Abstract

This study estimates the total benefit arising from the adoption of agricultural biotechnology

in one year (1997) and its distribution among key stakeholders along the production and

marketing chain. The analysis focuses on three biotech crops: herbicide-tolerant soybeans,

insect-resistant (Bt) cotton, and herbicide-tolerant cotton. Adoption of these crops resulted

in estimated market benefits of $212.5-$300.7 million for Bt cotton, $231.8 million for herbicide-tolerant cotton, and $307.5 million for herbicide-tolerant soybeans. These benefits

accounted for small shares of crop production value, ranging from 2 percent to 5 percent.

U.S. farmers captured a much larger share (about a third) of the benefits for Bt cotton than

with herbicide-tolerant soybeans (20 percent) and herbicide-tolerant cotton (4 percent).

Innovators’ share ranged from 30 percent for Bt cotton to 68 percent for herbicide-tolerant

soybeans. For herbicide-tolerant cotton, U.S. consumers and the rest of the world (including

both producers and consumers) received the bulk of the estimated benefits in 1997.

Estimated benefits and their distribution depend on the specification of the analytical framework, supply and demand elasticity assumptions, the inclusion of market and nonmarket

benefits, crops considered, and year-specific factors (such as weather and pest infestation

levels).

Keywords: Agricultural biotechnology, distribution of benefits, Bt cotton, herbicidetolerant cotton, herbicide-tolerant soybeans.

Acknowledgments

The authors thank Demcey Johnson, Mary Bohman, Katherine Smith, Michael

Schechtman, Keith Wiebe, Greg Traxler, GianCarlo Moschini, Utpal Vasavada, Ralph

Heimlich, and Aziz Elbehri for their insightful comments and suggestions on an earlier

draft of this report. Editing by Dale Simms and design contributions by Wynnice

Pointer-Napper are gratefully acknowledged.

United States

Department

of Agriculture

www.ers.usda.gov

Electronic Report from the Economic Research Service

November 2003

Technical

Bulletin

Number 1906 Size and Distribution of

Market Benefits From

Adopting Biotech Crops

Gregory K. Price, William Lin, José B. Falck-Zepeda,

and Jorge Fernandez-Cornejo
Contents

Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .iii

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .1

Previous Related Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

Scope of the Analyses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .3

Analytical Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .4

Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .5

Results of Previous Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .6

Theoretical Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8

Moschini and Lapan Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .8

Empirical Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .9

Farm-Level Effects on Crop Yields and Pest Control Costs . . . . . . . . . . . . . .13

Data Sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .13

Estimated Impacts on Crop Yields . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14

Estimated Impacts on Pest Control Costs . . . . . . . . . . . . . . . . . . . . . . . . . .15

Implications for Pesticide Use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .18

Estimating the Size and Distribution of Market Benefits . . . . . . . . . . . . . . . .20

Data and Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .20

Mean Values of Estimated Marshallian Surplus Changes . . . . . . . . . . . . . .21

Results for Bt Cotton . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .21

Results for Herbicide-Tolerant Cotton . . . . . . . . . . . . . . . . . . . . . . . . . . . . .22

Results for Herbicide-Tolerant Soybeans . . . . . . . . . . . . . . . . . . . . . . . . . . .24

Comparison of Results With Previous Findings . . . . . . . . . . . . . . . . . . . . .25

Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .27

Supply and Demand Elasticity Assumptions . . . . . . . . . . . . . . . . . . . . . . . .27

Efficiency of Technology Transfer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .29

Range of Estimated Surplus Gains or Losses . . . . . . . . . . . . . . . . . . . . . . .30

Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .33

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .35

Appendix A: Empirical Model for Measuring the Changes in 

Economic Surpluses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .38

Appendix B: Differences in Estimated Surplus Changes for Herbicide-Tolerant

Soybeans Due to Different Analytical Frameworks . . . . . . . . . . . . . . . . . . . . . . . .40

ii ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA
Summary

The adoption of biotech crops, particularly herbicide-tolerant soybeans and cotton,

has been rapid since their commercial introduction in 1996. For example, herbicidetolerant soybeans accounted for 81 percent of U.S. soybean acreage in 2003, leaping

from 7 percent in 1996. Biotech crops can offer producers distinct advantages over

conventional varieties, such as potentially higher yields and lower pest control costs.

But producers are not the only ones to gain from the adoption of agricultural

biotechnology. Biotechnology developers and seed companies gain by charging

technology fees and seed premiums to adopters who plant biotech varieties.

Ultimately, U.S. and foreign consumers benefit from biotech crops through lower

commodity prices, which result from increased supplies.

This study seeks to estimate the size and distribution of benefits from adopting the

three most prevalent biotech crops—Bacillus thuringiensis (Bt) cotton, herbicidetolerant cotton, and herbicide-tolerant soybeans—in 1997. The stakeholders considered in this study are U.S. farmers, U.S. consumers, biotechnology developers,

germplasm suppliers, and producers and consumers in the rest of the world (ROW).

We focus on specific and readily quantifiable market benefits accruing to stakeholders. As such, this analysis does not consider ease of pest management, a major

factor in the rapid adoption of herbicide-tolerant soybeans. Similarly, nonmarket

effects, including the environmental and health impacts of biotech crop adoption, are

not considered in this study. Nor do we address the effects of adopting biotech crops

on groups of consumers with different preferences toward biotech foods. 

The estimated total benefit for each of the three biotech crops is measured in

change to total welfare in both the seed input and commodity output markets. The

theoretical framework accounts for monopoly profits in the input market. Because

of intellectual property rights protection, the innovator prices the technology above

marginal cost, allowing the firm to realize monopoly profit. The model also measures welfare changes for producers and consumers in a competitive output market,

since some of the benefits generated by the innovation are passed on to them in the

form of higher production efficiency and lower commodity prices.

In this study, the estimated total market benefit from adopting each of the biotech

crops depends on the extent to which the commodity supply curve shifts outward

after the introduction of the technology. In each case, the shift in supply reflects

potential yield increases and savings in pest control costs. The estimated market

benefit also depends on the interaction of the supply and demand curves before

and after the introduction of the new technology. In this study, an empirical model

is developed to calculate the pre- and post-innovation prices and quantities in an

international market setting using information on adoption rates, crop yields, pest

control costs, technology fees, and seed premiums. The framework takes into

account the adoption of biotechnology outside of the United States, with assumptions regarding the efficiency of technology transfer to foreign countries.

For each of the three biotech crops in 1997, the estimated market benefits

ranged from $213 million to $308 million. Our estimates of benefits from agricultural biotechnology are based on two data sources: data estimated from the 1997

Agricultural Resource Management Survey (ARMS) and a private database for Bt

cotton. Both data sources isolate the effects of biotechnology on crop yields and pest

control cost savings. Gains ranging from $212.5 million (ARMS) to $300.7 million

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● iii
(private data source) were estimated from the planting of Bt cotton in 1997—3.6

percent to 5.1 percent of the value of upland cotton production. Herbicide-tolerant

cotton improved total welfare by an estimated $231.8 million (3.9 percent of the value

of upland cotton production), while the adoption of herbicide-tolerant soybeans

yielded $307.5 million in total benefits (1.7 percent of the value of soybean production). These estimates are generally higher than those of previous studies in the case

of Bt cotton, but lower for herbicide-tolerant soybeans.

The distribution of estimated benefits varied significantly across the three

biotech crops. U.S. farmers received about a third of the estimated total benefit

from adopting Bt cotton. (Previous studies estimated the share at around 50

percent.) In contrast, U.S. farmers captured just 20 percent of the estimated total

benefit from adopting herbicide-tolerant soybeans—a share at the lower end of the

benefit range reported in previous studies. With herbicide-tolerant cotton, a small

U.S. farmers’ share (4 percent) of the estimated total benefit was attributed to

greater seed costs over conventional varieties and lower world prices (which offset

the benefit of higher yields). Innovators captured 30 percent and 68 percent of the

estimated total benefits from the adoption of Bt cotton and herbicide-tolerant

soybeans. For herbicide-tolerant cotton, U.S. consumers and foreign producers and

consumers received the bulk of the estimated benefits in 1997.

Estimates of biotech benefits are sensitive to a number of factors, including

the analytical framework and supply elasticity assumptions. Sensitivity

analysis indicates that changes in the U.S. and ROW supply elasticity assumptions

have a more pronounced effect on the total benefit estimate than do changes in the

U.S. and ROW demand elasticity assumptions. Supply elasticity assumptions affect

the estimated benefits overall and those accruing to U.S. farmers more than for

U.S. consumers. For example, doubling the supply elasticities reduces the estimated total benefit by about half in the case of herbicide-tolerant soybeans and

causes U.S. soybean producers’ share of the estimated total benefit to disappear.

Estimates of stakeholder benefits depend on the extent to which market benefits

are captured in the analysis. Although not included in this study’s benefit estimates,

some important aspects of market benefits, such as the ease of pest management associated with herbicide-tolerant crops and the insurance value of insect-resistant crops,

can affect the results. In addition, potential nonmarket benefits, including effects on

the environment and human health, could influence the benefit estimates. As part of

the environmental effects, biotechnology can potentially lead to lower pesticide use.

Pesticide applications (measured in pounds of active ingredients) in 1997 were lower

for Bt cotton in the Southeast, herbicide-tolerant cotton nationwide, and herbicidetolerant soybeans in some major production regions. Other environmental and health

benefits associated with the adoption of biotechnology, such as pesticide toxicity

levels and the length of persistence in the environment, would factor into the total

(nonmarket) benefits but are not part of this assessment.

Year-specific variables, including pest infestation levels, affect the size and

distribution of benefits. For insect-resistant crops, such as Bt cotton, infestation

levels of target pests can fluctuate over time. With low infestation, farmers are

likely to derive fewer benefits from biotech crops. Weather conditions can also

vary across growing seasons, which may affect potential yield enhancements associated with planting biotech crops. Hence, multiyear analyses are desirable to

obtain more reliable estimates of the market benefits from agricultural biotechnology adoption.

iv ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA
Introduction

The adoption of agricultural biotechnology has grown

rapidly in the United States since its commercialization in 1996.2 Herbicide-tolerant soybeans have been

adopted particularly fast, from 7 percent of total soybean acreage in 1996 to 81 percent in 2003 (fig. 1;

Smith and Heimlich; USDA, 2003). The adoption of

herbicide-tolerant cotton has been nearly as fast, from

about 10 percent of upland cotton acreage in 1997 to

59 percent in 2003.3 In contrast, the adoption of herbicide-tolerant corn has expanded slowly, from 3 percent

in 1996 to 15 percent in 2003. Compared with herbicide-tolerant soybeans and cotton, the adoption of

insect-resistant (Bacillus thuringiensis or Bt) varieties

has also grown slowly. During 1996-2003, Bt cotton

(corn) adoption increased from 15 (2) percent in major

producing States to 41 (29) percent nationwide (fig. 2;

Smith and Heimlich; USDA, 2003).4, 5

Overall, rapid growth in the adoption of biotech varieties reflects a desire by producers for potential crop

yield increases, cost savings in pest control, and

greater ease of management (including labor savings).

Bt corn and cotton contain a gene that causes these

crops to produce proteins that are toxic to certain pests

but are harmless to other insects, humans, and animals.

Herbicide-tolerant crops (soybeans, corn, and cotton)

offer simple and flexible weed control programs and

allow producers to use one herbicide without causing

crop damage (Fernandez-Cornejo and McBride, 2002).

As a result of these perceived benefits, U.S. plantings

of biotech varieties increased from about 10 million

acres in 1996 to 101 million acres in 2003 (Smith and

Heimlich; USDA, 2003).

Consumers as a whole benefit from biotechnology in

crop production because of greater supplies and lower

market prices. This is especially true for consumers

who are indifferent to biotech versus nonbiotech products. Consumers insistent on nonbiotech goods are

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 1

Size and Distribution of Market Benefits

From Adopting Biotech Crops

Gregory K. Price, William Lin, José B. Falck-Zepeda, 

and Jorge Fernandez-Cornejo1

1 Price and Lin are with the Market and Trade Economics Division, ERS; Fernandez-Cornejo is with the Resource Economics

Division, ERS; Falck-Zepeda is with the International Service for

National Agricultural Research, The Hague, Netherlands.

2 For purposes of this study, agricultural biotechnology refers to the

use of recombinant DNA technology (DNA formed by combining

segments of DNA from different organisms) to alter or move genetic

material so that a plant (such as corn or soybeans) exhibits a desired

trait as a result of gene insertion. Fernandez-Cornejo and McBride

(2000) provide more detailed information about the basic concepts

and definitions of agricultural biotechnology.

3 The 2003 estimate for herbicide-tolerant cotton includes stackedgene varieties, which possess both insect-resistant and herbicidetolerant traits. Stacked-gene varieties accounted for 27 percent of

U.S. upland cotton acreage in 2003.

4 The 2003 estimates for Bt cotton and Bt corn include stackedgene varieties, which accounted for 27 percent of total upland cotton acreage and 4 percent of total corn acreage.

5 The decline in the adoption of Bt corn from 29 percent in major

producing States in 1999 to 19 percent in 2000 may have been

attributable, in part, to low infestation levels of European corn borers in 1998 and 1999 (USDA, 2001a).

Figure 1

Adoption of herbicide-tolerant soybeans, 

cotton, and corn in the United States, 1996-2003

Percent of acres

Soybeans

Cotton

Corn

Sources: Smith and Heimlich for 1996 and 1997 (using data from 

the Agricultural Resource Management Survey); USDA’s March 

2000 Prospective Plantings report for 1998 and 1999; and USDA’s 

June 2001, 2002, and 2003 Acreage reports for 2000 through 2003. 

Adoption in 1998 and 1999 includes both biotech and conventional 

varieties with the herbicide-tolerant trait. Adoption rates for corn and 

cotton include both herbicide-tolerant only and stacked-gene varieties.

1996 98 2000 02

0

20

40

60

80

100
worse off since they have to pay premiums, which

reflect the costs of product segregation. This study

does not consider the welfare effects for consumers

with divergent preferences for biotech foods.

Much debate has centered on how benefits from agricultural biotechnology are shared. Producers may benefit from higher net returns, but consumers may also

benefit. Recent studies concur that U.S. farmers

receive roughly one-half of the total estimated benefits

(Falck-Zepeda et al., 1999, 2000a, 2000b; Paarlberg).

However, some studies cite significantly different

shares for U.S. farmers (Frisvold et al.; Falck-Zepeda

et al., 2000a; Moschini et al.). These differences are

attributable to varying methodological approaches,

supply and demand elasticity assumptions, crops analyzed (e.g., herbicide-tolerant soybeans, Bt cotton),

study periods investigated, and choice of data sources

on farm-level impacts.

The purposes of this report are twofold: (1) to estimate

the size of the total benefits that arise from the adoption of agricultural biotechnology; and (2) to measure

the distribution of estimated benefits among key stakeholders—U.S. farmers, U.S. consumers, biotechnology

developers, germplasm suppliers, and the producers

and consumers in the rest of the world (ROW). We

focus on market benefits from adopting herbicide-tolerant soybeans as well as Bt and herbicide-tolerant

upland cotton in 1997, using data from the 1997

USDA Agricultural Resource Management Survey

(ARMS)—the latest data available at the time of

analysis—and a private data source for Bt cotton. The

ARMS records U.S. producers’ production practices,

resource use, and financial condition, as well as the

economic well-being of farm households. (Biotech

corn is excluded from this study because 1996 ARMS

data on Bt and herbicide-tolerant corn varieties may be

inaccurate and unreliable due to low adoption that

year—the first year of commercial availability; more

recent data are unavailable.) This study uses ARMS

data on potential crop yield gains and savings in pest

control costs after isolating the effects of biotechnology on these farm-level effects.

2 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA

Figure 2

Adoption of insect-resistant (Bt) corn and 

cotton in the United States, 1996-2003

Percent of acres

Cotton

Corn

Sources: Smith and Heimlich for 1996 and 1997 (using data from the 

Agricultural Resource Management Survey); USDA’s March 2000 

Prospective Plantings report for 1998 and 1999; and USDA’s June 

2001, 2002, and 2003 Acreage reports for 2000 through 2003. 

Adoption includes both Bt and stacked-gene varieties. 

1996 98 2000 02

0

10

20

30

40

50
A number of studies have estimated the benefits associated with the adoption of biotech crops. These studies vary by types of benefits, stakeholders, crops, and

years considered, as well as analytical frameworks

employed. Studies that examine the distribution of

estimated benefits among various stakeholders are limited to specific market benefits. Other studies focus on

nonmarket impacts, such as changes in pesticide use

and effects on the environment. Other differences

include supply and demand elasticity assumptions,

choice of data sources for farm-level effects (potential

yield enhancements and/or savings in pest control

costs), and the extent of farm-level impacts in the rest

of the world relative to those in the United States. As a

result of various approaches and assumptions, these

studies yield different results.

Scope of the Analyses

Several studies have examined the distribution of estimated benefits for a range of stakeholders, including

U.S. farmers, U.S. consumers, biotechnology developers, germplasm suppliers, and producers and consumers in the rest of the world. Falck-Zepeda et al.

(1999; 2000a; 2000b) and Frisvold et al. estimated the

distribution of benefits arising from the adoption of Bt

cotton during 1996-98. Falck-Zepeda et al. (2000a)

and Moschini et al. quantified the benefits from adopting herbicide-tolerant soybeans for those stakeholders

in 1997 and 1999, respectively.

Other studies have estimated the benefits from

biotech adoption for selected stakeholders. The U.S.

Environmental Protection Agency (EPA) estimated

the change in welfare realized by U.S. adopters of Bt

corn and Bt cotton between 1996 and 1999. Their

study uses a simple simulation model to estimate

adoption rates and the distribution of growers’ net

benefits using a uniform probability distribution.

Several studies have estimated Bt cotton growers’

benefits from yield enhancements and/or savings in

pest control costs (Stark; ReJesus et al.; Gibson et

al.; Marra et al.; Mullins and Mills; Gianessi;

Gianessi and Carpenter, 2000). While herbicide-tolerant soybeans did not offer significantly higher

yields in the late 1990s, U.S. farmers benefited from

lower total herbicide costs despite increased

glyphosate use (Marra et al.; Gianessi et al.).

For Bt cotton, farm-level cost savings associated with

reduced insecticide usage ranged from $28/acre to

$47/acre for U.S. adopters in the late 1990s (Stark;

Mullins and Mills). U.S. farmers were reported to have

realized higher gross returns of up to $73 per acre due

to higher yields (Stark). While herbicide-tolerant soybeans did not offer significantly higher yields, total

herbicide costs decreased $11 per acre in 1996 despite

increased glyphosate use (Marra et al.). Gianessi et al.

estimated that herbicide-tolerant soybean adopters

saved $20 per acre on weed control programs due to

lower herbicide costs in 2001. Other studies report significantly smaller herbicide cost savings, ranging from

$3 to $4.80 per acre (Rawlinson and Martin; Duffy

and Vontalge; Lin et al., 2001).

Comprehensive studies of the distribution of benefits,

such as those by Falck-Zepeda et al. (2000b) and

Moschini et al., consider the market benefits realized

by different stakeholders in the marketplace. These

complex studies use data on the farm-level effects as

well as other information (such as supply and demand

elasticities and commodity trade flows) to determine

changes in production, prices, commodity trade flows,

and innovator profits.

While these analyses address some of the important

market benefits for stakeholders, there are others that

are not covered. Biotech crops offer other market benefits to producers, such as simplified and flexible weed

management systems (Fernandez-Cornejo and

McBride, 2002). In addition to fewer herbicide applications, the window of application for glyphosate in

the case of herbicide-tolerant crops is relatively large,

and post-emergence treatments do not reduce soybean

yields or cause crop damage (Gianessi and Carpenter,

2000). Insect-resistant crops offer producers insurance

against targeted pest infestation. Farmers who choose

to grow biotech varieties anticipate that they will provide crop protection in the event that infestation

occurs. This “insurance value” is an ex-ante market

benefit for adopters since those producers must make

the adoption decision before the true infestation levels

are known.

These comprehensive studies do not consider nonmarket impacts, such as those on the environment and

human health. The adoption of some biotech crops,

such as Bt cotton, was shown to have reduced pestiEconomic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 3

Previous Related Studies
cide use because pest control is critical in cotton production. However, the reduction in pesticide use alone

does not capture all of the potential environmental and

health impacts of adopting biotech varieties.

Even if the adoption of some biotech crops may not

lead to reductions in pesticide use, positive benefits to

the environment may still arise. For example,

glyphosate, in the case of herbicide-tolerant soybeans,

is substituted for other synthetic herbicides that are

typically used in the production of conventional varieties. Adopters of this technology can rely on one to

two post-emergence herbicide applications instead of

three to four to control a broad spectrum of weeds

without causing crop injury (Gianessi and Carpenter,

2000). This should result in decreased fuel use for

operation of farm machinery. In addition, compared

with other synthetic herbicides, glyphosate is at least

three times less toxic and persists in the environment

half as long (Heimlich et al.; Ervin et al.; EPA). The

use of glyphosate in conjunction with herbicide-tolerant soybeans has allowed farmers to adopt no-till and

narrow-row planting practices, which aid in soil conservation (Carpenter and Gianessi, 1999a). Last, the

adoption of herbicide-tolerant soybeans leads to lower

water usage and imposes no restrictions on crop rotations (Ervin et al.; Gianessi and Carpenter, 2000).

Some studies assess the impact of biotech adoption in

terms of changes in pesticide use (Gianessi and

Carpenter, 1999 and 2000; Heimlich et al; FernandezCornejo and McBride; Lin et al., 2001; and Gianessi et

al.). For example, Gianessi et al. reported a decrease of

0.57 pound of active ingredients per acre for herbicidetolerant soybean adopters in 2001. That value is much

higher than the 0.02 pound-per-acre reduction shown

by Lin et al. (2001) for adopters in 1997.

Other biotech crop studies explicitly analyze the

impacts on wildlife. For example, EPA assessed the

benefits of lower pesticide use through biotech adoption by determining the reduction in wildlife mortality

and poisoning or death in humans. In the late 1990s,

according to EPA, reduced use of conventional insecticides associated with Bt cotton led to fewer impairments to aquatic wildlife.

While most studies focus on the benefits of biotech

crops, there are potential risks associated with the

adoption of these varieties (Ervin et al.). These risks

include the consequences of gene flow to wild species

and the impacts on genetic diversity in the ecosystem.

In addition, targeted pests may become resistant to

specific pesticides. In some instances, biotechnologyderived traits could result in adverse effects on beneficial insects. However, these potential impacts and

others are evaluated as part of the overall risk assessment for biotech crops prior to commercialization.

Analytical Framework

The works by Falck-Zepeda et al. (1999; 2000a;

2000b), Moschini et al., and Frisvold et al. aim to

measure changes in surpluses for various stakeholders,

including U.S. farmers, U.S. consumers, technology

innovators, and producers and consumers in the rest of

the world. In each study, welfare changes are calculated

from commodity supply, demand, and prices under two

different scenarios: (1) a base case where biotech adoption occurs, and (2) a counterfactual scenario where

biotechnology is not available to producers.

The general approach used to measure the distribution

of estimated benefits follows a spatial equilibrium

modeling structure. The works by Falck-Zepeda et al.

(1999; 2000a; 2000b) and Moschini et al. are based on

a theoretical framework developed by Moschini and

Lapan for assessing the welfare impacts of an innovation where the innovator behaves as a monopolist

under the protection of intellectual property rights

(IPR) in an input market. In addition to measuring

changes in Marshallian surplus—the sum of producer

and consumer welfare—in the commodity output market, which is characterized by a competitive structure,

the Moschini and Lapan model calculates the monopoly profits captured by the innovator. In contrast,

Frisvold et al. determine the benefits for adopters and

nonadopters separately using a mathematical programming model, which accounts for the impacts of commodity price changes and government price support

programs on the stakeholders’ welfare.

Analytical frameworks employed in previous studies differ in their specifications concerning the form of commodity supply and demand as well as the nature of the

supply shift attributed to biotechnology. Falck-Zepeda et

al. (1999, 2000a, 2000b) specified linear supply and

demand curves and assumed parallel shifts in supply

(table 1). These two assumptions impose significant

restrictions on the model structure. In such a framework,

producer surplus cannot decline with an innovation that

causes a parallel supply shift. In contrast, Frisvold et al.

and Moschini et al. used nonlinear supply and demand

4 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA
curves and assumed nonparallel supply shifts, which

impose fewer restrictions on the model.

While there are a number of differences among these

studies, they also exhibit some similarities. FalckZepeda et al. (1999, 2000a, 2000b) and Frisvold et al.

estimated the changes in producer welfare in various

U.S. production regions. Moreover, biotech adoption is

determined endogenously through land allocation

mechanisms for biotech and conventional varieties in

the studies by Moschini et al. and Frisvold et al.

Falck-Zepeda et al. (1999, 2000a, 2000b) did not

endogenize adoption decisions. Instead, actual adoption data were used as inputs in the estimation of the

model. Unlike the other two studies, Frisvold et al.

considered the effects of government program payments on the welfare of Bt and conventional cotton

producers. Last, while other studies considered only

the U.S. and ROW markets, Moschini et al. separated

South America, a major U.S. competitor, from the

ROW in their analysis of herbicide-tolerant soybeans.

Moschini et al. also considered the entire soybean

complex (including soybean oil and meal), while

Falck-Zepeda et al. (2000a) limited their investigation

to soybeans only.

Assumptions

Additional differences among the three prior studies

on biotech crops lie in the supply and demand elasticity assumptions. Model results hinge upon these

assumptions. U.S. supply elasticity assumptions are

especially critical in affecting the size and distribution

of estimated benefits because the technology’s impacts

are manifested through a shift in the supply curve.

The U.S. supply elasticity assumed in the models varies

greatly in the case of Bt cotton, ranging from perfectly

inelastic (within a small price interval) to 0.84 (table 2).

The upper-bound U.S. supply elasticity in the FalckZepeda et al. (2000a) study on herbicide-tolerant soybeans is similar to that assumed by Moschini et al., but

the lower value (0.22) is not. In general, a lower U.S.

supply elasticity increases the size and share of the estimated benefits that accrue to producers.

Variation in the U.S. demand elasticity is not as large

as for the U.S. supply elasticity, and variation in the

net export demand elasticity is relatively small in the

case of Bt cotton (table 2). Although there are differences in the ROW supply and demand elasticities, they

are generally small (except for Moschini et al.).

Previous studies also make various assumptions

regarding the efficiency of technology transfer to

ROW producers (table 2). That is, to what extent (relative to the U.S.) are potential yield enhancements and

savings in pest control cost realized by adopters in the

rest of the world? A 100-percent efficiency means that

the technology has the same farm-level effects in the

rest of the world as in the United States. In the case of

Bt cotton, Falck-Zepeda et al. (2000b) assumed a 50-

percent efficiency in technology transfer to the rest of

the world. This assumption was changed to 100 percent in a subsequent study (Falck-Zepeda et al.,

2000a). (Frisvold et al. did not consider adoption of Bt

cotton outside of the United States.) For herbicide-tolerant soybeans, a 100-percent efficiency was assumed

in all previous studies.

Data

Estimates of the farm-level effects from biotech adoption have come from various sources. In the case of Bt

cotton, both Falck-Zepeda et al. (2000b) and Frisvold

et al. relied on average values obtained from surveys

of county agents, State extension specialists, private

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 5

Table 1—Analytical framework specification in previous studies

Falck-Zepeda et al. Frisvold et al. Falck-Zepeda Moschini

Specification (1999, 2000a, 2000b) et al. (2000a) et al.

1996-98 1997 herbicide- 1999

------------Bt cotton----------- tolerant soybeans herbicide-tolerant 

soybeans

Form of supply and 

demand curves Linear Nonlinear Linear Nonlinear

Supply shift Parallel Nonparallel Parallel Nonparallel
consultants, and research entomologists (Williams).

Falck-Zepeda et al. (1999 and 2000a) also used the

Enhanced Market Data II, a private-sector source

applicable to the Southeast region (Plexus Marketing

Group, Inc., and Timber Mill Research, Inc.). Unlike

other data, this source isolates the impacts of biotechnology on cotton yields and insect control costs by

comparing Bt and non-Bt fields that are similar with

respect to weather, agronomic conditions, and production practices.

For herbicide-tolerant soybeans, Moschini et al. used

information from an Iowa State budget on the costs of

production. In contrast, Falck-Zepeda et al. (2000a)

used the average difference between yields and pest

control costs as reported by adopters and nonadopters

in the ARMS.

Significant differences across data sources have contributed to a wide range of estimates for stakeholders’

benefits. For example, Falck-Zepeda et al. (2000a)

assumed a 13-percent yield increase for herbicide-tolerant soybean adopters in the Corn Belt. In contrast,

adopters in the study by Moschini et al. were assumed

not to have realized any yield advantage. This difference caused U.S. farmers to capture a larger share of

the estimated total benefits in the study by FalckZepeda et al. (table 3).

Other data assumptions have influenced the distribution

of estimated benefits. Falck-Zepeda et al. (1999, 2000a,

2000b) assumed that the proportion of U.S. cotton production exported to the rest of the world matches the

proportion of imports relative to ROW cotton production. This assumption implicitly postulates that the consumption-to-production ratio in the United States is

identical to that in the rest of the world. Furthermore,

the proportion of regional production exported to the

ROW was assumed to be the same as at the national

level (40 percent). In determining the benefits for U.S.

and rest of the world stakeholders, regional distribution

data may be used to more accurately account for

domestic use and exports (Glade et al.).

Results of Previous Studies

In general, past studies have found that the bulk of

estimated benefits accrue to U.S. producers and technology innovators (biotechnology developers and

germplasm suppliers). However, reported benefits to

U.S. farmers and the biotech/seed firms vary greatly

(table 3). In the case of Bt cotton, U.S. producers

earned 5-59 percent of the estimated total benefit and

innovators received 26-47 percent. For herbicide-tolerant soybeans, U.S. farmers realized 20-77 percent of

the estimated total benefit and innovators captured 10-

45 percent.

6 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA

Table 2—Parameter assumptions in previous studies: Supply and demand elasticities and efficiency 

of technology transfer

Falck-Zepeda et al. Frisvold et al. Falck-Zepeda Moschini

Parameter (1999, 2000a, 2000b) et al. (2000a) et al.

1996-98 1997 herbicide- 1999

------------Bt cotton----------- tolerant soybeans herbicide-tolerant 

soybeans

U.S. supply elasticity 0.84 01 0.22 and 0.92 0.8

U.S. demand elasticity -0.101 -0.3 -0.42 -0.4

Net export demand elasticity -1.62 -2.0 -0.614 n.a.

ROW supply elasticity 0.15 0.05 0.3 0.6

ROW demand elasticity -0.13 -0.09 to -0.14 -0.07 -0.4

South America supply elasticity n.a. n.a. n.a. 1.0

South America demand elasticity n.a. n.a. n.a. -0.4

-----------------------------Percent----------------------------------

Efficiency of technology 

transfer to ROW 50-100 0 100 100

n.a.= Not applicable. ROW = Rest of the world. 1 By the nature of a step supply function, the U.S. supply elasticity is perfectly inelastic for small price changes.
Key parameters affecting these shares include specification of the analytical framework, supply and demand

elasticity assumptions, farm-level effects, and yearspecific variables (table 3). In terms of farm-level

effects, the lack of yield advantage for herbicide-tolerant soybeans assumed by Moschini et al. contributed

to a 20-percent share of the estimated benefits for U.S.

farmers. This share increased to 29 percent (under the

higher supply elasticity assumption) when a 13-percent increase in adopters’ yields was assumed for the

Corn Belt (Falck-Zepeda et al., 2000a).

Producers directly benefit from the adoption of biotech

crops through potentially higher yields and savings in

pest control costs. Consumers may also benefit

through lower commodity prices. Most studies found

that U.S. consumers received no more than 10 percent

of the estimated total benefits, though Frisvold et al.

reported 33 percent.

On a net basis, the rest of the world generally obtained

a small portion of estimated benefits from biotech

adoption in the United States. However, some studies

report benefit shares of 18-28 percent for the rest of

the world when both producer and consumer benefits

are considered. ROW consumers gain from the worldwide adoption of biotech crops because of lower commodity prices, and their surplus gains always exceed

the losses of ROW producers in previous studies.

Producers in other countries realize welfare losses primarily for two reasons: (1) widespread production of

conventional varieties in the rest of the world without

the yield advantages and/or cost savings associated

with biotech crops, and (2) exposure to lower prices

caused by the rapid adoption of biotech crops in the

United States.

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 7

Table 3—Benefits and their distribution from previous related studies

Study Year Total

benefits Share of the total benefits

U.S. farmers Innovators U.S. consumers Net ROW

$ million Percent

Bt cotton

Falck-Zepeda et al.( 1999) 1996 134 43 47 6 4

Falck-Zepeda et al. (2000b) 1996 240 59 26 9 6

Falck-Zepeda et al. (2000a) 1997 190 43 44 7 6

Falck-Zepeda et al. (1999) 1998 213 46 43 7 4

Frisvold et al. 1996-98 131-164 5-6 46 33 18

EPA1 1996-99 16.2-45.9 n.a. n.a. n.a. n.a.

Herbicide-tolerant soybeans

Falck-Zepeda et al. 1997-Low elasticity2 1,100 77 10 4 9

(2000a) 1997-High elasticity3 437 29 18 17 28

Moschini et al. 1999 804 20 45 10 26

n.a. = Not applicable. ROW = Rest of the world.

1 Limited to U.S. farmers' benefits.

2 Assumes a low U.S. soybean supply elasticity of 0.22.

3 Assumes a high U.S. soybean supply elasticity of 0.92.
The size and distribution of benefits from the adoption

of biotech crops have been subjects of public debate

since the crops’ commercialization in the mid-1990s.

While many studies have investigated these issues,

their results vary. The purpose of this study is to

explain how variability in specific factors can lead to

differences in the reported benefits. 

To measure the economic benefits resulting from the

adoption of biotech crops, one must consider potential

yield enhancements, savings in pest control costs, and

efficiency of technology transfer to ROW producers—

all in the context of supply and demand in the U.S.

and global market. The farm-level effects associated

with biotechnology shift the commodity supply curve

to the right (i.e., more supply at a given price). With a

given demand, this shift leads to a reduction in the

price of the commodity. The theoretical framework

employed in this study measures the change in

Marshallian surplus in the output market resulting

from the adoption of biotech crops. The model also

captures monopoly profits accruing to technology

innovators in the seed input market.

Moschini and Lapan Model

Moschini and Lapan provided a framework for modeling welfare changes where a new technology results in

production cost savings and the innovator enjoys intellectual property rights (IPR) protection. This model

serves as the theoretical foundation for this study. In

the case of biotech crops in the United States, IPR protection is typically enforced through licensing agreements between the innovators and producers.

In the Moschini and Lapan model, an input firm develops a new technology. Through patent protection or

trade secrecy, the innovator acquires a temporary

monopoly, thus allowing the firm to set the input’s price

above its marginal cost of production. The introduction

of this new input does not affect the purely competitive

nature of the output market. An important contribution

of the Moschini and Lapan model is that—unlike previous studies of public agricultural innovations, such as

those cited by Alston et al.—its welfare measurement

includes monopoly profits occurring in the input market

that are induced by IPR protection.

The new technology requires fewer inputs than the old

technology to produce the same level of output. In other

words, the innovation increases production efficiency. To

characterize this gain, Moschini and Lapan used a scaling factor to express the more efficient input as a fraction

of the pre-innovation input. The increase in efficiency

can also be translated into a reduction in input price. 

Moschini and Lapan developed output supply and

input demand functions under the hypothesis that,

given input and output prices, producers maximize

profit. Producers adopt the new technology if the perunit cost reduction is greater than the price differential

between the two technologies.

The price of the new input depends, in part, on the

demand for the commodity in the output market.

Moschini and Lapan assumed that the output market is

competitive. The interaction of output supply (S0) and

demand (D) results in the equilibrium price (P0) and

quantity (Q0) when only the old technology is available (fig. 3). Since the new technology is more efficient and yields more output with the same amount of

inputs, the supply curve shifts to the right (denoted by

S1). The equilibrium price and quantity with the new

technology are P1 and Q1.

It is assumed that the old input is supplied in the input

market at marginal cost, MC0 (fig. 4). Prior to the

8 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA

Theoretical Framework

Figure 3

Effect of introducing a more efficient technology 

in the output market

B

S1

D

S0

E

P0

P1

A

F

Q0 Q1

Quantity

 Price
introduction of the new technology, the input is priced

at MC0 if the input market is competitive. In that case,

the equilibrium demand is xc. Because the firm faces a

downward-sloping derived demand curve (DD), it is

able to price the new input above its marginal cost. If

the firm acts as a monopolist with the old technology,

the optimal usage (xo) is determined at the intersection

of the marginal revenue (MR) curve and MC0, with

the equilibrium price being w0. 

With the introduction of the new technology, the marginal cost falls to MC1 due to the efficiency gain.

Because the firm is protected through IPR, the monopolist maximizes profit by producing the input quantity

x1 at the equilibrium price w1. This theoretical framework postulates that the competitive market structure

for the traditional input does not affect the price

charged by the monopolist for the new input.

Because of the firm’s price-setting ability, the monopolist retains a portion of the surplus, with the remainder

being passed on to producers and consumers in the output market (Huffman). Total welfare must be measured

in both the output and input markets in order to account

for surpluses accrued to producers and consumers as

well as the monopoly profits induced by IPR. Thus, the

total change in social welfare due to the introduction of

the innovation comprises two components: (1) the

change in Marshallian surplus in the output market, and

(2) the monopolist’s profit in the input market. The

equivalent change in Marshallian surplus in the input

market is represented by the area (e+f+g+h), which is

the difference between the Mashallian surpluses in the

competitive, pre-innovation market—area (a+b+d)—and

the monopolistic, post-innovation market structure—

area (a+b+d+e+f+g+h). Producers’ welfare increases in

the input market due to the higher efficiency of the new

input. Consumers also benefit from the new technology

through increased output and lower commodity prices.

Thus, the change in Marshallian surplus is shared

among producers and consumers. The change in

Marshallian surplus in the input market is identical to

that in the output market, which is denoted by area

ABEF in figure 3. The monopolist’s profit is denoted by

the area (i+j+k+m+n) in figure 4.

Several conclusions can be drawn from Moschini and

Lapan’s conceptual model. First, to measure total welfare, one must estimate traditional Marshallian surplus

and then add the value of the change in monopoly profits induced by the innovation. Monopoly profits help the

innovator to recover research and development expenditures, which can be costly in the case of biotech crops.

Without these profits, few incentives to develop these

technologies would exist. Second, Marshallian surplus

can also be estimated from the derived demand function

for the input or from the supply function for the output.

Third, for empirical applications, one must determine

whether market power existed prior to the innovation in

order to determine if the measurement procedure

described above is appropriate.

This theoretical framework suggests that firms increase

research and development expenditures if IPRs are welldefined and firms are assured a minimum market size.

On the other hand, firms that attempt to extract too

much surplus by overpricing inputs may attract competitors or limit their market shares by discouraging

adoption of the new technologies. The adoption of new

technologies depends on whether the expected additional revenues from greater per-unit output and/or

lower input costs outweigh the higher cost of the innovation, including technology fees.

Empirical Model

Alston et al. developed a methodology for calculating

Marshallian surplus. Their framework is well established

in the economics literature and allows research-induced

benefits generated in an output market to be partitioned

between producers and consumers. Falck-Zepeda et al.

(2000b) modified the approach of Alston et al. to

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 9

Figure 4

Drastic innovation in the input market

i DD j

n

k

a

b

d

f

e g

m

h

MR

MC1

MC0

X0 Xc X1

X

w1

w0

w
account for monopoly profits induced by IPR protection

in the input market, as suggested by Moschini and

Lapan. This is the empirical model used here.

The modified framework characterizes a large, open

U.S. economy, as well as technological transfer to the

rest of the world. This model structure allows for trade

between the United States and the rest of the world

and assumes that the United States can significantly

affect world prices through its exports. The framework

postulates that commodity supply and demand functions can be modeled using linear equations. Details of

the model structure are in Appendix A.

Biotech crops potentially offer yield increases and savings in pest control costs, which may improve profitability. Per-acre yield enhancements are converted to

a per-ton cost savings by dividing the yield changes by

the U.S. supply elasticity (Alston et al.). Changes in

per-acre pest control costs are converted to a per-ton

basis by dividing them by one plus the per-acre yield

change caused by biotechnology. These farm-level

benefits typically come at a higher cost through technology fees charged by biotechnology developers and

seed premiums levied by seed companies. The net

change in input costs associated with biotech adoption

is the sum of the equivalent per-ton cost savings from

yield enhancements and pest control minus the technology fees and seed premiums. This change leads to a

shift in the supply curve and is represented by the vertical distance between the pre-innovation and postinnovation supply curves. 

If biotech crops are not available to ROW producers,

only the U.S. supply curve moves. On the other hand,

if biotech crops are available worldwide, then both the

U.S. and ROW supply curves shift to the right. The

extent to which the ROW supply curve shifts to the

right depends on the efficiency of technology transfer

to ROW producers. If they realize the same yield

enhancements, savings in pest control costs, and innovation fees as U.S. farmers, the vertical supply shift in

the two regions will be the same. In contrast, if ROW

producers realize only half of the net efficiency gains

as U.S. farmers, the vertical supply shift will be half as

large as in the United States.

Once a new technology is introduced and adopted,

only the world price that results from the supply shift

can be observed. It is not possible to observe the counterfactual price—the price that would have existed,

assuming the same supply and demand conditions, if

biotechnology had not been introduced. Estimated

changes in stakeholders’ welfare are made by comparing their surpluses that arise with and without the

innovation. The base case reflects the observed market

supply and demand as well as the resulting equilibrium price with the introduction of the innovation. The

supply shift is calculated based on the net cost savings

due to yield enhancements and lower pest control costs

for adopters after accounting for technology fees and

seed premiums paid to the innovators. The counterfactual world price, which reflects the equilibrium world

price without the innovation, is the sum of the

observed market price and the vertical supply shift.

The equilibrium world price occurs at the intersection

of the excess supply and excess demand curves (fig.

5). (For simplicity, figure 5 assumes no technological

transfer to the rest of the world. While the empirical

results would differ without this assumption, the

approach for measuring surplus changes for producers

and consumers remains the same.) The pre-innovation

excess supply curve is denoted by ESUS, 0, while the

post-innovation supply curve is ESUS, 1. The excess

supply curve maps the horizontal difference between

the U.S. supply (SUS, 0 in the case of ESUS, 0 and SUS, 1

for ESUS, 1) and demand (DUS) curves at every price

above the domestic equilibrium price. Similarly, the

excess demand curve (ED) is a locus of points indicating the horizontal difference between the ROW

demand (DROW, 0) and supply (SROW, 0) curves at every

price below the ROW equilibrium price. Before the

introduction of the technology, the equilibrium world

price is P0, but falls to P1 because the introduction of

the innovation causes a rightward shift in supply. The

quantity traded in the post-innovation market (QT1) is

determined at the intersection of the excess supply

(ESUS,1) and excess demand (ED) and equals the volume exported by the United States and imported by

the rest of the world. The quantity traded in the preinnovation market is computed in the same manner.

U.S. consumer welfare prior to the introduction of

biotechnology is bounded by the area below the demand

curve (DUS) and above the counterfactual world price,

P0. The innovation increases U.S. consumer surplus due

to the decline in the world price. The new U.S. consumer surplus becomes a larger triangular area, including the pre-innovation U.S. consumer surplus plus the

hashed area between P0 and P1. Thus, the change in

U.S. consumer surplus is denoted by the hashed area.

The formula for computing the change in U.S. consumer surplus is included in Appendix A.

10 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA
U.S. producer surplus prior to the introduction of

biotechnology is represented by the area below P0 and

above the pre-innovation supply curve, SUS, 0. After

the innovation, U.S. producer surplus becomes the area

below P1 and above the post-innovation supply curve,

SUS, 1. The change in U.S. producer welfare is the area

between the two supply curves below P1 minus the

area between P0 and P1 above the pre-innovation supply curve. With the assumptions of linear supply and

demand curves as well a parallel shift in supply, this

change is identical to the green area in the U.S. panel

(fig. 5; Alston et al.).

Monopoly profits accruing to the innovators depend, in

part, on the technology fees and seed premiums

charged to farmers in the United States and ROW. The

firms’ profits also hinge on the rate at which biotech

crops are adopted. While it is possible to estimate the

gross revenues realized by the innovators, it is difficult

to measure the monopoly profits obtained from

biotechnology. First, the agreements between the

biotechnology developers and germplasm suppliers are

typically confidential, so it is nearly impossible to

account for the revenue-sharing schemes agreed upon

by the companies. Second, revenue estimates do not

consider certain variable costs, such as those associated with administrative, marketing, and IPR enforcement activities. Third, the characterization of research

and development costs as either variable or sunk costs

is problematic in the calculation of monopoly profits.

In this study, monopoly profits are estimated using

information on technology fees and seed premiums,

acreage planted to biotech crops, and company reports

concerning their licensing agreements (Falck-Zepeda

et al., 2000b). This analysis excludes the above variable expenses, and hence, might overstate the innovators’ profits.

In this study, an empirical model is applied to the

adoption of Bt cotton as well as herbicide-tolerant soybeans and cotton in 1997. That year was selected due

to the availability of ARMS data on the farm-level

effects of biotech and conventional varieties. The

United States had a significant presence in the global

cotton and soybeans markets—21 percent and 46 percent of world production and 28 percent and 59 percent of world trade in 1997 (USDA, 2000c and

2001c). Technology transfer to ROW producers was

incorporated in the framework because two of the

three biotech crops were commercially available outside of the United States—Mexico and Australia in the

case of Bt cotton and Argentina and Canada for herbicide-tolerant soybeans (James).

To determine the size and distribution of benefits realized by U.S. farmers, U.S. consumers, technology

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 11

Marshallian surplus distribution

Figure 5

P P P

P0

P1

United States Quantity Traded ROW

SROW, 0

DROW, 0

ES US, 0

ES US, 1 SUS, 0

SUS, 1

CUS, 0 CUS, 1 QT0 QT1 QROW, 0

QT0

QT1

QT0

QT1

U.S. producer

surplus change

U.S. consumer

surplus change

ROW consumer

surplus change

Net ROW

surplus change

DUS

ED

QUS, 0 QUS, 1 QROW, 1 CROW, 0 CROW, 1

ROW producer

surplus change
innovators, and ROW consumers and producers, the

following steps were applied:

(1) Estimate the technology-induced supply shift

for each commodity-producing region using

data on adoption rates, crop yields, and savings in pest control costs net of technology

fees and seed premiums; 

(2) Calculate the impacts of the new technologies

on world and regional prices; and

(3) Estimate the changes in the Marshallian surpluses in the United States and ROW and partition them between producers and consumers.

Profits for biotechnology developers and seed companies are determined outside of the above framework.

Data on adoption rates, technology fees, and seed premiums are key to determining innovators’ profits.

These variables are fixed in the base case.

12 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA
Benefits to producers from adopting biotech crops can

be represented by a shift in supply, reflecting potential

increases in crop yields and/or savings in pest control

costs. U.S. and ROW consumers indirectly benefit

from biotech adoption because increased crop supplies

lower commodity prices. Because the technologyinduced supply shift affects the surpluses of both producers and consumers, accurate information is needed

about biotechnology’s farm-level impacts.

This section details the impacts of biotechnology on

crop yields and pest control costs. These estimated

benefits are only a subset of the entire economic

impact of biotechnology. Changes in pesticide use

attributed to the adoption of biotechnology do not capture all the potential environmental and health impacts.

Other benefits not covered include the ease of pest

management associated with herbicide-tolerant crops

and the insurance value against the potential infestation of targeted pests for Bt cotton (Fernandez-Cornejo

and McBride, 2002).

Data Sources

Potential increases in crop yields and savings in pest

control costs associated with the adoption of biotechnology are difficult to quantify. This section discusses

two data sources that were used to measure the farmlevel effects employed in this study.

Producer surveys are a primary data source for measuring differences in crop yields and pest control costs

between adopters and nonadopters of a given biotech

crop (e.g., Falck-Zepeda et al., 2000b). Survey data

reflect actual producer costs associated with the use of

each crop production technology. Moreover, survey

data can be used to show frequency distributions of

crop yields and pest control costs for adopters and

nonadopters separately, as well as associated statistics,

such as mean values and standard deviations.

The Agricultural Resource Management Survey

(ARMS), a nationwide USDA producer survey, has

been used by some researchers to quantify the farmlevel impacts of biotechnology (Falck-Zepeda et al.,

2000a). Farm financial and chemical use data are

reported for all crops in the ARMS survey each year,

while detailed enterprise production practices and cost

data are collected for several commodities (including

soybeans and cotton) on a rotating basis every 4 to 7

years (McBride).6

According to McBride, four characteristics of the

ARMS data make it useful for assessing the farm-level

impacts of biotech adoption. First, the ARMS has broad

coverage, including all of the major producing States

for a given commodity—generally more than 90 percent

of the crop acreage. Second, ARMS uses a stratified

random sample, where each farm represents a known

number of similar farms in the population, based on

sampling probabilities. Each farm is weighted by the

number of farms it represents so that the ARMS sample

can be expanded to reflect the targeted population.

Third, ARMS enterprise cost-of-production data contain

sufficient detail about specific inputs to isolate seed and

pest control costs associated with commodity production. Finally, since enterprise cost-of-production data

can be obtained for each responding farm, a distribution

of costs can be developed. 

An alternative to using producer survey data is to rely

on State enterprise cost-of-production budgets estimated by State extension programs at land-grant universities. These budgets for biotech and conventional

crop varieties are relatively inexpensive to obtain and

can be easily modified for use in research applications

(e.g., Duffy and Vontalge). One advantage of using

these data is that factors other than the choice of crop

variety can be controlled in order to isolate the cost

difference between the two technologies (McBride).

However, these data may not be representative of the

entire farm population because input and output levels

often reflect above-average management. In addition,

State budgets are location specific, mainly for a State

or a portion of a State, thus making it difficult to represent a broad population and/or geographic area.

More important, enterprise budgets are typically not

comparable across States because of inconsistencies in

design and the inclusion of biotech crops. In fact,

many States do not differentiate their enterprise budgets between biotech and conventional varieties.

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 13

Farm-Level Effects on Crop Yields and Pest Control Costs

6 The 1997 ARMS data are used in this study because these are the

latest available information on cotton and soybeans.
In this study, farm-level impacts resulting from

biotech adoption are estimated from ARMS data—

hereafter called “estimated ARMS effects”—using an

econometric procedure that excludes the effects of

other factors (Fernandez-Cornejo et al.; FernandezCornejo and McBride). The econometric model

accounts for the fact that farmers’ adoption of

biotechnology and pesticide use decisions may be

simultaneous. In addition, the model corrects for selfselectivity to prevent biased results. Self-selection

arises because farmers are not assigned randomly to

one of the two groups (i.e., either adopters or nonadopters). Instead, they make the adoption choices

themselves. Therefore, adopters and nonadopters may

be systematically different, and these differences may

manifest themselves in farm performance, which

could confound the effect of biotech adoption.

Results of the econometric model are expressed in elasticity form. In terms of the impact on crop yields, the

adoption of herbicide-tolerant soybeans has a small but

positive and significant effect. U.S. herbicide-tolerant

soybean yields in 1997 were estimated to have increased

by less than 1 percent for a 10-percent increase in adoption (Fernandez-Cornejo and McBride). This yield effect

is generally consistent with other studies (Gianessi and

Carpenter, 2000; Carpenter and Gianessi, 1999b, 2000;

Moschini et al.; Duffy and Vontalge). For Bt cotton in

the Southeast and herbicide-tolerant cotton nationwide,

yields in 1997 were estimated to have increased by 1 to

5 percent for a 10-percent increase in adoption

(Fernandez-Cornejo and McBride).

The impact of biotech adoption on pesticide use, based

on this econometric model, varies by commodity and

across active ingredients. An increase in the adoption

of herbicide-tolerant soybeans was estimated to have

led to a statistically significant reduction in the use of

herbicides other than acetamides and glyphosate,

which fell 1.4 percent for a 10-percent increase in

adoption in 1997 (Fernandez-Cornejo et al.). In contrast, the adoption caused a significant increase in

glyphosate use, which rose 4.3 percent for a 10-percent increase in adoption. The change in acetamides

was not statistically significant.

For each herbicide active ingredient, the rate of application and the share of area applied vary by region.

Thus, the change in herbicide use by category (e.g.,

acetamides and other herbicides) differed across production regions. The net effect of an increase in

biotech adoption on herbicide use depended on the

extent to which the decrease in the use of other herbicides offset the increase in glyphosate use.

An increase in the adoption rate of Bt cotton did not

lead to a significant change in the use of organophosphate and pyrethroid insecticides (Fernandez-Cornejo

et al.). However, a 10-percent increase in adoption led

to a 2.1-percent decrease in the use of other insecticides in the Southeast, which was statistically significant. Thus, the net effect of an increase in the adoption

of Bt cotton in that region was a decrease in total

insecticide use. The change in herbicide use nationwide associated with the adoption of herbicide-tolerant

cotton was not statistically significant.

Other data sources for quantifying the farm-level

impacts of biotech adoption are databases maintained

by private firms. For example, in their study of 1997

Bt cotton, Falck-Zepeda et al. (2000a) used the comprehensive Enhanced Market Data II, or EMD (Plexus

Marketing Group, Inc., and Timber Mill Research,

Inc.). These data were derived from surveys in which

cotton consultants provided agronomic and pest management information on matched pairs of Bt and nonBt cotton fields in the same locations. To ensure

similarity, the matched pairs of fields were carefully

selected so that they represented equivalent agronomic

practices and productivity. The EMD covers fields in

Alabama, Arkansas, Georgia, Louisiana, Mississippi,

North Carolina, South Carolina, and east Texas. Like

the estimated ARMS effect in the Southern Seaboard,

the EMD isolates the impacts of biotechnology on

crop yields and pest control costs.

Estimated Impacts on Crop Yields

To truly calculate farm-level effects of biotech crops,

one must discern the difference in crop yields

(between adopters and nonadopters) that is attributable

to the technology. This section discusses the impact on

crop yields across the two data sources: (1) the estimated ARMS effects based on the econometric model

for all three biotech crop varieties, and (2) the EMD

database, which is applicable only to Bt cotton produced in the Southeast. The impact of adopting Bt cotton on crop yields, based on 1 year of data (1997),

appears to vary significantly across the two data

sources and production regions. In the Southern

Seaboard, yields for Bt cotton adopters are estimated

to have been higher than for nonadopters in both data

sources, as shown in table 4 (see figure 6 for ERS crop

14 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA
production regions).2 For example, according to the

estimated ARMS effects, Bt cotton adopters’ yields in

the Southern Seaboard averaged about 847 pounds per

acre, compared with 700 pounds for nonadopters, a

21-percent advantage.

The estimated ARMS effect indicates a 17-percent

increase in yields for herbicide-tolerant cotton

adopters nationwide. In some regions, herbicide-tolerant cotton yields may have been lower than for conventional varieties. In particular, farmers in the

Mississippi Portal encountered serious and unexpected

problems with their herbicide-tolerant cotton during

the 1997 growing season (Virginia Cooperative

Extension). Some growers found deformed bolls and

bolls that dropped off the plants. About 20 percent of

the region’s herbicide-tolerant cotton was affected.

However, the problems may have been caused by factors other than the herbicide-tolerant technology itself,

such as soil type and weather conditions.

For herbicide-tolerant soybeans, the estimated ARMS

effect indicates only 3-percent higher yields for

adopters nationwide, which is consistent with other

studies’ findings that the adoption of herbicide-tolerant

soybeans has little or no overall impact on soybean

yields (Gianessi and Carpenter, 2000; Moschini et al.).

The negligible yield effect is consistent with the argument that the simplicity and flexibility in pest management programs are key drivers of the rapid adoption of

herbicide-tolerant soybeans (Fernandez-Cornejo and

McBride, 2002).

Estimated Impacts on Pest 

Control Costs

Impacts of Bt and herbicide-tolerant technologies on

cotton and soybean pest control costs include expenses

associated with pesticide materials, application, scouting, and cultivation. Pest control costs for Bt cotton

adopters were lower than for nonadopters in 1997.

Regional differences in pest control cost savings were

quite large, depending on the data source. For example,

adopters’ pest control costs averaged about 7 percent

lower than for nonadopters in the Southern Seaboard,

based on the estimated ARMS effects (table 5). These

savings reached as high as 60 percent (based on the

EMD) in the Southern Seaboard and 54 percent in the

Mississippi Portal. While both data sources isolate the

impact of biotechnology on insect-control costs, the

divergent estimates are hard to reconcile. Computing the

benefits from biotech adoption with the EMD is likely

to result in much larger estimated benefits for U.S.

farmers than with the estimated ARMS effects.

The estimated ARMS effect for pest control costs in

the Southern Seaboard was calculated using elasticities

that reflect the percentage change in pesticide use in

response to a 1-percent increase in the adoption of

biotech crops (Fernandez-Cornejo et al.). To illustrate,

the first step is to estimate the expenses associated

with pesticide active materials, ingredient by ingredient, used by nonadopters in a specific production

region, such as the Southern Seaboard in the case of

Bt cotton. Based on USDA’s State-level chemical use

data, the insecticide application rate per crop year and

the percent of area applied with insecticides were tabulated by insecticide active ingredient at the regional

level, as shown in table 6 (USDA, 1998a). 

Insecticide active ingredients were grouped into three

categories: organophosphates, pyrethroids, and other

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 15

7 No estimated ARMS effects are available for Bt cotton yields in

other production regions.

Table 4—Impact of adopting Bt cotton on crop

yields by region and by data source, 1997

Data source

Production region Estimated ARMS effect EMD

Percent

Southern Seaboard +21.0 +11.3

Fruitful Rim n.a. n.a.

Mississippi Portal n.a. + 3.7

Eastern Uplands n.a. n.a.

n.a. = Not applicable. EMD = Enhanced Market Data II.

Sources: Estimated ARMS effects adapted from Fernandez-Cornejo

et al. EMD obtained from Plexus Marketing Group, Inc., and Timber

Mill Research, Inc.

Table 5—Impact of adopting Bt cotton on pest 

control costs by region and by data source, 1997

Adopters' differences in pest 

control costs from nonadopters

Production region Estimated ARMS effect EMD

Percent

Southern Seaboard -7.08 -60.0

Fruitful Rim n.a. n.a.

Mississippi Portal n.a. -54.3

Eastern Uplands n.a. n.a.

n.a. = Not applicable. EMD = Enhanced Market Data II.
insecticides. Price data for insecticide active ingredients were obtained from USDA (1998c) and a database of 1996 prices developed by Gianessi and

Marcelli, with some necessary conversions from the

prices of final product to those of active-ingredient

equivalents. 

Multiplying the active ingredient prices by the individual

weighting factors (application rate per crop year times

the share of area applied) gives the per-acre expenses

associated with each active ingredient for nonadopters.

Adding up the per-acre expenses across active ingredients results in the total expense associated with insecticides—$20.48 per acre for nonadopters of Bt cotton in

the Southern Seaboard. Including expenses for pesticide

application, scouting, and cultivation (taken from the

ARMS) increased the total insect control cost to $27.92

per acre for nonadopters in 1997.

Insecticide costs for adopters are estimated by accounting for potential savings in insecticide use, ingredient by

ingredient. In the Southern Seaboard, the -0.21 elasticity

for “other insecticides” means that adopters’ use of those

materials was 21 percent lower than for nonadopters.

Expenses associated with the “other insecticides” were

$1.86 per acre lower for adopters in 1997 (table 6). No

change occurred in the use of organophosphates and

pyrethroids. In total, expenses for all insecticides equaled

16 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA

ERS crop production regions

Figure 6

Basin and Range

Fruitful Rim Prairie Gateway Mississippi Portal Southern Seaboard Eastern Uplands

Largest share of nonfamily

farms, smallest share of 

U.S. cropland.

4% of farms, 4% of value

of production, 4% of cropland.

Cattle, wheat, and sorghum

farms.

Northern Great Plains Heartland Northern Crescent

Largest farms and smallest 

population.

5% of farms, 6% of value of

production, 17% of cropland.

Wheat, cattle, and sheep farms.

Most farms (22%), highest 

value of production, (23%), 

and most cropland (27%).

Cash grain and cattle farms.

Most populous region.

15% of farms, 15% of value

of production, 9% of cropland.

Dairy, general crop, and cash

grain farms.

Largest share of large 

and very large family 

farms and nonfamily farms.

10% of farms, 22% of value

of production, 8% of cropland.

Fruit, vegetable, nursery, and 

cotton farms.

Second in wheat, oat, 

barley, rice, and cotton 

production.

13% of farms, 12% of 

value of production, 

17% of cropland.

Cattle, wheat, sorghum, 

cotton, and rice farms.

Higher proportions of 

both small and larger farms 

than elsewhere.

5% of farms, 4% of value

of production, 5% of 

cropland.

Cotton, rice, poultry, and

hog farms.

Mix of small and larger 

farms.

11% of farms, 9% of value

of production, 6% of 

cropland.

Part-time cattle, general 

field crop, and poultry farms.

Most small farms of any

region.

15% of farms, 5% of 

value of production, and 

6% of cropland.

Part-time cattle, tobacco,

and poultry farms.
$18.62 per acre for adopters, about 9 percent lower than

for nonadopters. Including expenses for insecticide

application and scouting brought the total pest control

cost to $26.03 per acre for adopters, a savings of about 7

percent over nonadopters.

Herbicide-tolerant cotton shows no statistically significant impact on herbicide use nationwide, according to

the estimated ARMS effect. However, adopters of this

technology did realize gains through lower total weed

control costs. Adopters in the Southern Seaboard,

Mississippi Portal, and Prairie Gateway experienced a

savings of 5-46 percent due to lower application, cultivation, and scouting expenses.

Similar to Bt cotton, weed control costs for herbicidetolerant soybean adopters were lower than for nonadopters in 1997 (table 7). The savings realized by

adopters ranged from about 1 percent to as much as 34

percent across production regions. This cost reduction is

much smaller than in the study by Moschini et al. for

1999, which ranged from 49 percent to 66 percent

(based on a reduction of $20 per hectare), depending on

the number of additional glyphosate treatments applied.

Estimated ARMS effects for regional weed control

costs are calculated in the same manner as for Bt cotton employing herbicide use elasticities (FernandezCornejo et al.). A 1-percent increase in adoption leads

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 17

Table 6—Insecticide costs for Bt cotton adopters versus nonadopters: Southern Seaboard, 1997

Insecticide active Rate per Area Weight Price Cost for Cost for

ingredient crop year applied nonadopters adopters

lb. per acre Percent lb. per acre $ per lb. $ per acre

Organophosphates

Malathion n.a. n.a. n.a. 4.820 n.a. n.a.

Methyl parathion n.a. n.a. n.a. 6.825 n.a. n.a.

Acephate 0.290 6.451 0.019 17.067 0.319 0.319

Phorate 0.833 9.828 0.082 10.700 0.876 0.876

Profenofos 0.633 1.963 0.012 12.400 0.154 .154

Dicrotophos 0.038 4.010 0.002 11.075 0.017 0.017

Subtotal 1.212 1.212

Pyrethroids

Cypermethrin 0.128 10.303 0.013 91.636 1.204 1.204

Lambdacyhalothrin 0.062 42.758 0.027 231.270 6.157 6.157

Cyfluthrin 0.066 16.467 0.011 239.500 2.599 2.599

Zeta-cypermethrin 0.029 3.925 0.001 186.667 0.216 0.216

Tralomethrin 0.025 3.434 0.001 275.280 0.232 0.232

Fenpropathrin n.a. n.a. n.a. 78.030 n.a. n.a.

Subtotal 10.408 10.408

Other insecticides

Aldicarb 0.716 43.327 0.310 24.667 7.654 6.047

Chlorpyrifos n.a. n.a. n.a. 12.68 n.a. n.a.

Oxamyl n.a. n.a. n.a. 386.25 n.a. n.a.

Endosulfan n.a. n.a. n.a. 13.03 n.a. n.a.

Dicofol n.a. n.a. n.a. 29.14 n.a. n.a.

Methomyl 0.319 3.365 0.011 26.519 0.284 0.225

Disulfoton 0.277 3.487 0.010 9.538 0.092 0.073

Esfenvalerate 0.043 5.993 0.003 224.242 0.581 0.459

Thiodicarb 0.378 3.925 0.015 16.620 0.246 0.195

Subtotal 8.858 6.997

Total insecticide costs 20.478 18.618

Application costs 3.185 2.653

Scouting costs 4.261 4.761

Total per-acre insect control costs 27.924 26.032

n.a. = Not applicable

Sources: Gianessi and Marcelli; USDA 1998a, 1998c.
to a 0.43-percent increase in glyphosate use but a 0.14-

percent decrease in the use of other synthetic herbicides. Expenses associated with the use of glyphosate

were about $1.16 per acre higher for adopters in the

Heartland (table 8). However, the decline in expenses

associated with the use of other herbicides—$3.40 per

acre—more than offset the increase in expenses for

glyphosate. As a result, adopters’ expenses for all herbicides totaled $25.64 per acre, versus $27.89 for nonadopters. Adopters of herbicide-tolerant soybeans in

the Heartland are estimated to have realized a 10.7-

percent ($3.50 per acre) savings in weed control costs

when application, scouting, and cultivation expenses

are considered along with herbicide costs.

Implications for Pesticide Use

Biotechnology led to reductions in pesticide use for Bt

cotton in the Southern Seaboard, herbicide-tolerant

cotton nationwide, and herbicide-tolerant soybeans in

some major production regions. However, the reduction in pesticide use itself does not accurately measure

total direct benefits to the environment and human

health. Measuring herbicide use in pounds of active

ingredients implies that, on a pound-for-pound basis,

two ingredients have equal impacts. But in the case of

herbicide-tolerant soybeans, other herbicides are

replaced by glyphosate, which is less toxic and persistent than other herbicides (Heimlich et al.).

For Bt cotton, adoption clearly reduces insect control

costs, but it also lowers the use of some insecticide

active ingredients. While there is no compelling evidence showing that adopters’ use of organophosphates

and pyrethroids was lower, their use of “other insecticides” is estimated to be 21 percent lower than for

nonadopters.

In contrast, the impact of adopting herbicide-tolerant

soybeans on herbicide use is not as clear. While herbicide-tolerant soybeans lowered the use of “other herbicides” by 14 percent for adopters, adopters used 43

percent more glyphosate. Since average application

rates vary across herbicide active ingredients, the net

effect of substituting one herbicide for another may lead

to an increase or a decrease in the total pounds of active

ingredients used. Our analysis shows that the impact of

adopting herbicide-tolerant soybeans on pesticide use

was mixed—a net decline in the Heartland and Prairie

Gateway but an increase in all other regions. Overall,

the impact of herbicide-tolerant soybeans is a 3-percent

increase in herbicide use (measured in pounds of active

ingredients) nationwide in 1997.

The decline in herbicide use (in terms of active ingredients applied) for herbicide-tolerant soybean adopters in

1997 was limited to selected regions, ranging from 1.6

percent in the Heartland to 3.3 percent in the Prairie

Gateway. For example, the use of glyphosate increased

from 0.19 pound per acre for nonadopters to 0.27 pound

per acre for adopters in the Heartland (table 8). In contrast, the use of “other herbicides” decreased from 0.70

pound per acre for nonadopters to 0.60 pound per acre

for adopters. The end result was a decline in the use of

all herbicides from 0.997 pound for nonadopters to

0.981 pound for adopters (a 1.6-percent reduction),

which was lower than the 10.7-percent decrease in weed

control costs for adopters. The increases in herbicide

use in other regions were as follows: 8.4 percent,

Northern Crescent; 11.7 percent, Mississippi Portal; and

10.9 percent, Southern Seaboard.

18 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA

Table 7—Impact of adopting herbicide-tolerant

soybeans on weed control costs, 1997

Production region Estimated cost savings

Percent

Heartland -10.65

Northern Crescent -12.21

Southern Seaboard -3.91

Northern Great Plains n.a.

Mississippi Portal -4.45

Prairie Gateway -0.89

Eastern Uplands -33.92

n.a.= Not available.

Source: Estimated ARMS effects.
Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 19

Table 8—Impact of herbicide-tolerant soybeans on herbicide use and weed control costs: Heartland, 1997

Herbicide use

Herbicide active Rate per Area Weight Price Cost for Costs for Nonadopters Adopters

ingredient crop year applied nonadopters adopters

lb. per Percent lb. per $ per lb. $ per acre lb. per acre

acre acre

Acetamides

Metolachlor 1.999 4.346 0.087 8.688 0.755 0.755 0.087 0.087

Alachlor 0.877 2.333 0.020 6.325 0.129 0.129 0.020 0.020

Subtotal 0.884 0.884 0.107 0.107

Glyphosate 0.710 26.807 0.190 14.175 2.699 3.860 0.190 0.272

Other herbicides

Pendamethalin 1.074 29.479 0.317 8.909 2.820 2.425 0.317 0.272

Trifluralin 0.739 19.591 0.145 7.850 1.137 0.978 0.145 0.125

Bentaton 0.613 9.532 0.058 19.075 1.115 0.959 0.058 0.050

Clomazone 0.566 4.199 0.024 19.900 0.473 0.407 0.024 0.020

2, 4-D 0.372 9.567 0.036 3.725 0.133 0.114 0.036 0.031

Acifluorfen 0.140 8.338 0.012 28.920 0.338 0.291 0.012 0.010

Metribuzin 0.204 10.083 0.021 36.933 0.759 0.652 0.021 0.018

Imazethapyr 0.052 42.563 0.022 315.900 7.005 6.024 0.022 0.019

Sethodydim 0.154 8.009 0.012 67.333 0.833 0.716 0.012 0.011

Chlorimuron-thyl 0.030 13.868 0.004 1142.770 4.770 4.102 0.004 0.004

Clethodim 0.078 4.362 0.003 108.990 0.371 0.319 0.003 0.003

Dimethenamid n.a. n.a. n.a. 14.23 n.a. n.a. n.a. n.a.

Fenoxaprop 0.123 6.893 0.009 165.400 1.407 1.210 0.009 0.007

Fluazifop-P-butyl 0.048 7.774 0.004 64.830 0.242 0.208 0.004 0.003

Flumetsulam 0.055 1.915 0.001 n.a. n.a. n.a. 0.001 0.001

Flumiclorac Pentyl 0.020 1.292 0.000 215.830 0.055 0.047 0.000 0.000

Fomesafen 0.169 6.442 0.011 36.340 0.397 0.341 0.011 0.009

Imazamox n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

Imazaquin 0.079 12.671 0.010 150.000 1.494 1.285 0.010 0.009

Lactofen 0.082 4.597 0.004 58.710 0.221 0.190 0.004 0.003

Linuron 0.053 0.089 0.000 24.000 0.001 0.001 0.000 0.000

Quizalofop-ethyl 0.035 2.533 0.001 143.190 0.128 0.110 0.001 0.001

Sulfentrazone n.a. n.a. n.a. n.a. n.a. n.a. n.a. n.a.

Thifensulfuron 0.003 9.645 0.000 2084.320 0.503 0.432 0.000 0.000

Paraquat 0.273 1.912 0.005 14.470 0.075 0.065 0.005 0.004

Subtotal other herbicides 24.276 20.877 0.698 0.600

Adjusted subtotal (account 

for missing other herbicides) 24.302 20.900 0.699 0.601

Total herbicide use 0.997 0.981

Total herbicide material costs 27.885 25.644

Application costs 3.338 2.875

Scouting costs 0.291 0.447

Cultivation costs 1.267 0.314

Total weed control costs 32.782 29.280

n.a. = Not applicable.

Sources: Gianessi and Marcelli; USDA 1998a, 1998c.
This study adopts the empirical model developed by

Falck-Zepeda et al. (2000b) to estimate the economic

gains for various stakeholders associated with the adoption of Bt and herbicide-tolerant cotton and herbicidetolerant soybeans. Potential yield enhancements and

savings in pest control costs are incorporated into models that derive each crop’s supply shift resulting from

biotechnology. Given domestic and export demands,

counterfactual world prices and quantities demanded of

the commodities—those that would have prevailed in

the market if biotechnology had not been introduced—

are determined from market equilibrium conditions.

Producer and consumer surpluses in the United States

and international markets are then estimated. Finally,

monopoly profits accruing to the biotechnology developers and germplasm suppliers are calculated.

Because the biotech crops considered in this study are

raw commodities, U.S. and ROW consumers include

final consumers as well as intermediate buyers. For

example, crushers buy soybeans to make soybean meal

and soybean oil. Soybean meal is then sold to feed

manufacturers as a protein supplement. Refined soybean oil can be used directly for food consumption or

sold to food manufacturers. Final consumers benefit

from buying products in which soybean meal and oil

were used as inputs in the production processes. Thus,

it is assumed that the price reduction caused by the

shift in supply from biotechnology is shared among

many buyers. The benefits to these buyers and final

consumers will go to those who are indifferent to

biotech versus nonbiotech foods.

Data and Assumptions

The empirical model makes use of data in which the

effects of biotechnology on crop yields and pest control costs are isolated. The estimated ARMS effects

were used in the cases of herbicide-tolerant cotton and

soybeans nationwide as well as Bt cotton in the

Southern Seaboard. Because of discrepancies in the

reported farm-level effects, the EMD were also used in

the analysis of Bt cotton (Southern Seaboard and

Mississippi Portal only). This private sector data

source provides another perspective on the likely range

of estimated surplus changes from adopting Bt cotton. 

The yield effects and changes in pest control costs

assumed in this study vary by region (and by data

source in the case of Bt cotton). This study considers

four production regions for cotton and seven for soybeans (tables 4 and 7). Based on the estimated ARMS

effects, 1997 Bt cotton yields were 21 percent higher

for adopters than for nonadopters in the Southern

Seaboard. The yield increase was smaller according to

the EMD, ranging from 4 percent to 11 percent.

Herbicide-tolerant cotton and soybean yields were 17

percent and 3 percent higher nationwide, according to

the estimated ARMS effects.

Adopters of Bt cotton in the Southern Seaboard realized pest control expenses that were 7 percent lower

than those of nonadopters, based on the estimated

ARMS effect, and 60 percent lower with the EMD. In

the case of herbicide-tolerant cotton, adopters’ savings

in pest control costs ranged from 5 percent to 46 percent. For herbicide-tolerant soybeans, the savings

ranged from 1 percent to 34 percent, depending on the

production region (table 7).

This study assumes that the efficiency of technology

transfer to ROW producers equals 50 percent for Bt

cotton and herbicide-tolerant soybeans. Technology

transfer for herbicide-tolerant cotton was not considered because this biotech variety was only available in

the United States in 1997.

Crop acreage data were obtained from USDA (1998b).

Regional adoption data, as well as seed prices, premiums, and technology fees, were taken from the ARMS.

Adopters’ pest control costs were derived from the

ARMS using pesticide use elasticities, application

rates, and chemical prices. Commodity prices were

estimated for each ERS crop production region using

weighted State price data (USDA, 1998c).

While our estimation of the stakeholders’ surpluses

relies heavily on the Falck-Zepeda et al. (2000b)

framework, a number of their assumptions were

altered to better reflect commodity flows and trade

patterns. Regional crop distribution data were used to

determine the shares of production allocated to domestic use and exports (Glade et al.; Larson et al.). In

addition, the assumption concerning the share of cotton imported by the rest of the world relative to its

production was modified using data on ROW produc20 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA

Estimating the Size and Distribution of Market Benefits
tion and imports from USDA’s World Agricultural

Supply and Demand Estimates (USDA, 2000c).

The assumptions made in this study concerning U.S.

and ROW supply and demand elasticities differ from

those in previous analyses (table 2). In this analysis,

regional domestic supply elasticities were taken from a

recent study by Lin et al. (2000), which reflect the policy and market environments of the 1997 crop year

(table 9). The U.S. cotton mill demand and net export

demand elasticities were obtained from studies by

Meyer and Duffy et al., respectively. The U.S. demand

and shortrun net export demand elasticities for soybeans

were estimated by Hyberg and Mercier. A longrun

export demand elasticity of -1.36 estimated by Uri et al.

supports the value reported by Hyberg and Mercier.

Like Falck-Zepeda et al. (2000a), the ROW supply elasticities were taken from a study by Sullivan et al. Given

the net export demand elasticities and ROW supply

elasticities reported in the literature, the theoretically

consistent ROW demand elasticities were computed for

soybeans and cotton (Houck).

Key variables, including crop yields and pest control

costs, were assigned probability distributions in this

study.8 Crop yields were assumed to be normally distributed. In any given season, some producers experience below-average yields while others achieve

above-average yields. Most producers, however, have

yields near the cross-sectional mean for a growing

season. Seed, herbicide/insecticide, scouting, application, and cultivation costs were assumed to be lognormally distributed—a distribution that best fits the

ARMS data. Including probability distributions in the

simulations does not significantly alter the results in

the cases of herbicide-tolerant cotton and soybeans.

In contrast, the total estimated benefit associated with

the adoption of Bt cotton is 2-3 percent higher with

the probability distributions.

Mean Values of Estimated Marshallian

Surplus Changes

Changes in Marshallian surplus estimates were computed using models that include data on regional

adoption rates, crop yields, seed costs (including technology fees and premiums), pest control costs, supply

and demand elasticities, commodity flows, and technology transfer to ROW producers. Welfare changes

were then estimated for farmers and consumers in the

United States and ROW (see Appendix A for mathematical details).

The models were simulated with a computer program,

@RISK, to account for the probability distributions

assigned to certain key variables. The software package randomly chose values from the probability distributions and calculated the stakeholders’ welfare

changes. The simulations were allowed to iterate

10,000 times. In the base scenario of this study, only

the estimated mean surplus changes are reported. The

mean values obtained from the simulations do not differ greatly from the point estimates calculated without

the probability distributions.

Results for Bt Cotton

With the estimated ARMS effects, global benefits from

adopting Bt cotton in 1997 were estimated at $212.5

million (table 10), with 78 percent of the surplus

accruing to the United States. The estimated world

benefit was $300.7 million with the EMD. These benefits accounted for 3.6-5.1 percent of the value of

upland cotton production that year. Benefits received

by U.S. farmers were estimated to range from $61.4

million (estimated ARMS effects) to $117.4 million

(EMD). This range reflects the different assumptions

concerning the extent of the technology’s impacts on

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 21

8 The mean values of the estimated Marshallian surplus changes

reported in this analysis were computed using point estimates for

the U.S. and ROW supply and demand elasticities for all three

biotech crops. Point estimates are used to foster transparency in

identifying the driving forces that affect the models’ simulation

results and to avoid arbitrarily assigning minimum and maximum

values for the probability distributions when supporting data

(such as relevant standard errors of the regression coefficients)

are not available.

Table 9—Supply and demand elasticities assumed

in this study 

Parameter 1997 Bt and 1997 herbicideherbicide-tolerant tolerant

cotton soybeans

U.S. supply elasticity 0.47 0.28

U.S. demand elasticity -0.50 -0.50

Net export demand elasticity -0.97 -1.21

ROW supply elasticity 0.15 0.30

ROW demand elasticity -0.15 -0.25
crop yields and pest control costs. Greater savings in

pest control costs in the Southern Seaboard and

Mississippi Portal under the EMD were the driving

force behind the larger estimated welfare gain for U.S.

producers (table 5). U.S. farmers’ share of the estimated world benefit ranged from 29 percent to 39 percent (fig. 7).

The estimated market benefits realized by the innovators—Monsanto (the biotechnology developer) and

Delta & Pine Land (the germplasm supplier)—remain

constant across the two data sources. The variables

that affect their estimated benefits—including adoption

rates, technology fees, and seed premiums—were

fixed in 1997. Monsanto’s estimated gain was determined primarily by the $32-per-acre technology fee

(above and beyond the price premiums) that the company charged U.S adopters. Monsanto also collected

the same technology fee on Mexico’s 37,100 acres of

Bt cotton. Adopters of the technology in Australia—

where 165,000 acres were planted to that variety—

were charged approximately $74 per acre.9 Delta &

Pine Land received a royalty payment of $5.11 per

acre from Monsanto for the use of its parent

germplasm (Falck-Zepeda et al., 2000b). In addition,

Delta & Pine Land derived a portion of its estimated

benefits from a $2-per-acre seed premium charged to

U.S. adopters, accounting for 28 percent of the

germplasm supplier’s estimated surplus gain.10

Monsanto is estimated to have received $62.0 million

in 1997 from the adoption of Bt cotton worldwide,

while Delta & Pine Land’s estimated benefit totaled

$12.9 million (table 10). Regionally, the Mississippi

Portal and Southern Seaboard provided the bulk of

these estimated benefits (about $20 million each)

because they are two major cotton-producing regions.

The estimated benefits realized by the innovators

remain constant across the two data sources because

they are not dependent on the farm-level effects of

biotechnology.

U.S. consumers (including cotton shippers, brokers, and

mill buyers) are estimated to have received between

$29.9 million (estimated ARMS effects) and $50.4 million (EMD) due to lower prices resulting from the adoption of Bt cotton. The world price of cotton was

estimated to have declined 0.50 cents to 0.81 cents per

pound (0.69-1.11 percent of the counterfactual world

price—72.8 cents per pound) due to the introduction of

the new technology, depending on the data source. U.S.

consumers received a relatively small portion of the

total estimated benefit, averaging 16 percent across the

two data sources (fig. 7). This is not surprising, given

that the insect resistance of Bt cotton is an input trait

that primarily benefits producers through reduced yield

losses and lower insect control costs.

Consumers and producers in the rest of the world were

estimated to have realized a net market benefit of

$46.4 million (estimated ARMS effects) to $58.1 million (EMD). The technology-induced increase in cotton supply lowered its world price, benefiting

consumers. ROW producers, on the other hand, suffered welfare losses because most of them grew traditional varieties. Thus, they did not realize the cost

savings associated with Bt cotton and were fully

exposed to the reduction in the world price. ROW consumers and producers, on a net basis, obtained 19 percent (EMD) to 22 percent (estimated ARMS effects) of

the estimated total world benefit (fig. 7).

Results for Herbicide-Tolerant Cotton

The size and distribution of market benefits associated

with the adoption of herbicide-tolerant cotton were

calculated using the estimated ARMS effects. The

adoption of this technology resulted in an estimated

global gain of $231.8 million in 1997, with the United

States receiving 67 percent (table 11). This benefit represented 3.9 percent of the value of upland cotton pro22 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA

Table 10—Estimates of world surplus changes for

Bt cotton, 1997

Stakeholder Estimated ARMS effect EMD

$ million

U.S. farmers 61.4 117.4

U.S. consumers 29.9 50.4

Monsanto 62.0 62.0

Delta & Pine Land 12.9 12.9

ROW producers -134.8 -233.4

ROW consumers 181.2 291.5

Net ROW 46.4 58.1

World benefit 212.5 300.7

EMD = Enhanced Market Data II.

9 Throughout this report, estimates of Monsanto’s benefits are

likely to be overstated because unknown administrative expenses,

such as those associated with marketing and IPR enforcement, are

not taken into account.

10 No seed premiums were charged in other countries that year.
duction that year. U.S. consumers were estimated to

gain $132.2 million while ROW consumers realized an

estimated benefit of $808.8 million. These benefits

were due to higher yields that boosted cotton supply

and lowered the world price by 2.5 cents per pound

(3.4 percent of the counterfactual world price). This

amount was much higher than the price effect from Bt

cotton. In percentage terms, U.S. consumers captured

the majority of the estimated benefits (fig. 8).

As with Bt technology, the herbicide-tolerant trait is

geared to benefit adopters. However, U.S. farmers

were estimated to have gained only $9.6 million from

the adoption of herbicide-tolerant cotton. Greater seed

costs (including seed premiums and technology fees)

and the lower world cotton price offset much of the

estimated benefits from higher yields, which were 17

percent higher for adopters nationwide. In 1997, the

loan rate for upland cotton ($0.519 per pound) was

lower than the world cotton price. Thus, U.S. cotton

producers did not receive marketing loan gains or loan

deficiency payments in that marketing year. The cotton

loan program could affect the outcome in other years

when loan rates are effective. U.S. farmers’ share of

the estimated total benefits was small—4 percent. The

estimated benefits accruing to Monsanto and Delta &

Pine Land were small as well.

ROW consumers were estimated to have gained

$808.8 million from the adoption of herbicide-tolerant

cotton, due exclusively to the decrease in the world

price. ROW producers’ estimated surplus fell in 1997

because they did not have access to the technology.

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 23

Percentage shares of the estimated total world surplus gain 

from adopting Bt cotton, 1997

Figure 7

U.S. farmers

28.9%

Monsanto

29.2%

Delta & Pine Land

6.1%

U.S. consumers

14.1%

Net ROW

21.8%

U.S. farmers

39.0%

Monsanto

20.6%

Delta & Pine Land

4.3%

U.S. consumers

16.8%

Net ROW

19.3%

Estimated

ARMS effects

EMD

Table 11—Estimates of surplus changes for herbicide-tolerant cotton, 1997

Stakeholder Estimated ARMS effects

$ million

U.S. farmers 9.6

U.S. consumers 132.2

Monsanto 10.6

Delta & Pine Land 3.8

ROW producers -733.3

ROW consumers 808.8

Net ROW 75.5

World benefit 231.8

Figure 8

Stakeholders' shares of the estimated total 

world benefit from adopting herbicide-tolerant 

cotton, 1997

U.S.farmers—4.1%

Monsanto—4.6%

Delta & Pine Land—1.6%

U.S. consumers—57.1%

Net ROW—32.6%
Thus, they were fully exposed to the falling world

price without the benefits of higher yields and/or lower

weed control costs. On a net basis, the ROW was estimated to have gained $75.5 million, or 33 percent of

the total world benefit (fig. 8).

Results for Herbicide-Tolerant

Soybeans

The gain in total world surplus from the adoption of

herbicide-tolerant soybeans in 1997 was estimated at

$307.5 million, with the United States capturing 94

percent of the estimated benefit (table 12). This benefit

accounted for 1.7 percent of the value of soybean production that year. With the estimated ARMS effects,

U.S. farmers received only 20 percent ($61.5 million)

of the estimated total benefits (fig. 9). This small

amount is due largely to the negligible percentage

yield increase and small savings in weed control costs

in major soybean-producing regions, which are consistent with other studies such as those by Gianessi and

Carpenter (2000) and Duffy and Vontalge (table 7).

While the farm-level effects were small in the case of

herbicide-tolerant soybeans, adopters may have realized other benefits that are not quantified in this study,

particularly those arising from simplified and flexible

weed control programs and fewer restrictions on crop

rotation, conservation tillage systems, and narrow-row

plantings (Fernandez-Cornejo and McBride, 2002).

Monsanto’s estimated revenue ($85.6 million) from

herbicide-tolerant soybeans was the result of a $7.25-

per-acre technology fee charged to adopters.11 This

total is likely to be underestimated because it excludes

the benefit of increased glyphosate sales resulting from

the adoption of herbicide-tolerant soybeans. The total

benefit estimated for germplasm suppliers ($124.4 million), which consisted of numerous seed companies,

was derived from seed premiums that ranged from

$1.58 to $8.47 per acre (the weighted average value

was $4.31). The combined share of the estimated benefits (68 percent) captured by the innovators was large

in 1997 due to the minimal farm-level effects for

adopters (fig. 9).

Estimated benefits captured by Monsanto and the seed

companies do not take into account the payments that

licensing companies paid Monsanto for the use of the

technology. When the herbicide-resistant trait was first

developed for soybeans, Monsanto allowed some seed

companies to purchase the technology outright for a

fixed fee. Other firms were required to pay licensing

fees. Because “use-of-technology” payment information is proprietary, it was not included in the calculation of the innovators’ benefits. To the extent that the

seed companies made these payments to Monsanto,

this study overstates the seed companies’ benefits and

underestimates the gains that accrued to Monsanto.

U.S. consumers benefited through increased soybean

supply, which lowered the world price by 1.2 cents per

bushel (0.17 percent of the counterfactual world price

of $7.06 per bushel). Domestic consumers received

only 5 percent of the estimated total benefit from herbicide-tolerant soybeans (fig. 9). Because U.S. producers realized only a modest net savings in pest control

24 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA

Table 12—Estimates of surplus changes for herbicide-tolerant soybeans, 1997

Stakeholder Estimated ARMS effects

$ million

U.S. farmers 61.5

U.S. consumers 16.3

Monsanto 85.6

Seed companies 124.4

ROW producers -35.0

ROW consumers 54.8

Net ROW 19.8

World benefit 307.5

Figure 9

Stakeholders' share of the estimated benefits 

resulting from adopting herbicide-tolerant 

soybeans, 1997

U.S. farmers—20.0%

Monsanto—27.8%

Seed companies—40.4%

U.S. consumers—5.3% Net ROW—6.4%

11 In 1997, the technology fee was $5 per 50-pound bag of herbicide-tolerant soybean seed. A 1.45 bag-per-acre seeding rate was

assumed when calculating the technology fee on a per-acre basis.
costs, the price decrease for soybeans was modest. The

minimal price change contributed to consumers’ attaining only a small share of the estimated total benefit.

This study does not differentiate among consumers

with different attitudes toward biotech foods. Even

though U.S. consumers as a whole gained from the

adoption of herbicide-tolerant soybeans, some consumers may have been negatively affected by the technology. Those who were indifferent to biotech versus

nonbiotech foods benefited from the trait (because of

slightly lower prices), but individuals who prefer but

could not select nonbiotech foods faced a negative

externality (Golan et al.).

ROW consumers were also estimated to have gained

from the adoption of herbicide-tolerant soybeans,

assuming consumer indifference to biotech versus nonbiotech foods. While the estimated net change in ROW

surplus was positive, foreign producers suffered estimated losses. Except in Argentina, the adoption of herbicide-tolerant varieties outside of the United States was

minimal in 1997.12 As a result, most foreign producers

faced lower world soybean prices without realizing the

slight yield gains and reductions in weed control costs

associated with herbicide-tolerant soybeans.

Comparison of Results With 

Previous Findings

The estimated total benefit ($212.5 million to $300.7

million) from Bt cotton (1997) in this study is generally greater than other studies’ estimates. Direct comparison of this study’s results with those covering

other crop years is inappropriate due to year-specific

factors, such as weather and pest infestation levels.

The shares of the estimated benefits reported in this

study appear to be lower for U.S. farmers and the

innovators but higher for U.S. consumers and the rest

of the world than in Falck-Zepeda et al. (2000a). In

contrast, this study’s findings differ significantly from

Frisvold et al., who show that innovators and U.S. consumers received the bulk of the estimated total benefits. These discrepancies are largely attributed to

differences in the model structure specified in the two

studies, as well as supply and demand elasticity

assumptions. 

Our estimate of the total benefit ($307.5 million) resulting from the adoption of herbicide-tolerant soybeans is

significantly lower than the $1.1 billion reported by

Falck-Zepeda et al. (2000a) under the low U.S. supplyelasticity scenario (table 3). In addition, their study

shows a much larger share of the estimated benefits for

U.S. farmers (due, in part, to larger yield enhancement

effects assumed in their study), but lower shares for

innovators and U.S. consumers. For example, U.S.

farmers realized 77 percent of the estimated total benefit

($808 million) in their study, while this study shows

only $62 million to U.S. farmers, or 20 percent.

It is difficult to compare this study’s results for herbicide-tolerant soybeans with those of Moschini et al.

First, their study explicitly includes soybean-processed

products as well as soybeans, while our study is limited to soybeans only. Second, the two analyses cover

different years—1999 versus 1997. Third, the analytical frameworks and elasticity assumptions differ.

While this analysis shows a considerably smaller estimated total benefit than the $804 million in Moschini

et al., the shares of the estimated benefits that accrued

to U.S. farmers (about 20 percent) are comparable

across the two studies.

Measuring the benefits arising from the adoption of

biotechnology depends on a number of factors. The

results are affected by the choice of the analytical

framework, particularly with respect to the nature of

U.S. and ROW supply curves (linear versus nonlinear)

and the shift in supply (parallel versus nonparallel). In

addition, different supply and demand elasticity

assumptions could influence both the size and distribution of estimated benefits.

Although there are differences in the theoretical frameworks of Falck-Zepeda et al. (2000b) and Moschini et

al., their separate approaches can be reconciled by

equalizing certain assumptions. Appendix B demonstrates that by using identical U.S. and ROW supply

and demand elasticities as well as the same farm-level

effects, stakeholders’ estimated benefits are generally

convergent, regardless of differences in the frameworks. This suggests that the choices of linear or nonlinear supply and demand functions and parallel or

nonparallel supply shifts are not as critical in affecting

the size and distribution of benefits as the U.S. and

ROW supply elasticities and the magnitude of farmlevel effects associated with the new technologies.

The size of the surplus gains hinges on the scope of

the analysis, particularly with regard to which market

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 25

12 Approximately 3.5 million acres of herbicide-tolerant soybeans

were planted in Argentina and 2,500 acres in Canada in 1997,

while 11.8 million acres were planted in the United States (James).
benefits are considered and whether nonmarket benefits are included in the analysis. This study is limited

to certain market benefits that accrue to various stakeholders. Market benefits that are not quantified in this

study, but may be significant, include ease of pest

management in the case of herbicide-tolerant soybeans, the insurance value associated with insectresistant crops like Bt cotton, and fuel savings from

fewer pesticide applications (Fernandez-Cornejo and

McBride, 2002). It is widely recognized that the first

benefit has driven the rapid adoption of herbicide-tolerant soybeans by U.S. farmers. Moreover, the importance of nonmarket benefits, such as impacts on the

environment and human health, is crucial but not

quantified here. Year-specific variables, such as

weather and pest pressures, also influence the size of

the market benefits and their distribution.

The size and distribution of market benefits also

depend on the type of new biotech traits. Bt and herbicide-tolerant technologies, which are the focus in this

study, are input traits and directly benefit producers

through potential yield enhancements and/or savings in

pest control costs. In contrast, crops with output traits,

which are still in development, are geared to benefit

consumers more directly.

Last, the benefits arising from the adoption of biotech

crops depend on who develops the technologies. Most

commercially available biotech crops to date have been

developed by the private sector through research and

development efforts that are typically protected by intellectual property rights, such as patents. Technology fees

are necessary to recoup research and development costs

that are incurred by these private firms. Thus, the benefits to producers and consumers are reduced under the

private development scenario because the private firms

are able to extract monopoly profits through technology

fees. In contrast, public sector development (such as by

land-grant universities and government research agencies) leads to greater benefits for producers and consumers than in the private development scenario for two

reasons: (1) producers are not likely to be charged technology fees, and (2) the innovations are likely to be

public goods, which benefit consumers (Smith et al.).

The comparison of benefits from biotechnology with

those of nonbiotech innovations in earlier years is difficult. Previous studies on the benefits of adopting

agricultural nonbiotech innovations focus on public

sector investment and the distribution of benefits

between producers and consumers. Public sector

research, particularly in the area of self-pollinated

seeds, has historically been difficult for private inventors to appropriate—not only because the products are

reproducible, but also because most biological inventions, until recently, were not subject to standard

patent law (Smith et al.). Thus, agricultural research

was unlikely to attract adequate private investment

because the prospects for financial returns were low. 

However, recent developments in patent laws and the

potential to earn monopoly profits spurred greater

interest in private sector development, including the

area of biotechnology. (The Plant Variety Protection

Act, enacted in 1970 and amended in 1994, provides

IPR protection to developers of new plant varieties that

are sexually reproduced by seed, and utility patent protection for plant innovations was explicitly extended

by 1985.) Studies that look at biotech innovations consider the benefits that accrue to producers, consumers,

and innovators, while studies that focus on nonbiotech

innovations have nearly always been limited to the

benefits to producers and consumers (and, in a few

cases, processors as well) (Alston, Norton, and Pardey;

Alston, Sexton, and Zhang).

26 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA
Our estimated benefits from the adoption of three

biotech crops in 1997 represent base scenarios that

assume a set of supply and demand elasticities as well

as specific farm-level effects realized by ROW producers. However, uncertainty surrounding the values of

these parameters warrants sensitivity analyses to determine how the results may differ in response to changes

in these parameters. In addition, we tackle uncertainty

surrounding the estimated stakeholder benefits by

showing the percentile distributions of the estimated

surplus gains for the three crops.

Supply and Demand 

Elasticity Assumptions

To gauge the extent to which different supply and

demand elasticities affect surplus estimates, the elasticity values in the base scenarios were adjusted for

each biotech crop. In total, there were four alternate

scenarios for each crop. The benefits were computed

with U.S. and ROW supply elasticities that are (a)

double their original values and (b) half their original

values. Likewise, stakeholders’ benefits were computed with U.S. domestic and net export demand elasticities, as well as a ROW demand elasticity, that are

(a) double their original values and (b) half their original values.

The sensitivity analysis indicates that changes in the

supply elasticities (especially for the United States)

have a dramatic effect on estimated total surplus gains

(figs. 10-12). For example, the increase in estimated

world welfare associated with Bt cotton adoption

(using the estimated ARMS effects) is 74 percent

higher than in the base case when the U.S. and ROW

supply elasticities are cut in half. In contrast, the estimated total benefit is 37 percent smaller when the supply elasticities are doubled (fig. 10). 

The estimated benefits that accrue to U.S. farmers

greatly depend on the values of the supply elasticities.

For example, variations in supply elasticities produce

dramatic changes in the estimated surplus for U.S. soybean producers. With smaller values, U.S. farmers would

have realized an estimated surplus gain ($301.5 million)

that is nearly 5 times as large as in the base case (fig.

12). In contrast, U.S. farmers would have incurred an

estimated welfare loss with higher supply elasticities.

U.S. producers’ share of the estimated total benefits is

also affected by the magnitude of the supply elasticities,

particularly for Bt cotton and herbicide-tolerant soybeans (fig. 13). Doubling the supply elasticities causes

U.S. soybean producer’s share to disappear. Lowering

supply and demand elasticities results in higher benefit

estimates for U.S. consumers and the net ROW.

Because the factors (e.g., adoption rates, technology

fees, and seed premiums) that determine the innovators’

benefits are fixed in the model for a given crop year,

their estimated welfare gains remain unchanged as the

supply and demand elasticities are adjusted.

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 27

Sensitivity Analysis

Sensitivity of benefit estimates to changes in supply elasticities: 

Bt cotton (estimated ARMS effects)

Figure 10

$ million

U.S. farmers U.S. consumers Monsanto Delta & 

Pine Land

ROW 

producers

ROW

 consumers

Net ROW Total

-300

-200

-100

0

100

200

300

400

One-half base elasticities Base elasticities Double base elasticities
28 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA

Sensitivity of benefit estimates to changes in supply elasticities: 

Herbicide-tolerant cotton

Figure 11

$ million

U.S. farmers U.S. consumers Monsanto Delta & 

Pine Land

ROW 

producers

ROW

 consumers

Net ROW Total

-2,000

-1,500

-1,000

-500

0

500

1,000

1,500

2,000

One-half base elasticities Base elasticities Double base elasticities

Sensitivity of benefit estimates to changes in supply elasticities: 

Herbicide-tolerant soybeans

Figure 12

$ million

U.S. farmers U.S. consumers Monsanto Seed

companies

ROW 

producers

ROW

 consumers

Net ROW Total

-100

0

100

200

300

400

500

600

700

One-half base elasticities Base elasticities Double base elasticities

Sensitivity of U.S. farmers' share of estimated surplus gain to changes in U.S. and 

ROW supply elasticities

Figure 13

Percent

Herbicide-tolerant cotton

Bt cotton Herbicide-tolerant soybeans

One-half base elasticities Base elasticities Double base elasticities

0

10

20

30

40

50

60
Altering the demand elasticities leads to more modest

changes in estimated total benefits for the three crops

and smaller changes in estimated producer and consumer surpluses (figs. 14-16). For example, given

inelastic supply and demand, the estimated U.S. consumer surplus increases slightly and U.S. producer

surplus falls slightly when the U.S. demand becomes

even more inelastic. If U.S. supply becomes more

inelastic, the estimated U.S. producer surplus becomes

considerably larger. Sensitivity analysis of the EMD

benefit estimates produces the same results. 

Efficiency of Technology Transfer

In this sensitivity analysis, the base assumption for

efficiency of technology transfer is varied to encompass “low” and “high” farm-level impacts in the ROW.

Specifically, ROW producers are hypothesized to have

realized either 10 percent (the low-efficiency case) or

100 percent (the high-efficiency case) of the technologies’ impacts on crop yields and pest control costs, as

compared with 50 percent in the base scenario. The

efficiency assumption was not considered for herbicide-tolerant cotton since that variety was not commercially available to ROW producers in 1997. About 30

percent of Bt cotton was grown outside of the United

States in 1997—mostly in Australia and South Africa

(James). For soybeans, about 23 percent of the herbicide-tolerant variety was produced in the ROW, primarily in Argentina.

The estimated total world surplus would increase as a

result of a more efficient transfer of technology, with

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 29

Sensitivity of benefit estimates to changes in demand elasticities: 

Bt cotton (estimated ARMS effects)

Figure 14

$ million

U.S. farmers U.S. consumers Monsanto Delta &

Pine Land

ROW 

producers

ROW

 consumers

Net ROW Total

-300

-200

-100

0

100

200

300

400

One-half base elasticities Base elasticities Double base elasticities

Sensitivity of benefit estimates to changes in demand elasticities: 

Herbicide-tolerant cotton

Figure 15

$ million

U.S. farmers U.S. consumers Monsanto Delta &

Pine Land

ROW 

producers

ROW

 consumers

Net ROW Total

One-half base elasticities Base elasticities Dould base elasticities

-1,000

-800

-600

-400

-200

0

200

400

600

800

1,000
the gains almost entirely in the ROW (figs. 17-18).

While ROW producers would still incur a welfare loss,

their higher yields and greater savings in pest control

costs would mitigate some of the loss caused by

greater supply and a lower world price. As a consequence of the downward pressure on cotton prices,

U.S. farmers would experience a slightly lower estimated welfare gain. In contrast, U.S. and ROW consumers would benefit from lower prices.

Range of Estimated Surplus 

Gains or Losses

Variability in parameter values for certain key variables leads to estimated stakeholder benefits that are

dispersed around the estimated mean values. The

degree of variability for these parameters is incorporated in the @Risk simulations through assumed probability distributions.

The estimated total benefit resulting from the adoption

of Bt cotton varies widely, especially when the EMD

are used (fig. 19). With that data source, there is a 50-

percent probability that the estimates of the total welfare change will fall between a loss of $217 million

(25th percentile) and a gain of $817 million (75th percentile). This large dispersion is due primarily to variation in the estimated benefits that accrue to U.S.

farmers and the net ROW. The ranges of the benefit

estimates are smaller for all stakeholders (except the

innovators) when the estimated ARMS effects are

employed (fig. 20).

In the case of herbicide-tolerant cotton, there is little

variation in the estimated benefits that accrue to U.S.

farmers and consumers, due largely to the use of point

estimates for regional savings in pest control costs (fig.

21). The dispersion in the estimated total benefits ($169

million to $294 million) mirrors the variability in estimated welfare gains realized by the ROW (on a net

basis). Relative to herbicide-tolerant cotton, the estimated surplus gains from herbicide-tolerant soybean

adoption are more variable for U.S. farmers and the rest

of the world (fig. 22). The innovators’ estimated surplus

gains are not constant for herbicide-tolerant cotton and

soybeans because the estimates use variables that have

probability distributions assigned to them.

30 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA

Sensitivity of benefit estimates to changes in demand elasticities: 

Herbicide-tolerant soybeans

Figure 16

$ million

U.S. farmers U.S. consumers Monsanto Seed

companies

ROW 

producers

ROW

 consumers

Net ROW Total

One-half base elasticities Base elasticities Double base elasticities

-100

-50

0

50

100

150

200

250

300

350
Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 31

Sensitivity of benefit estimates to changes in the efficiency of technology transfer: 

Bt cotton (estimated ARMS effects)

Figure 17

$ million

U.S. farmers U.S. consumers Monsanto Delta &

Pine Land

ROW 

producers

ROW

 consumers

Net ROW Total

-200

-150

-100

-50

0

50

100

150

200

250

300

10% Efficiency Base (50% Efficiency) 100% Efficiency

Sensitivity of benefit estimates to changes in the efficiency of technology transfer: 

Herbicide-tolerant soybeans

Figure 18

$ million

U.S. farmers U.S. consumers Monsanto Seed

companies

ROW 

producers

ROW

 consumers

Net ROW Total

10% Efficiency Base (50% Efficiency) 100% Efficiency

-100

-50

0

50

100

150

200

250

300

350

Dispersion of benefit estimates: Bt cotton (EMD)

Figure 19

$ million

U.S. farmers U.S. consumers Monsanto Delta &

Pine Land

ROW 

producers

ROW

 consumers

Net ROW Total

25th Percentile Mean 75th Percentile

-600

-400

-200

0

200

400

600

800

1,000
32 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA

Dispersion of benefit estimates: Bt cotton (estimated ARMS effects)

Figure 20

$ million

U.S. farmers U.S. consumers Monsanto Delta &

Pine Land

ROW 

producers

ROW

 consumers

Net ROW Total

25th Percentile Mean 75th Percentile

-300

-200

-100

0

100

200

300

400

500

Dispersion of benefit estimates: Herbicide-tolerant cotton

Figure 21

$ million

U.S. farmers U.S. consumers Monsanto Delta &

Pine Land

ROW 

producers

ROW

 consumers

Net ROW Total

25th Percentile Mean 75th Percentile

-1,000

-800

-600

-400

-200

0

200

400

600

800

1,000

Dispersion of benefit estimates: Herbicide-tolerant soybeans

Figure 22

$ million

U.S. farmers U.S. consumers Monsanto Seed

companies

ROW 

producers

ROW

 consumers

Net ROW Total

25th Percentile Mean 75th Percentile

-100

-50

0

50

100

150

200

250

300

350

400
The estimated total benefit arising from the adoption

of three biotech crops in 1997 varied significantly

across crops, ranging from $213 million to $301 million for Bt cotton (depending on the data source) to

$308 million for herbicide-tolerant soybeans. The

adoption of herbicide-tolerant cotton resulted in an

estimated total gain of $232 million. This study’s estimate of the total benefit from adopting Bt cotton

exceeds those of other studies that consider the 1997

crop. In contrast, the estimate of the total benefit for

herbicide-tolerant soybeans lies toward the lower end

of the range reported in previous analyses.

While a number of previous studies have estimated

that U.S. producers obtain about half of the estimated

total benefits, this analysis finds that they received

about a third or less in 1997. Past estimates of U.S.

producers’ benefit shares vary widely in the case of

herbicide-tolerant soybeans, ranging from 20 percent

to 77 percent. In this study, the share of the estimated

benefits that accrued to domestic soybean producers is

at the lower end of that range. U.S. producers received

a small portion of the estimated benefits from herbicide-tolerant cotton; modest savings in pest control

costs did not compensate for losses resulting from

lower market prices. 

This analysis finds that innovators received 30 percent

(average of the results from the estimated ARMS

effects and EMD) of the estimated total benefits arising from Bt cotton adoption, a value generally lower

than in other studies. In contrast, innovators captured

68 percent of the estimated benefits from herbicidetolerant soybeans, considerably higher than previous

estimates. In the cases of these two biotech crops, U.S.

consumers received a small share of the estimated total

benefits (5 percent to 17 percent), a result comparable

with other studies. With herbicide-tolerant cotton, 57

percent of the estimated benefits accrued to U.S. consumers because of lower commodity prices.

Considerable uncertainty surrounds the estimates of

total benefits arising from the adoption of biotechnology. Of the three crops, Bt cotton has the widest dispersion of estimated total benefits, ranging from -$9

million to $431 million with the estimated ARMS

effects, compared with the mean of $213 million. The

dispersion of estimated total benefits appears to be

smaller for both herbicide-tolerant cotton and soybeans.

Estimated total benefits—as well as the shares that

accrue to the various stakeholders—are sensitive to the

choice of analytical framework, particularly with

respect to the nature of the U.S. and ROW supply

curves (linear versus nonlinear) and the shift in supply

(parallel versus nonparallel). Results also depend on

assumptions concerning the U.S. and ROW supply and

demand elasticities. The sensitivity analysis shows that

altering the U.S. and ROW supply elasticities has a

bigger impact on the estimated stakeholder benefits

than changing the demand elasticities.

Many other factors, which are not quantified in this

study, influence the size and distribution of benefits

stemming from biotech adoption. Stakeholder benefits

depend on the extent to which both market and nonmarket benefits are included in the analysis. This study

captures only certain market benefits, disregarding the

convenience value of simplicity and flexibility in weed

control programs and the insurance value of crop protection associated with insect-resistant crops. Given

the minimal farm-level effects associated with herbicide-tolerant soybeans, ease of pest management is

regarded as the primary reason behind the rapid adoption of this technology by U.S. farmers.

Neither does this study fully consider nonmarket benefits, such as impacts on the environment and human

health, which may be significant. Biotechnology led to

reductions in pesticide use (measured in pounds of

active ingredients) for Bt cotton in the Southern

Seaboard, herbicide-tolerant cotton nationwide, and

herbicide-tolerant soybeans in some major production

regions. However, analyzing changes in pesticide use

alone does not accurately measure the total direct benefits to the environment and human health.

First generation biotech crops have had input trait

characteristics, such as insect resistance, that primarily

benefit producers. As biotech crops with output traits

are developed, they could directly benefit consumers.

In addition, the benefits arising from the adoption of

biotech crops depend on who develops the technologies. If biotech crops were to be developed by the public sector, the technologies would likely be public

goods. As a result, consumers may capture a greater

proportion of the benefits.

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 33

Conclusions
Last, benefits from biotech crops are dependent on

year-specific and crop-specific factors, such as weather

and pest infestation levels. This suggests that multiyear

analyses and analyses of other crops, such as corn,

would yield a more accurate perspective on the size

and distribution of benefits resulting from the adoption

of agricultural biotechnology. This extended analysis

will be particularly relevant with increased technology

transfer to the ROW, the emergence of several competing biotechnology varieties for some crops, and evolving pest management requirements for Bt products that

may affect pesticide use.

34 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA
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Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 37
The empirical economic surplus model proposed by Alston et al. is based on the assumption that the U.S. and ROW supply and demand functions can be modeled with the

following equations:

U.S. supply: QUS = αUS + βUS (P + kUS ) = ( αUS + βUS kUS) + βUS P,

U.S. demand: CUS = γUS - δUS P,

ROW supply: QROW = αROW + βROW (P + kROW) = ( αROW + βROW kROW ) + βROW P,

and

ROW demand: CROW = γROW - δROW P,

where QUS and CUS are the quantities produced and consumed of the commodity (which

may include biotech and/or conventional varieties) in the United States. Similarly, QROW

and CROW are the quantities produced and consumed in the ROW.1 The terms kUS and

kROW are the vertical shift in the U.S. and ROW supply curves due to the introduction of

biotechnology. Last, P is the equilibrium world price of the commodity. A graphical representation of this model is presented in figure 5.

The first step in deriving the formulas that determine changes in producer and consumer

surpluses is to use the identity QUS + QROW = CUS + CROW, which allows for the estimation of P. The existence of a single equilibrium world price follows from the Law of One

Price assumption, which states that regional prices only differ from the world price by

transportation costs (Falck-Zepeda et al., 2000a).

The equilibrium price observed after the introduction of biotechnology is referred to as P1,

while the counterfactual price—the price that would have prevailed had the technology not

been introduced and identical supply and demand conditions existed—is denoted by P0.

Because the welfare changes associated with the adoption of biotechnology are measured

relative to the absence of the innovation, P0 must be estimated. The formula for estimating

the world price is

P = (γUS + γROW - αUS - αROW - βUS kWORLD) / (βUS + δUS + βROW + δROW),

where kWORLD is the sum of kUS and kROW. If there is no supply shift, kUS , kROW , and

thus kWORLD, equal 0 and

P = P0 = (γUS + γROW - αUS - αROW ) / (βUS + δUS + βROW + δROW ).

38 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA

Appendix A: Empirical Model for Measuring the Changes in 

Economic Surpluses

1 As in the Moschini and Lapan model, this study does not consider consumer heterogeneity in valuing

biotech innovations. Different consumer preferences toward biotech products and government regulations

among export markets could lead to divergent values of biotech and nonbiotech products for U.S. and ROW

consumers. Considering consumer heterogeneity could affect the resulting surplus changes, including the benefits for consumers as a whole as well as those with divergent preferences toward biotech products, in this

study.
On the other hand, if there is a shift in supply due to the introduction of biotechnology and

kWORLD equals KP0, where K= kWORLD/P0, then P = P1 = (γUS + γROW - αUS - αROW - βUS

K P0) / (βUS + δUS + βROW + δROW ) and the change in price, P1- P0 = - βUS KP0 / (βUS +

δUS + βROW + δROW ). The absolute value of the relative price change (Z) is Z= -(P1- P0) /

P0 = βUS K / (βUS + δUS + βROW + δROW ), which is assumed to be the same for all U.S.

production regions due to the Law of One Price. By using the trade equilibrium assumption QT0 = CROW,0 - QROW,0 = QUS,0 - CUS,0 (the zero subscripts indicate counterfactual

values), Z can be defined in elasticity form as

Z = εUS K / [εUS + SUS ηUS + (1- SUS ) ηEROW].

The term εUS is the U.S. supply elasticity for the biotech crop, ηUS is the absolute value of the

U.S. demand elasticity for the commodity, ηEROW is the absolute value of the net export

demand elasticity, and SUS is the share of U.S. production that is consumed domestically.

As adapted from Alston et al., the formulas for changes in producer and consumer

surpluses in the United States and the ROW are:

∆ PSUS = P0 QUS,0 (KUS - Z) (1 + 0.5 ZεUS),

∆ CSUS = P0 CUS,0 Z (1 + 0.5 Z ηUS),

∆ PSROW = -P0 QROW,0 (K ROW - Z) (1 + 0.5 ZεROW),

∆ CSROW = P0 CROW,0 Z (1 + 0.5 Z ηROW),

∆ USASUS = ∆ CSUS + ∆ PSUS,

and 

∆ ROWSROW = ∆ CSROW + ∆ PSROW,

where ∆ PSUS is the change in U.S. producer surplus, ∆ CSUS is the change in U.S.

consumer surplus, ∆ PSROW is the change in ROW producer surplus, ∆ CSROW is the

change in ROW consumer surplus, εROW is the ROW supply elasticity, and ηROW is the

absolute value of the ROW demand elasticity. The terms ∆ USASUS and ∆ ROWSROW

represent the change in total surplus in the United States and ROW. These formulas

assume that the pre-adoption world and U.S. regional prices, quantities, and relevant

elasticities are known. While the counterfactual commodity prices and quantities are not

known, they can be estimated from the equations above. Following Alston et al. and

Pinstrup-Andersen et al., the equations are:

P0 = P1 / {1 - [εUS K / [εUS + SUS ηUS + (1- SUS)ηEROW] }

and

Q0 = Q1 / {1 + [εUS K ((SUS ηUS) + (1- SUS)ηEROW)] / [εUS + SUS ηUS + (1- SUS) ηEROW]}.

After estimating the shift in supply due to the adoption of biotechnology as well as the

counterfactual world price, the surplus changes accruing to U.S. farmers, U.S. consumers,

and ROW consumers and producers are calculated. The gains realized by the technology

innovators are estimated separately using data on adoption rates, technology fees, and

seed premiums.

Economic Research Service/USDA Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 ● 39
This section attempts to reconcile differences in the

estimates of surplus changes resulting from two separate analytical frameworks. This study relies on an

approach used by Falck-Zepeda et al. (2000a) to estimate the size and distribution of benefits resulting

from the adoption of biotech crops. Two key characteristics of their framework are (1) linear supply and

demand functions, and (2) parallel shifts in supply. In

contrast, the model developed by Moschini et al.

allows for a nonlinear specification of the supply and

demand curves and nonparallel shifts in supply. These

two approaches are chosen for reconciliation here

since both address the size and distribution of benefits

resulting from the adoption of herbicide-tolerant soybeans. While herbicide-tolerant soybeans are highlighted in this example, the general conclusions would

likely be applicable to other commodities. 

Differences in the findings arising from these two

approaches may be attributed to several factors, including key features of the frameworks, supply and demand

elasticity assumptions, and the farm-level effects. To

assess the effect of these two frameworks on estimated

surplus changes, differences in other factors must be

controlled. To do this, assumptions concerning supply

and demand elasticities and farm-level effects were

equalized across the two frameworks. That is, the

assumptions made by Falck-Zepeda et al. (2000a) were

replaced by those in the Moschini et al. study.

To reconcile these two different approaches, the following key parameters in this study’s framework were

altered:

(a) Elasticities of supply were changed to 0.8 for

both the United States and ROW. Because

Moschini et al. specify a three-market model,

South America and the ROW were combined

into one ROW region to conform with the twomarket model in Falck-Zepeda et al. (2000a).

The 0.8 supply elasticity for the combined ROW

region is an average of the elasticities for the

ROW (0.6) and South America (1.0) in

Moschini et al.

(b) Herbicide cost savings was changed to $20 per

hectare.

(c) Yield advantage was eliminated.

(d) Soybean demand elasticity was lowered to

–0.4.

(e) Per-hectare seed cost was changed to $45 for

the United States and $40 for the ROW. 

(f) Herbicide-tolerant seed costs were adjusted to

be 43 percent and 22 percent higher than that

for conventional seed in the United States and

the ROW, respectively, to reflect the technology fees paid by adopters.

Altering the supply and demand elasticity assumptions

and farm-level effects to conform with those used in

Moschini et al. leads to similar changes in the estimated

stakeholder welfare, except for ROW producer surplus

(appendix table B-1). Using the Falck-Zepeda et al.

(2000a) framework, U.S. producers captured nearly 20

percent of the estimated surplus gain created by the

adoption of the herbicide-tolerant soybeans. In both

cases, innovators’ profits account for approximately half

of the estimated total world benefit. However, in the case

of ROW farmers, the re-estimation of the model renders

an estimated welfare loss of about $112 million—significantly higher than the estimated $31-million loss based

on the Moschini et al. framework. Although equalizing

many of the assumptions largely reconciles the differences between the two approaches, specification of the

model structure appears to account for the remaining discrepancies between the two sets of results.

40 ● Size and Distribution of Market Benefits From Adopting Biotech Crops / TB-1906 Economic Research Service/USDA

Appendix B: Differences in Estimated Surplus Changes for HerbicideTolerant Soybeans Due to Different Analytical Frameworks

Appendix table B-1—Comparison of analytical

frameworks for herbicide-tolerant soybeans

Stakeholder Surplus gain in Surplus gain from 

this study1 Moschini et al.2

$ million % of $ million % of 

total total

U.S. producers 135.2 19 156.0 19

U.S. consumers 93.0 13 81.0 10

Innovators 368.8 51 358.0 45

ROW producers -112.1 -31.0

ROW consumers 227.7 237.0 

Net ROW 115.7 16 206.0 26

World benefit 702.7 804.0 

1 Incorporates the assumptions described above in this appendix so

as to reflect those made by Moschini et al. However, the framework

is the same as the one used in this study to generate estimated surplus gains for the various stakeholders.

2 Reported in Moschini et al., who use a different framework from

the one used in this study.