APPLICATION OF THE MODEL
Reported here are the production, price, and
income implications of eliminating acreage diversion
and price and income support programs for feed
groups, wheat, soybeans and cotton. Other programs
including those for tobacco, wool, peanuts and rice
are assumed to continue.
The initial response to elimination of crop
acreage controls would be an increase in acreages
planted to crops. For the purpose of this study, it is
assumed that the removal of acreage restrictions for
feed grains, wheat and cotton would add a
“normal-yield equivalent” of 20 million harvested
acres of feed grains, 12 million acres of wheat and 3
million acres of cotton in the first year. Table 2
summarizes the economic impact of this
“unrestricted production policy” on specific
commodity categories and aggregate farm incomes.
To save space only simulation results for 1980 and
the base 1980 variable levels are tabulated. The 1980
simulation estimates reflect agriculture’s economic
position after farmers have had seven years to adjust
to the unrestricted production policy. By 1980, farm
prices recover substantially from the extremely low
levels of the first year of unrestricted production
($21 per ton for feed grains, 14 cents per pound for
cotton). Model results indicate that farmers would
not scale down production levels sufficiently by 1980
to balance supplies and demands at the base 1980
prices. The larger production levels depress cash
receipts, due to inelastic demands, and increased
production expenses. These results coupled with the
elimination of direct payments under the feed grain,
wheat and cotton programs, yield a reduction of net
farm income of over one-half ($8.7 billion compared
to $17.8 billion).
The free market estimates from this study are
consistent with the findings of other research studies.
For example, the aggregate simulation model
developed by Quance and Tweeten [21] estimated a
1980 net income of $9.2 billion with free markets.
With a continuation of present programs they
estimate a 1980 net farm income of $14.7 billion.
Free market net income estimates for other time
horizons have been about 40-50 percent of income
levels with historical programs in effect [13, 23, 18,
26].
SUMMARY AND CONCLUSIONS
This paper is largely methodological in nature. Its
purpose is to suggest one method of developing a
simple commodity-disaggregated policy model that
incorporates the professions’ best estimates of
commodity supply and demand requirements for a
future point in time. Unlike many highly aggregated
models, the impacts of a policy change on
production, price and income levels of major farm
commodities are estimated by the model as well as
the policy’s effect on national farm income.
Furthermore, no optimization assumptions are
superimposed on the system. Commodity production,
price and income levels are positivistically determined
via the dynamic and interdependent supply and
demand structures. The validity of the model rests
solely on the validity of the parameter estimates fed
into the model and the accuracy of the base
projections. Even though some of the parameter
estimates used in the model are based on meager
information, the synthetic development of the model
allows the researcher to draw on the expertise of
researchers who have spent months or years analyzing
a supply or demand structure for a commodity or
commodity group.
The model is not complete since only four crops
are included endogenously in the model. A larger
model with additional crop categories would be
desirable. Furthermore, the influence of stochastic
influences such as weather fluctuations and disease
problems are not incorporated into the model.
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