ROOM AT THE TABLE - Intersight - University at Buffalo

extent of Erie County cropland (99.455 acres). Therefore, implementing this
rearrangement should yield the same self­reliance for each food group. Formulas
used in the existing conditions of agricultural production are again employed to
derive the eventual annual tonnage produced in each food group.
J. Limitations
Perhaps the most notable limitation would be the disregard of other
essential components within the food sector, which most certainly have an impact
on the capacity of the region to secure itself with food. For instance, the ability to
process the raw commodities produced at farms into the wide variety of products
purchased at retail and the capacity for food to be distributed between all these
players within the system. Furthermore, the analysis is largely conceptual in
the type of crops applied and used to calculate yields; that is, since no accurate
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within the county given the collected data, many crop types known to be grown
within Erie County are not applied to this analysis, due to data constraints. For
instance, no land is allocated to the raising of pigs or sheep since no indication is
given by the input data and is instead included in the land devoted to the production
of beef. Since the nutrient requirements of these livestock differ from those of
beef cattle, this generalization limits the reliability of the results. Moreover, the
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food resources such as, urban agriculture, residential gardens, aquaculture, and
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separation of crop types by 30m x 30m cells, while being consistent with the
input CDL, is not indicative of reality. Furthermore, the consumption scenarios
do not consider the recommended vitamin and mineral intake for individuals. The
consumption factor also neglects the wide variety of fruits, vegetables, meats that
current eating habits demand, and is suggesting that this diversity must become
limited to the crops considered in this analysis. Likewise, the analysis does not
consider the cultural appropriateness, according to the county’s population, of the
food grown by county farms.
VII. Chapter 8 ­ Economic Impact of the Food System
The economic analysis relies on an Input/Output (I/O) model. The I/O
model used 2009 data obtained from a private vendor, IMPLAN. IMPLAN data
is the most widely used software for I/O analyses. We used county­wide 2009
IMPLAN data of Erie County to describe economic conditions in 2009, and
estimate the multiplier effects of alternative scenarios.
The multiplier output is an indicator of economic impact, whereas an
increase in spending produces a general increase over the initial amount spent.
We examined various industries to determine which industry sectors held high
economic multipliers in each component of the food system. These indicators are
based on transactions which took place within Erie County in 2009.
i) Multiplier effects
To measure the economic impact of alterations in agricultural industry, the
multiplier effects in Erie County are estimated using IMPLAN software. As
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spending by the sectors related to food industries ripple throughout the county
economy, direct, indirect, and induced effects will be produced for Erie County’s
economy.
­ Direct economic impact:
This describes initial spending in a particular sector of the food industry.
For example, an increase in purchases of wine by consumers corresponds to an
increase in the sale of wine by a wine seller.
­ Indirect economic impact:
These effects result from a change in inter­industry purchases as they respond
to new demands of directly affected industries. For instance, a wine buyer would
need to buy crates for wine bottles from a crate manufacturing plant.
­ Induced economic impact:
A portion of food­industry employee incomes is spent on food, housing,
and other expenses payable within the county. As this money is retained within
the local economy, successive waves of spending are created. For example, an
increase in demand for wine may lead to an increased need for employees, which
will generate a need for more housing.
ii) Scenarios
Several scenarios were tested to verify the change in demand which will
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2009 IMPLAN data.
­ Fruits and vegetables (Agriculture)
Scenario 1: Eat healthy
The results of a hypothetical 20% increase in total demand for fruits and
vegetables (using the current proportion of local consumption for current fruits
and vegetables) are estimated.
Scenario 2: Eat healthy and locally
The consequence of a 20% increase in total demand for fruits and vegetables
along with a doubling in the proportion of these food groups being purchased
locally is measured.
­ Bakery, cookie and pasta (Processing)
Scenario 3: Increase food processing establishments
The economic impacts of introducing additional processing places (20%
above the current number) for bakery, cookie and pasta into Erie County are
estimated in this scenario.