Farmers Balance Off-Farm Work and Technology Adoption
Farm households that
rely heavily on off-farm income have a tendency
to adopt farm technologies that save management
time.
Jorge
Fernandez-Cornejo
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Off-farm
income has risen steadily over recent
decades. Small-farm households are more
likely than larger farms to devote time
to off-farm employment. |
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New
technologies enhance options for trading
onfarm work for off-farm employment.
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Farm
households with higher off-farm income
are more likely to adopt farm technologies
that economize on management time than
those that are time intensive. |
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| This
article is drawn from . . . |
| Off-Farm
Income, Technology Adoption, and Farm Economic
Performance, by Jorge Fernandez-Cornejo,
with contributions from A. Mishra, R. Nehring,
C. Hendricks, A. Gregory, and M. Southern,
ERR-36, USDA, Economic Research Service, January
2007.
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| You
may also be interested in . . . |
| “Does
Off-Farm Work Hinder ‘Smart’ Farming?”
by K.R. Smith, in Agricultural Outlook,
AO-294, USDA, Economic Research Service, September
2002. |
Effectively managing land, water,
machinery, and other inputs—as well as adopting
new technologies and production practices—can
help ensure the success of a farm business and the
economic well-being of a farm household. Yet, farm
operators and their household members are increasingly
relying on off-farm employment to improve their
bottom lines. While contributing to the economic
well-being of farm households, off-farm jobs compete
with onfarm responsibilities for managerial time,
which, in turn, may affect the economic performance
of the farm business. Consequently, time-saving
benefits are driving the decisions of certain farm
operator households to adopt new technologies and
practices.
In addition to sustaining growth
in agricultural productivity and ensuring an abundance
of food and fiber, adopting innovative farm technologies
also changes the way farm households regard employment
choices. A recent ERS study finds that the adoption
of time-saving technologies, such as herbicide-tolerant
(HT) soybeans, is associated with higher off-farm
incomes (see box, “Modeling
Off-Farm Income and Technology Adoption”).
On the other hand, the adoption of time-intensive
technologies such as precision farming is more closely
associated with lower off-farm incomes. These findings
confirm a trade-off between the time spent on farm
and off-farm activities, which, in turn, translates
into a trade-off between expanding farm operations
and increasing off-farm income-generating activities.
Off-Farm Income Is Increasingly
Important for Farm Households
Off-farm income received by farm
operators and their spouses has risen steadily over
recent decades as job opportunities have grown and
mechanization and other technological innovations
have lessened onfarm labor needs. Off-farm income
as a share of total U.S. farm household income rose
from about 50 percent in 1960 to more than 80 percent
over the past 10 years. On average, a farm household
received about $81,500 in 2004, netting only $14,200
from farming activities. Earned off-farm income
averaged $48,800 and unearned income was about $18,500
(Social Security, interest, etc.). Fifty-two percent
of farm operators worked off-farm in 2004, up from
44 percent in 1979. Over the same period, the share
of spouses working off-farm grew from 28 to 45 percent.
Not surprisingly, the amount of time allocated to
off-farm employment has also risen. From 1996 to
2004, farm operators increased their average time
employed off-farm 20 percent from 830 hours to 1,002
hours, while not markedly changing the number of
hours spent working on the farm (1,525 hours in
1996 and 1,574 in 2004). Over the same period, the
spouses of farm operators increased their average
off-farm work hours from 690 to 809 per year.
Small Farms Are Particularly
Dependent on Off-Farm Income
Operators of smaller farms have
higher off-farm incomes, both earned and total,
than operators of larger farms. In 2004, farm households
with gross farm sales less than $10,000 averaged
just over $74,000 in off-farm income. In contrast,
households with farm sales between $250,000 and
$499,999 averaged about $45,000 in off-farm income.
While off-farm income constitutes the largest component
of total farm household income on average, its share
decreases with farm size. Off-farm income is no
longer the largest component of household income
for those farms with gross sales higher than $250,000
(less than 8 percent of U.S. farms).
| Operators
of smaller farms have higher off-farm incomes |
Farm sales |
Share of farms |
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$9,999 or less |
43.7 |
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$10,000-$99,999 |
40.7 |
67,971 |
4,091 |
$100,000-$249,999 |
7.9 |
46,913 |
33,999 |
$250,000-$499,999 |
4.2 |
44,870 |
79,516 |
$500,000-$999,999 |
2.0 |
52,077 |
116,766 |
$1,000,000 or more |
1.5 |
41,082 |
370,184 |
All farms |
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| Source: 2004 Agricultural
Resource Management Survey. |
The inverse relationship between
off-farm earned income and farm size is largely
attributed to a higher likelihood of off-farm employment
and more hours worked off the farm by operators
of smaller farms. More than 55 percent of operators
with farm sales less than $100,000 reported off-farm
hours in 2004, versus 20 percent or less for operators
of farms with sales above $250,000. However, off-farm
income obtained by those farm operators who work
off-farm does not vary much with farm size, averaging
$47,000 for operators of the smallest farms and
$39,000 for those of the largest farms.
Off-Farm Work Has Implications
for Technology Adoption
Farmers choose technologies and
practices they expect to yield the greatest net
benefits based on their own preferences, farm characteristics,
demand for their product, ease of application, and
costs. Traditional economic research examines the
benefits and costs of adopting agricultural innovations
focusing on the farm business. However, an analysis
based solely on net returns does not sufficiently
explain variations in the rates of adoption for
many recent agricultural innovations because the
value of management time is excluded. For example,
farmers rapidly adopted HT soybeans even though
they showed no significant advantage in net returns
over conventional soybeans. On the other hand, farmers
have been slow to adopt other technologies, such
as integrated pest management (IPM), despite the
potential for higher net returns and other advantages.
Such examples suggest that, in many cases, adoption
of new farm technologies and practices is driven
by “unquantified” factors, such as simplicity
and flexibility of use, that translate into reduced
managerial intensity and more free time for other
activities, particularly off-farm employment.
USDA survey results show operators
of high-sales, large, and very large farms—which
depend on farm revenues more than on off-farm earnings—tend
to adopt more management-intensive technologies.
For example, 18 percent of the operators of large
farms adopted precision farming in 1998, compared
with 3 percent of small-farm operators (who worked
fewer on-farm hours).
Technology Adoption and
Household Income
ERS examined the interaction of
off-farm income-earning activities and adoption
of four agricultural technologies of varying managerial
intensity—herbicide-tolerant crops, conservation
tillage, insect-resistant (Bt) corn, and yield monitors
(see box, “Selected Agricultural
Technologies”). This research also considered
the relationship between the adoption of these innovations
and farm household income from onfarm and off-farm
sources.
Adoption of HT soybeans, first
introduced in 1996, grew 70 percent in just 5 years,
despite no significant impacts on farm financial
net returns. However, after controlling for other
factors, a 16-percent increase in off-farm household
income is associated with a 10-percent increase
in the probability of adopting HT soybeans. This
finding suggests that operators employed off-farm
are more likely to adopt HT soybeans because the
simplicity and flexibility of weed control saves
managerial time. Also, a 9.7-percent increase in
total household income is associated with a 10-percent
increase in the likelihood of adoption of HT soybeans.
Similarly, a nearly 10-percent
increase in off-farm household income (and a nearly
5-percent gain in total household income) is associated
with a 10-percent increase in the probability of
adopting conservation tillage. Conservation tillage
is believed to be a management labor-
saving practice, but to a lesser degree than use
of HT soybeans.
On the other hand, the adoption of yield monitors,
a key component of precision agriculture, is associated
with lower off-farm income. An 8.4-percent decrease
in off-farm household income is associated with
a 10-percent increase in the probability of adopting
yield monitors. These techniques are managerially
time intensive, compared with HT soybeans and conservation
tillage, which are managerially time saving.
The adoption of Bt corn did not
show a significant relationship to off-farm household
income, indicating that Bt corn may be managerially
time neutral. Before the commercial introduction
of Bt corn in 1996, most farmers accepted yield
losses rather than incur the expense and uncertainty
of chemical control. For those farmers, the use
of Bt corn reportedly resulted in yield gains rather
than pesticide savings, and savings in managerial
time also were small.
Time/Income Trade-Offs
Have Policy Implications
Findings confirm a trade-off between
time spent on farm and off-farm activities. Households
operating small farms are more likely than larger
farm types to devote time to off-farm opportunities
and to adopt management-saving technologies (such
as herbicide-tolerant crops). Small-farm households
are less likely to adopt management-intensive technologies,
such as integrated pest management.
The relationship between off-farm
work and a farm’s economic performance also
suggests that a farm household’s dependence
on off-farm income affects the distributional consequences
of agricultural policies. Conservation, research
and development, extension services, and farm support
programs may affect farm households differently
depending on the relative importance of onfarm and
off-farm income-generating activities. Thus, the
consequences of government policies are largely
dependent on the diversity of U.S. farm households,
particularly regarding their income sources. For
example, a policy promoting the adoption of management-intensive
agricultural practices (such as IPM) may be less
effective unless it takes into consideration the
demands on managerial time required by the particular
practice.
These findings also have implications
for private agricultural research and development
(R&D). Innovators often base their economic
evaluations of returns to R&D on the expected
profitability of potential innovations for farmers.
For example, innovators may consider the extent
of yield increases and/or input cost reductions
resulting from a new technology relative to the
costs of adoption and current management practices.
This research shows that the value of management
time is an important additional element to be included
in the economic evaluations of new technologies.
| Modeling
Off-Farm Income and Technology Adoption |
| Economic
models help researchers estimate the impact
of a change in policies, programs, behavior,
or a myriad of other factors. For this study,
ERS researchers expanded the agricultural
household model to include the technology
adoption decision together with many other
important farm household economic decisions.
The updated model allowed researchers to consider
first the interaction of off-farm work and
adoption of agricultural technologies and
then the impact of technology adoption on
farm household income (from onfarm and off-farm
sources) after controlling for such interaction.
The analysis used data from nationwide surveys
of corn and soybean farmers in 2000-01.
The hypothesis is that adoption
of managerial-saving technologies (such as
HT soybeans) frees up management time for
use elsewhere (notably off-farm employment),
leading to higher off-farm income. On the
other hand, managerially intensive technologies
(such as precision agriculture) would result
in less time available for off-farm activities,
leading to lower off-farm income.
An alternative hypothesis
is that farmers already working off-farm may
be more disposed to adopt managerial-saving
technologies. This may lead to additional
off-farm work and result in even higher off-farm
income. Similarly, farmers who are working
off-farm may be reluctant to adopt managerially
intensive technologies.
In either case, adoption
of managerial-saving technologies would be
associated with higher off-farm income and
adoption of managerially intensive technologies
would be related to lower off-farm income.
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| Selected
Agricultural Technologies |
| Herbicide-tolerant
(HT) soybeans contain traits that allow them
to survive certain herbicides that would destroy
conventional soybeans along with the targeted
weeds. HT soybeans allow farmers to use more
effective post-emergent herbicides, expanding
weed management options. HT soybeans have
been adopted rapidly, reaching 89 percent
of soybean planted acres in 2006, and are
said to save managerial time because of the
relative simplicity of the weed control program.
Conservation tillage is
defined as “any tillage or planting
system that maintains at least 30 percent
of the soil surface covered by residue after
planting.” It includes no-till, ridge-till,
and mulch-till techniques. Adoption of conservation
tillage for corn peaked at about 41 percent
of corn planted acreage in 1997. Conservation
tillage is believed to save managerial labor.
Bt corn crops carry the
gene from the soil bacterium Bacillus thuringiensis
(Bt). Crops containing the Bt gene are able
to produce proteins that are toxic when ingested
by certain insects. Bt corn was planted on
35 percent of corn acreage in 2005. Savings
in managerial time depend on the type of insect
to be controlled. Use of Bt corn to control
the European corn borer is believed to result
in a small savings.
Yield monitors provide farmers
site-specific data that allow them to spatially
vary input application and production practices.
Yield monitors were used on 33 percent of
corn acreage and 25 percent of soybean acreage
in 2001. Adoption of yield monitors is believed
to be management intensive. |
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