products +40% Currency Devaluation 40% Real devaluation Capital flight+15% Balanced Contraction -15% Global externality considerations Subsidize conservation R$1.21 per carbon ton of reduced emissions -30% Tax deforestationtax of R$0.25 per carbon ton emitted -43%Scale Amazon Inter- regional National International

10. South/SE 22% Productivity Improvements in Brazilian Agriculture (1985-1995) Northeast 24% Legal Amazon 30% Center- West 54%

11. Process/DriverScenarioSub-cases% change in deforestation Tenure Regimes in Amazon Remove speculative incentives to deforest -23% Technological ChangeInnovation in agriculture: 1985-1995 Amazon Innovation +48% Extra-Amazon-27% Combined effect +2% Transportation Costs 20% reduction in costs for Amazon products +40% Currency Devaluation 40% Real devaluation Capital flight+15% Balanced Contraction -15% Global externality considerations Subsidize conservation R$1.21 per carbon ton of reduced emissions -30% Tax deforestationtax of R$0.25 per carbon ton -43% Scale Amazon Inter- regional National International

12. Innovation and Agronomic Sustainability in the Amazon: stock effects vs. expectation effects Sustainability improvements: annuals or livestock? u uannuals decrease deforestation, livestock increases deforestation Productivity improvements increase deforestation Increasing sustainability

13. Strengths of the “macro” approach… The structure of the model allows for multiple land use change mechanismsThe structure of the model allows for multiple land use change mechanisms A lot of structural information is readily available:A lot of structural information is readily available: u economic accounting constraints u factor intensities u Survey data: ag census, production, household, labor statistics The economic structure can be linked to environmental processesThe economic structure can be linked to environmental processes

14. … and the inevitable weaknesses Uncertainty about parameters: rarely estimated econometricallyUncertainty about parameters: rarely estimated econometrically Lack of spatial detail is a drawback if environmental variables are heterogeneous over spaceLack of spatial detail is a drawback if environmental variables are heterogeneous over space Requires a lot of effort to build a good model: no easy off-the-shelf answers to difficult questions.Requires a lot of effort to build a good model: no easy off-the-shelf answers to difficult questions.