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J
Economic Models Used to
Assess the Effects of Biofuel
Production in the United States
E
conomic 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) mod-
els, 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 exog-
enous 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).
337
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338 APPENDIX J
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 compara-
tive static or dynamic model. Comparative static models compute the market equilibrium
under one set of conditions; when conditions change, the models compute the new equilib-
rium 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 character-
ized 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 al-
ternative 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
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 congres-
sional 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 analy-
sis. 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 adjust-
ment 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 sto-
chastic versions of FAPRI.
FASOM
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 environ-
mental 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.
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339
APPENDIX J
Environmental Protection Agency (EPA) to determine GHG reductions from various bio-
fuel pathways. As indicated above, FASOM is the only one of the models that looks forward
and solves all years simultaneously.
GTAP
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 homo-
geneous 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) es-
sentially 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 com-
pared 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
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 cur-
rent 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 de-
viations 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 func-
tions. 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.
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340 APPENDIX J
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 data-
base 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 insuf-
ficient 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.
REFERENCE
Williams, J.R., P. Dyke, W. Fuchs, V. Benson, O. Rice, and E. Taylor. 1990. EPIC—Erosion/Productivity Impact
Calculator: 2. User Manual. Washington, DC: U.S. Department of Agriculture - Agricultural Research Service.
