provided by Research Papers in Economics
Profitability of Alfalfa
Hay Storage Using Probabilities:
An Extension Approach
Ronald L. Shane and Gordon L. Myer
Film managers are usually faced with making decisions involving risk and
uncertainty. A common source of risk and uncertainty is related to price variability. It is
possible to attach probabilities to price variability based on historical data, thus
providing the manager with additional information to base decisions. The purpose of this
study is to develop and present extension information in a form that assists a producer to
choose a marketing strategy based on the producer’s own risk preference. This was done
by developing probability of percentage rates of return based on historical data. Alfalfa
hay is used as the commodity example.
Commodity producers are frequently
faced with the decision of whether to sell a
commodity at harvest time or to store for
later sale. While there are alternative deci-
sion criteria, profitability has to be a primary
concern for commercial producers. This
study concentrates on relating commodity
price variability over time to profitability of
storage. A procedure which has general ap-
plication is illustrated with alfalfa hay.
A producer is necessarily interested in
future prices when considering storage. The
traditional extension approach to this ques-
tion has been to forecast a future price or
future price range, based on historical data
and current demand∕supply information. But
for some commodities, empirical price fore-
casts useful to producers may not be availa-
ble. For example, if only annual data is
available on determinants of commodity de-
mand and supply, price forecasts for monthly
decisions will not be possible.
Ronald L. Shane and Gordon L. Myer are Assistant
Professors of Agricultural Economics at the University of
Nevada, Reno.
This article is a joint contribution of the Nevada
Cooperative Extension Service and the Nevada Agricul-
tural Experiment Station, Journal Series Number 429.
Thus an extension technique is presented
here where historical monthly price data are
used to calculate expected percentage rates
of return from storage along with their as-
sociated probabilities of occurrence. In this
method, future alfalfa price levels are treated
as unknown, with future price changes hav-
ing known probability distributions — i.e.,
they are assumed to follow historical patterns
of variability.
Because commodity producers make deci-
sions relative to storage they must have
expectations regarding future prices relative
to current prices. Subjective probability esti-
mates are attached by producers, implicitly
in most cases, to future prices alternatives.
The possible date of future sale is not gener-
ally fixed at a single point in time, although
the maximum storage time is usually less
than a year. For example, a producer may
have decided to sell the commodity before
December 31, but any month before that
date may be acceptable.
The purpose of this paper is to present an
extension tool that: 1) provides a method of
calculating historical probabilities for various
rates of return for the purpose of increasing
producer’s information base; (2) provides a
measure of profitability in terms of a histori-
cal average percentage rate of return that сдп
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