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Understanding U.S. Farm Exits
Robert A. Hoppe and Penni Korb
Economic Research Report No. (ERR-21), June 2006
About 717,100 farms in the U.S. went out of business—or
exited—between 1992 and 1997. But the total number of
farms declined by just 13,400 because the number of entries
(703,700 farms) nearly equaled exits. In fact, the farm count
has remained relatively stable since the 1974 Census, reflecting
exits and entries essentially in balance.
Understanding farm exits is important for three reasons. First,
knowing which types of farms are most likely to exit might be
useful to policymakers interested in the effects of exits on
exiting farmers, the remaining farms, and farm communities.
Second, exits help reallocate resources between farming and
other economic activities and within the farm sector itself.
Third, farm exits—and farm entries—may play an important
role in introducing technologies and productivity growth, as
in other industries.
What Is the Issue?
U.S. farm numbers have been relatively stable between agricultural
censuses in recent decades, but beneath the surface, farming
is a much more dynamic industry than the farm count indicates.
The relatively small net change in farm numbers masks substantial
turnover in farms. Knowing the underlying socioeconomic components
of this turnover provides a more thorough understanding of exits
and gives other researchers a method of predicting exits.
What Did the Study Find?
U.S. farm exit rates are 9-10 percent per year, within 1 percentage
point of those for all U.S. small nonfarm businesses with no
employees. Small businesses have a high exit rate, and most
U.S. farms are small businesses. U.S. farms and other small
businesses have not disappeared completely because entry rates
as well as exit rates are high.
We studied two fundamental drivers of farm exits, farm size
and operator age. The life cycle of farm operators is important
in understanding farm exits because most U.S. farms are fairly
small family businesses and the life of the farm is correlated
with the life of the farmer. The correlation is not 100 percent
because the farm may continue as a business after an elderly
operator leaves, if operation of the farm as a separate business
continues under another operator, such as an adult child. The
results show the following:
• Exit rates decline as farm size (measured by sales)
increases.
• Nevertheless, exit rates are still 6-7 percent for large
farms (sales of $250,000 or more).
• The exit rate initially declines with age until it reaches
8-9 percent for farmers between 45 and 54 years of age.
• The rate then increases and peaks at 12-13 percent for
farmers who are at least 65 years old.
Because the operator’s age and farm size are important
determinants of farm exits, the report uses logistic regression
models to estimate exit probabilities, which control for these
factors. Two of the most striking findings from the study—the
narrowing gap in the probability of exit between Black- and
White-operated farms and the relationship between exit probability
and the age of the farm business—emerged when we examined
the effect of other farm and operator characteristics on exit
probabilities:
• Exit probabilities between the 1992 and 1997 Censuses
are 5-7 percentage points higher for Black-operated farms than
for White-operated farms, depending on sales class and operator
age. These Black/White differences represent a substantial decline
from the 1982-87 intercensus period, when exit probabilities
were 9-10 percentage points higher for Black-operated farms.
• Exit probability is inversely related to business age;
it is substantially higher for recent entries than for older,
more established farms.
• Exit probability is particularly low for large farms
that are at least 14 years old and operated by farmers who are
younger than 65. The lower exit probability for these large,
well-established farms may help explain the growing concentration
of production among fewer farms, particularly if the farms are
passed on to other family members and continue in operation.
How Was the Study Conducted?
This study used data from the 1997 Census of Agriculture Longitudinal
File to analyze the forces that drive farm exits. USDA’s
National Agricultural Statistics Service created the longitudinal
file from five agricultural censuses to follow individual farms
between 1978 and 1997. Data from the longitudinal file were
used to calculate exit rates for farms in different sales classes
and with operators in different age groups. These data were
also used in logistic regression models to estimate exit probabilities,
controlling for operator age and farm size. This study provides
a straightforward procedure for estimating exit probabilities
that can be applied to any group of farms.
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