MARKET FORECASTS
Market forecasts, or forecasts for specific industries or types of products, are based
on general economic forecasts and a great deal of information about the specifi c
industry involved. Agricultural economists continually monitor changing economic
indicators that track or lead agricultural trends. Some use complex mathematical
methods (econometric models) to predict demand for various products and
commodities. In the food business, demographic data is carefully studied to forecast
demand for specific products. Demographic factors such as family size, age, income
level, and education tell market researchers much about what kind and how much of
specific types of food products will be purchased in a region.
Factors determining farm market demand have been researched extensively. For
example, agricultural economists have worked to understand various cycles or patterns
in livestock production. Historically, pork production cycled every four years, while the
cattle cycled about every nine years. During these cycles, prices fell as the number of
animals on feed increased, and profits declined. As a result, some less efficient
producers exited from the market, livestock numbers dropped, and prices gradually
increased. The cattle cycle was longer because of the length of the gestation period for
cattle, taking more time to increase production. Dramatic changes in the size and
structure of pork and cattle operations over the past 20 years and the technologies used
by pork and cattle producers have certainly affected these cycles. Still, information and
forecasts on sow herd size, cattle on feed, dairy cow numbers, etc. is extremely important
to nutrition companies, milling equipment companies, livestock marketing firms and
meat processing companies because it directly impacts their prospects and customers
and thereby their market.
The demand for most farm inputs such as animal health products and fertilizer is a
derived demand. This means that the demand for a specific type of product or service
depends greatly on the demand for another product or service for which it is used. The
demand for fertilizer, for example, is a function of the demand for the crops it helps
produce. When the manager of a fertilizer plant in the Midwest is projecting the demand
for nitrogen, the corn market is carefully considered. The manager knows that the price
farmers anticipate for corn in the next season will greatly affect the number of acres of
corn they will plant and the amount of fertilizer they will want to buy. Consequently,
agribusiness managers are careful students of the market for whatever products their
supplies help to produce.
Not surprisingly, there is a great interest in current information on nearly every
product produced by farmers. Summaries and analyses of market conditions for virtually
every agricultural product are distributed widely each day — from both public and private
sources. Important grain and livestock market information is instantly flashed to analysts
and agribusinesses as transactions occur throughout the day via a variety of media —
television, radio, satellite news services, and the Internet, to name a few. Government
and private reports estimating current and projected acreage and livestock numbers are
released frequently throughout the year to help agribusinesses monitor trends and adjust
their plans.
Like agricultural input firms, food firms are also very interested in market demand.
Food marketers pay special attention to two key areas when forecasting sales —
regionality and seasonality. Food consumption patterns can vary dramatically from one
region of the country to another. For example, grits sell well in the Southeast U.S., but few
consumers may even know about this product in other regions of the country.
Consumption of food products will vary dramatically by season as well. Summer fruit,
vegetable, and ice cream sales, and holiday sales of turkey and ham are excellent
examples. Combined with good demographic data, bringing regional and seasonal
factors into the equation helps food marketers fi ne-tune their market forecasts.
Note that despite all the sophisticated techniques, forecasting market demand is
far from an exact science. Random events such as unexpected weather, consumer fads,
a food safety scare, or an international crisis can play havoc with the most elaborate
market demand forecast. Here, techniques such as contingency analysis or sensitivity
analysis become important. The general idea here is to bound a forecast with an upper
and lower range that helps the manager understand the uncertainty that comes with any
forecast. For example, when forecasting market demand, a fertilizer firm may look at corn
prices under strong export market, normal export market, and weak export market
conditions. Such a range of corn price forecasts helps the manager better understand
the market demand risk in the coming business environment and plan accordingly.
