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2-Plants: Another disillusioning U.S. study on GE crop benefits

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SOURCE: Economic Research Service, USDA, U.S.
DATE:   July 20, 1999

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Genetic engineering is a technique used to alter or move genetic
material (genes) of living cells (A number of the terms used in
this article are defined in Agricultural Biotechnology Concepts
and Definitions). U.S. acreage using genetically engineered crops
has increased from about 8 million acres in 1996 to more than 50
million acres in 1998, in major states where data have been
collected (see Genetically Engineered Crops for Pest Management,
also in this Issues Center). Has adoption of this technology
benefited farmers and the environment?

Answering this question is not easy, even though survey data have
been collected on the characteristics and performance of farms
adopting biotech crops. Attributing differences in yields,
pesticide use, and profits between adopters and nonadopters
observed in the data solely to adoption of genetically engineered
crops is nearly impossible because many other factors also affect
yield and pesticide use. For example, producers with more
favorable soils and climate may have higher yields than those
operating under less favorable conditions, whether they used
herbicide-tolerant varieties or not. Producers in areas of
greater pest pressure may use more pesticide applications than
those with fewer pest problems, despite adopting Bt crops.

However, the impacts of GMO (Genetically Modified Organisms)
adoption can be explored by statistically controlling for other
factors that also affect the impact. Multivariate regression
modeling in effect decomposes the influence various factors exert
on the decision to adopt GMO technology, and the influence of
other factors on yields, pesticide use, and variable profits.
This report summarizes preliminary findings from such models
using 1997 survey data.

Factors Affecting Adoption

What combination of producer characteristics and resource
conditions are associated with greater probability of adopting
GMO technology? Variables examined included farm size, operator
education and experience, target pest for insecticide use, seed
price, debt-to-assets ratio, use of marketing or production
contracts, irrigation, crop price, and use of consultants The
statistical significance and importance of these variables varied
among crops and technologies, illustrated by the cases of
herbicide-resistant soybeans and Bt cotton.

Herbicide-resistant soybeans
Larger operations and more educated operators are more likely to
use herbicide-tolerant soybean seed. As economists have observed
in other cases, expected profitability positively influences the
adoption of agricultural innovations. Thus, average crop price is
a statistically significant and positive factor influencing
adoption. Use of conventional tillage is another significant
factor that reduces adoption, since farmers use conventional
tillage to help control weeds, while herbicides are used with
conservation or no-till practices. Weed infestation levels and
seed price were positively correlated with adoption, with
adopters preferring more expensive, higher quality seed, even
excluding technical fees for herbicide-resistant varieties.

Bt Cotton
Adoption of insect-resistant cotton was only modeled
in the Southeast (AL, GA, NC, SC) because insecticide use in this
region was less affected by routine spraying regimes unrelated to
the use of Bt cotton, such as boll weevil control in other
producing regions, notably Mississippi. Production and marketing
contracts and seed price were statistically significant variables
positively associated with the adoption of Bt cotton. Presence of
insect pests targeted for insecticide use was also statistically
significant, but negative: more target pests treated with
traditional synthetic insecticides are associated with lower Bt
cotton adoption levels.

Modeling Impacts of Adoption

Given a specific level of GMO adoption, the impact can be
assessed by controlling for the many factors that also contribute
to that impact, in addition to using GMO seeds. Herbicide
tolerant soybeans and cotton and Bt-enhanced cotton crops are
modeled individually. In each model, pest infestation levels,
other pest management practices, crop rotations, and tillage are
controlled for statistically. Geographic location is included as
a proxy for soil, climate, and agricultural practice differences
that might influence impacts of adoption. In addition, the impact
model includes correction factors (obtained from the adoption
model) to control for self-selection of the technology due to
differences in producer characteristics between adopters and
nonadopters Results of such modeling can be interpreted as an
elasticity--the change in a particular impact (yields, pesticide
use or profits) relative to a small change in adoption of the
technology from current levels. The results can be viewed in
terms of aggregate impacts across the entire agricultural sector
as more and more producers adopt the technology, or in terms of a
typical farm as they use the technology on more and more of their
land. As with most cases in economics, the elasticities estimated
in the quantitative model should only be used to examine small
changes (say, less than 10 percent) away from current levels of


Table 1. The Impact of Adoption of Herbicide-Tolerant and Insect
         Resistant Field Crops

             Effect with respect to change in the adoption of
           Herbicide-tolerant  Herbicide-tolerant  Bt cotton 1997
           soybean 1997 (1)    cotton 1997 (1)     Southeast (1)

Change in yields
           small increase (2)  increase (3)        increase (3)

Change in profits
                   0 (4)       increase (3)        increase (3)

Change in pesticide use


- Acetamide herbicides 
                   0 (4)

- Triazine herbicides
                                      0 (4)

- Other synthetic herbicides
               decrease (3)           0 (4)

- Glyphosate   increase (3)           0 (4)


- Organophosphate insecticides                          0 (4)

- Pyrethroid insecticides                               0 (4)

- Other insecticides                                decrease (3)

1 Based on Fernandez-Cornejo, Klotz-Ingram, and Jans (1999).
  "Farm-Level Effects of Adopting Genetically Engineered Crops in
  the U.S.A." Selected Paper presented at the International
  Conference "Transitions in Agbiotech: Economics of Strategy and
  Policy." NE 165, Washington, DC, June 24-25, 1999.
2 Small increases or decreases are less than 1 percent change for
  a 10 percent change in adoption.
3 Increases or decreases are less than 5 percent change for a 10
  percent change in adoption.
4 Underlying coefficients are not statistically different from


Impacts From Adopting Herbicide-Tolerant Crops

Cotton production relies heavily upon herbicides to control
weeds, often requiring applications of two or more herbicides at
planting and postemergence herbicides later in the season. Close
to 28 million pounds of herbicides were applied to 97 percent of
the 13 million acres devoted to upland cotton production in the
12 major states in 1997.

In 1997, increases in adoption of herbicide-tolerant cotton are
estimated to have increased yields, leading to increased variable
profits (see Table 1, Impact of Adoption of Herbicide-Tolerant
and Insect-Resistant Crops). However, no statistically
significant change in herbicide use on cotton was observed in

By contrast, increased use of herbicide-tolerant soybeans (17
percent of 1997 soybean acres) produced only a small increase in
yield, and no significant change in variable profits in 1997.
Soybean production in the U.S. uses a large amount of herbicides,
and 97 percent of the 66.2 million acres devoted to soybean
production in the 19 major states were treated with more than 78
million pounds of herbicides in 1997. Genetic engineering
produces tolerance to glyphosate herbicide in soybeans, of which
15 million pounds were used in 1997. However, almost two-thirds
of the herbicides used on soybeans were other synthetic
materials. As GMO adoption increased, use of glyphosate herbicide
(such as Roundup) also increased but use of other synthetic
herbicides decreased by a larger amount. The net result was a
decrease in the overall pounds of herbicide applied.

Impacts From Adopting Insect-Resistant Cotton

Cotton production uses a large amount of insecticides and 77
percent of the 13 million acres devoted to upland cotton
production in the 12 major states were treated with 18 million
pounds of insecticides in 1997. Malathion was the top insecticide
used on cotton, with farmers applying more than 7 million pounds
of this chemical in 1997. Aldicarb was second (2.4 million
pounds), followed by methyl parathion (2 million pounds), and
acephate (0.9 million pounds).

In 1997, an increase in adoption of Bt cotton in the Southeast
(to 22 percent of cotton acres) led to an increase in cotton
yields and variable profits (see Table 1, Impact of Adoption of
Herbicide-Tolerant and Insect-Resistant Crops).

While use of organophosphate insecticides and pyrethroid
insecticides did not have significant changes associated with an
increase in Bt adoption, there was a significant decrease in
other insecticides, such as aldicarb.


Statistically controlling for factors other than adoption of
genetically engineered seeds allows an understanding of the
likely impacts of marginal changes in adoption on yields,
profits, and pesticide use. Impacts vary with the crop and
technology examined. Increases in adoption of herbicide-tolerant
cotton were associated with significant increases in yields and
variable profits, but were not associated with significant
changes in herbicide use. Increases in adoption of herbicide
tolerant soybeans were associated with small increases in yields
and variable profits, and significant decreases in herbicide use.
Increases in adoption of Bt cotton resistant to insects in the
Southeast were associated with significant increases in yields
and profits and decreased insecticide use.

For more information, contact Kitty Smith, 202-694-5500, or Ralph
Heimlich, 202-694-5504.

-| Hartmut Meyer
-| Co-ordinator
-| The European NGO Network on Genetic Engineering
-| Reinhaeuser Landstr. 51
-| D - 37083 Goettingen
-| Germany
-| phone: #49-551-7700027
-| fax  : #49-551-7701672
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