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Model Comparison Subgroup. July 15, 2010. Comparison to CBO scoring. CBO need to know effects of the ‘policy’ Marginal effects of policy implementation Baseline important in determining effects of policy implementation. We are tasked with scoring fuels, not policy effects
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Model Comparison Subgroup July 15, 2010
Comparison to CBO scoring • CBO need to know effects of the ‘policy’ • Marginal effects of policy implementation • Baseline important in determining effects of policy implementation. • We are tasked with scoring fuels, not policy effects • Average effects over a large volume change in fuel type produced • Marginal effect may be quite different than the average • Can not know if LCFS reduces US GHG CARB reasserts that the objective of the expert working group is to score the fuels, taking an average of the impact of some volume of exogenously increased biofuel production. This is not an analysis of the policy effects but the scoring of the fuel necessary to implement the policy.
Models Evolve • Models not static, expand to address the questions of the day. • All have grown to include some representation of biofuels • Many have grown to include more classes of land • Many have added direct calculations of GHG emissions • While some models more ‘public’ than others, most defy casual use in the analysis of policy.
General Equilibrium (GE) Partial Equilibrium (PE) Sector(s) specific: Agriculture and biofuel Product differentiation (Palm oil, corn, wheat) World market clearing Detailed policy Dynamic year to year changes Problematic question: Effects on labor costs? Change in transport costs? • Economy wide representation • Product aggregates (coarse grains vegetable oils) • Armington bilateral trade • Stylized policy • Increments: one long run equilibrium to the next. • Problematic questions: • Where is the blend wall? • Path to equilibrium? *Generalizations, each model has unique features, coverage and emphasis
GTAPVersion 6 • GTAP @ Purdue University • Publicly available many users • 87 GTAP regions (aggregated to 19), by 19 AEZ • Crops (broad categories), pasture, forest • GHG calculations (GTAP-E) • One off future period (long run equilibrium) • Biofuel coverage (GTAP-E) first generation liquid biofuels
LEI-TAP • An elaboration of GTAP with the following features (and others) • More detailed agriculture policy representation • Land supply curve • Linkage to biophysical model (yields and feed conversion)
MIRAGEmodeling international relationships in applied general equilibrium • Created at CEPII, modified at IFPRI • Utilizes the GTAP 7 database, coverage defined similarly? • Incorporates ethanol and biodiesel (first generation liquid biofuels) sectors and some disaggregation of feedstocks. • Increased detail on crop production and intensification • Broad land use catagories • Includes biofuel co-product accounting
EPPAemissions predictions policy analysis • Created at MIT • Utilizes GTAP database • Augmented to include data on emissions of GHG, aerosols, etc
IMPACT modelInternational Model for Policy analysis of Agricultural Policies and Trade • IFPRI, International Food Policy Research Institute • World Bank, UN, USAID, etc. • 115 reported regions • 30 crop and livestock-fish categories • Base period, solution to 2050 • 1st generation liquid biofuels, implicit 2nd generation production after 2025 • Emphasis on food security and resource availability • Includes modules for water use and calorie/nutrition effects
Aglink-COSIMO • OECD in Paris and UN-FAO Rome • OECD, UN-FAO, DG-AGRI, AG Canada • ~ 40 countries and regions. • Primary annual crops, palm, sugar, livestock, dairy, fish. • Some country areas done as a ‘system’. • No pasture or other land uses explicit • No endogenous GHG calculations • Base period ~10 years • Includes first generation liquid biofuels across select developed and developing countries. • Attention to policy representation • Two organizations (OECD CN, RU, BR )
FAPRI modelFood and Agricultural Policy Research Institute • FAPRI: University of Missouri and Iowa State University • Limited user base • US Congress, policy makers • World in country and regional aggregates • Primary annual crop land, palm and sugar in major producing/consuming countries and CRP explicit. Livestock and dairy • US area done as a system, world area done with own price and select cross prices. • Model extension for calculating GHG. • Base period 10 years extended to 15 and 20 years for various analysis. • Includes first generation liquid biofuels (US and world), second generation liquid biofuels (US) and simple biomass for electrical generation (US). • Strong attention to policy representation 1 U.S. and Brazil have sub-country regions 2 Brazil includes additional land types
CAPRI modelCommon Agricultural Policy Regionalized Impact • University of Bonn • DG-AGRI, EU commission • EU27, Norway, Balkans: Sub country land grids-combined with world trade model response. • Currently treats arable and grass lands as fixed quantities (with changes in fallow and intensity) • Includes GHG calculations • Base Period: ~10 years • Includes first generation liquid biofuels • EU focused with additional details on farm level effects.
Other models of note • GLOBIOM • FAPRI-MU stochastic model • US with world reduced forms, distributional analysis • FASOM Texas A&M • Broad land use categories for regions of the US. • FAPRI-MU DOE model • Detailed crop use and broad land use categories, linked to US stochastic model
Dealing with uncertainty • How do the models deal with uncertainty • In exogenous factors • In model parameters • In ‘equation errors’ or calibration values
http://ftp.jrc.es/EURdoc/JRC42597.pdf • http://www.ifpri.org/publication/international-model-policy-analysis-agricultural-commodities-and-trade-impact-0 • http://www.agri-outlook.org/document/13/0,3343,en_36774715_36775671_40082829_1_1_1_1,00.html • http://www.cepii.fr/anglaisgraph/workpap/pdf/2002/wp02-17.pdf • Unreleased JRC document comparing many of the models listed here.