Economic models are widely used for agricultural and energy policy analysis. For biofuels in the United States, the four main models that have been used are the Food and Agricultural Policy Research Institute (FAPRI) model, the Forest and Agricultural Sector Optimization (FASOM) model, the Global Trade Analysis Project (GTAP) model, and the Policy Analysis System (POLYSYS) model. FAPRI has been developed by Iowa State University and the University of Missouri. FASOM has had many contributors over the years, but development currently is managed by Texas A&M University. GTAP is led by Purdue University and POLYSYS by the University of Tennessee. Each model is large and complicated and has unique strengths and weaknesses. This section provides a general summary of each model.
SUMMARY OF ECONOMIC MODELS
Three of the models (FAPRI, FASOM, and POLYSYS) are partial-equilibrium (PE) models, which means that not all sectors of the economy are included in the model. These PE models focus on the agricultural sector with limited account of other sectors through exogenous information. General-equilibrium (GE) models, such as GTAP, provide coverage of all sectors of the economy, although at a much more aggregate level. GTAP also covers all regions of the world. Thus, GE models capture the interactions among sectors and between product and factor markets. However, GE models, especially global ones like GTAP, cannot model the interactions among detailed sectors of agriculture or regions as PE models can. For many questions, PE models that concentrate on one or a few sectors are appropriate for responding to policy questions regarding the sector(s) of interest. PE models generally are richer in detail regarding cropping practices, land quality and use, and regional variations, and they can permit more in-depth analysis of sector-specific policies. However, the models implicitly assume that what goes on in the agricultural sector will not have a large effect on the rest of the economy and vice versa (that is, the agricultural sector can be analyzed without worrying explicitly about what happens in the rest of the economy).
Forward-looking models assume perfect knowledge of the future; recursive dynamic models assume agents are myopic and operate as if current prices will continue into the future. FASOM is a forward-looking model and solves all years simultaneously, whereas FAPRI and POLYSYS are recursive dynamic models. GTAP can be run either as a comparative static or dynamic model. Comparative static models compute the market equilibrium under one set of conditions; when conditions change, the models compute the new equilibrium without worrying about the path from one equilibrium to the other. The comparative static solution does not have a particular time reference, although it is generally characterized as medium term or about eight years.1
The three PE models originally had a heavy focus on agricultural policy, although FASOM was designed to examine competition between forestry and agricultural sectors for land from its early stages. GTAP originally was developed to evaluate the effects of alternative trade policies in international trade negotiations and regional and bilateral trade agreements. Thus, GTAP is more heavily focused on the trade dimension. Specific details of each model follow.
FAPRI is a model of the U.S. agricultural sector, with extensions for the rest of world, designed originally for agricultural policy analysis. The model has been supported by congressional appropriations and is heavily used in providing information to congressional staffers on questions related to the Farm Bill. The FAPRI baseline—projections for the next decade—is used for policy and general outlook work by many others. In fact, the FAPRI baseline is used to help develop the POLYSYS baseline. The U.S. Department of Agriculture Economic Research Service uses the FAPRI baseline for some of their analysis. The model covers all the major U.S. agricultural crops and livestock sectors. It pays strong attention to detailed policy representation. It accounts for cropland use (as well as pasture for the United States and Brazil) and agricultural trade data (especially for the United States), but treats other macroeconomic effects as exogenous inputs to the model. International trade is included with the rest of world divided into regions. Trade adjustment is accounted for directly through supply and demand shifts with no consideration for traditional trade patterns. In other words, it adopts the Heckscher-Ohlin assumption that domestic and imported goods are identical. There are both deterministic and stochastic versions of FAPRI.
Before 1996, FASOM was an agricultural sector model, but it was modified in the mid-1990s to include the forestry sector. Since that time the model has been under continuous development. It presently includes detailed regional representation for cropland, pasture, and forestland for the United States. It is connected to the rest of the world by a relatively simple excess supply and demand structure. FASOM has often been used for environmental and greenhouse-gas (GHG) analyses; it was the primary model used by the U.S.
1 The biofuel modeling done by Purdue University to date has been done with the comparative static version of the model. However, others (for example, Massachusetts Institute of Technology, using the Emissions Prediction Policy Analysis model) have used the GTAP database as part of a recursive dynamic simulation model that runs for 100 years or more.
Environmental Protection Agency (EPA) to determine GHG reductions from various biofuel pathways. As indicated above, FASOM is the only one of the models that looks forward and solves all years simultaneously.
GTAP is both a database and a modeling framework. The GTAP database can be used with other models, and the basic GTAP model can be adapted to particular questions of interest. GTAP adopts the Armington approach to international trade, which means that domestic and imported goods are differentiated. Changes in the structure of international trade are less pronounced than for models with the Heckscher-Ohlin assumption of homogeneous goods. There are 57 sectors plus 3 biofuel sectors in the standard GTAP database. However, most research is done with far fewer regions and sectors. Aggregation tools are available to permit users to specify whatever regional and sector aggregation they prefer. Global land is divided into 18 agroecological zones, and land covers of cropland, pasture, and forest are included. GTAP simulations (using the comparative static approach) essentially estimate the global economic effects from whatever policy or technology shock is of interest. For example, GTAP has been used to estimate the effects of a 15-billion gallon mandate for corn-grain ethanol. To do so, the results of the baseline model run are compared to the results of introducing a shock into the model that requires 15 billion gallons of corn-grain ethanol be produced to satisfy the Renewable Fuel Standard as amended under the Energy Security and Independence Act of 2007 (RFS2) while holding other demands and requirements constant. The results of these two model runs are then compared with respect to corn price, corn exports and imports, other agricultural prices, land-use change, and other relevant economic variables.
POLYSYS includes eight U.S. crops (corn, sorghum, barley, oats, cotton, rice, wheat, and soybean) and seven livestock sectors (beef, pork, turkeys, broilers, eggs, lamb and mutton, and dairy). The model divides the United States into 305 crop-reporting districts; its current version is able to analyze county-level effects if needed. The POLYSYS simulations are anchored to USDA’s published crop-projection baseline, and the simulations provide deviations from that baseline for the shock of interest. Crop and livestock supply is regionally generated, and demand is handled through a system of simultaneous equations. POLYSYS also tracks farm income, government payments, and several environmental variables. For environmental variables, POLYSYS interacts with the Environmental Policy Integrated Climate (EPIC) model (Williams et al., 1990, p. 18). The model can be and commonly is run stochastically to capture the effects of uncertainty and nonlinearities in some of the functions. In recent years, POLYSYS has been modified to include crop residues and dedicated energy crops as biomass feedstock supply options.
LAND COVER IN ECONOMIC MODELS
The models differ in the extent to which types of cover are included. GTAP and FASOM have forestland, pasture, and cropland, although it is predominantly only U.S. land in FASOM. POLYSYS includes cropland and pasture, but not forestland at present, although it may be added in the near future. FAPRI has cropland and pasture for the United States and Brazil but not forestland.
INCORPORATING BIOFUELS INTO ECONOMIC MODELS
All four models were developed before the implementation of RFS2, but each has been modified in recent years to include varying degrees of biofuel coverage. FAPRI and GTAP include only first-generation biofuels (corn-grain ethanol, sugarcane ethanol, and oilseed-based biodiesel). The institutions that run these models plan to expand the database to include second-generation biofuels, and in recent years, FAPRI has increased the level of detail of its representation of Brazil to account for changes due to biofuels. FASOM and POLYSYS include second-generation biofuels from cellulosic feedstocks presently used. FASOM is the only model of the four to include electricity generation from cellulosic feedstocks. Incorporating biofuels into the models is complex. The difficulty of using the models for projections of biofuel feedstock production centers around three areas of insufficient detail.
CAPTURING WORLD MARKET EFFECTS VERSUS AGRICULTURAL PRODUCTION DETAILS
Whether global trade interactions and linkages with other sectors are needed is largely an empirical question. Both GE and PE models have advantages and disadvantages. FAPRI, FASOM, and POLYSYS enter some macro-variables exogenously and consider world trade linkages and flows. The comparative static version of GTAP does not project changes over time; rather, it compares the situation at two points in time given whatever shock has been applied to the model. The PE models normally simulate through time and compare the results with and without a given shock to a predetermined baseline.
CELLULOSIC BIOMASS NOT INCLUDED IN MOST MODELS
Cellulosic biomass crops, including crop residues from grain crops, perennial grasses, bagasse from sugarcane, and woody crops and residues, are being considered as a source of feedstock for liquid transportation fuels. The production and cost estimates that exist vary widely over time, space, and studies. Of the four models being discussed, FASOM includes woody biomass and POLYSYS includes cellulosic biomass crops and woody biomass. GTAP is in the process of adding cellulosic biomass, and FAPRI is in process of including cellulosic crop residue and switchgrass.
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