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Regional Modeling and Linking Sector Models with CGE Models

Regional Modeling and Linking Sector Models with CGE Models. Presented by Martin T. Ross Environmental and Natural Resource Economics Program RTI International at Third Forestry and Agriculture Greenhouse Gas Modeling Forum October 12-15, 2004 Shepherdstown, WV.

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Regional Modeling and Linking Sector Models with CGE Models

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  1. Regional Modeling and Linking Sector Models with CGE Models Presented byMartin T. Ross Environmental and Natural Resource Economics Program RTI International at Third Forestry and Agriculture Greenhouse Gas Modeling Forum October 12-15, 2004 Shepherdstown, WV

  2. Overview of Presentation • Uses of Computable General Equilibrium (CGE) Models • Overview of ADAGE Model • Issues Associated with Regional Modeling • Linkages with Detailed Sector Models • Electricity Dispatch Models • Agriculture and Forestry Models • Difficult Issues and CGE Data Requirements

  3. Uses of CGE Models • Combine Economic Theory and Empirical Data to Cover All Aspects of Economic Behavior • Broad Representation of Technologies • CGE Models can’t Incorporate All Features of Agriculture/Forestry Models • Uses Include: • Macroeconomic policy effects • Interactions of agriculture/forestry and energy • Leakage issues • Provide information to detailed sector models

  4. Overview of ADAGE Model(Applied Dynamic Analysis of the Global Economy) • Dynamic, Intertemporally-Optimizing Model • Rational consumers with foresight who maximize utility • Typically has around 5 regions and 10-15 industries • Solves in 5-year intervals (2005 to 2050/2075) • Production Structures • Nested CES functions and associated elasticities • Other than electricity, based on MIT model structure • Baseline Uses EIA’s AEO & IEO Energy Forecasts • Carbon Dioxide Emissions Tied to Fuel Use in BTUs • Non-CO2 Emissions (CH4, N2O, HFC, PFC, SF6) • MIT approach (endogenous modeling, input to sectors) • EPA forecasts by gas and sector

  5. Overview of ADAGE Model

  6. General Issues of Regional CGE Modeling • Establishing Interstate Trade Patterns • Commodity Flow Survey data • Gravity Trade: trade = f(income,distance) • Modeling Trade in Goods • Armington (goods are differentiated by source) • Homogeneous, or identical, goods • Estimation of State-Level Results • Regional model of US => results to states • Model single state and surrounding regions

  7. General Issues of Regional CGE Modeling • Feasible Changes in Production • Electricity generation – e.g., total potential wind or biomass, penetration rate of new technology • Land use and values, also potential crops • Constraints on Electricity Flows • IPM data on transmission links • EIA data on congestion points in system

  8. Linkages with Sector Models: Policy Modeling • GHG Policy Modeling • Carbon – emissions tied to fuel use • Look at heatrate (BTU/kWh) and how fast technology change occurs • Other Types of Emissions Policies (SO2, NOx) • No direct link between fuel use and emissions • Fuel switching & retrofits to reduce emissions (options and costs are unit specific) • Link to detailed electricity dispatch model

  9. Approaches to Linking Models(CGE & Electricity Sector Models) • Indirect Linkage • Use sector model’s cost estimates, let CGE model structure determine changes in electricity prices, fuel use, etc. • Direct Linkage • Force CGE model to replicate other results (electricity price, coal/gas use and prices) • Removal of Electricity Sector in CGE Model • Rely on detailed model for all electricity results • Need iterative solves passed between models to reach a consistent equilibrium

  10. Links with Ag/Forestry Models • Response Functions (McCarl/Sands work with ASM/FASOM & SGM) • Express Relationship among Sequestration, Afforestation, Biofuels and Carbon Prices • Repeated Simulations of Ag/Forestry Models • Carbon and fuel prices • Commodity demands • Trade flows, etc. • Incorporate in Relationship in CGE Model

  11. Links with Ag/Forestry Models • Endogenize Land Reactions in CGE Model (GTAP, FARM, MiniCAM/AgLU, MIT, GTEM) • GOAL: represent broad reactions of ag/forest sectors in CGE model, if not the details • Land is input to production • GTAP and EPA development of data by AEZ • Allows modeling of competition for land among uses and shifts in rental values • Need ag/forestry sector results to inform CGE model structure * Differences between Static and Dynamic Models

  12. Endogenizing Land in CGE Models

  13. Difficult Issues With Endogenous Modeling • How to Model Land • Land rents – flow variable (from data) • Land stocks – tied to carbon levels • Past Land Uses • Implications for carbon stocks (Tracking multiple land stocks, similar to capital?) • Rising Marginal Costs of Land Conversion • Technology parameter changes • Decreasing returns to scale through fixed input

  14. Dynamic Issues of Land Modeling • “Saturation” and Impermanence • Management Intensity and Rotations • Harvesting Decisions • Long-term Reactions Depend on Foresight • Used by sector models like FASOM and TSM • Without foresight, may be difficult for agents in a CGE model to consider these dynamic issues when adjusting behaviors

  15. Links with Ag/Forestry Models • Direct Links to Ag/Forestry Models (Sohngen/Mendelsohn and DICE/RICE model) • Coordinate Baselines and Reactions • Pass Information between Models • GHG permit price • Land rental values • Energy consumption and prices • Demand for ag/forestry products by industries and households accounting for changes in prices and income

  16. Data Requirements • Current Land Rents by Crop and Region • Current Acres by Crop and Region (Probably have to estimate state shares) • Baseline Estimates of Future Changes • Crop production, rents, acres • Urbanization • Costs, Conversion Emissions, Feasible Land Transformations and Output, and Sequestration Potential

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