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Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
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3
Farm-Level Economic Impacts

As shown in Chapter 1, farmers growing soybean, cotton, and corn adopted genetically engineered (GE) varieties over the last decade on the majority of acres planted to these crops in the United States. Much smaller acreages were planted in 2009 to a few other GE crops, such as canola, sugar beet, squash, and papaya. The decision to plant GE crops has affected the economic circumstances not only of the adopting farmers but in some cases of farmers who chose not to adopt them. The economic effects on farmers who adopt GE crops span their production systems and marketing decisions. In this chapter, we discuss the potential yield effects, changes in overhead expenses and management requirements, and shifts in market access and value of sales. A wide array of studies conducted mostly during the first 5 years of adoption has provided evidence for assessing the overall economic implications for farmers (see Box 3-1). We also discuss here the economic effects of GE-crop use on livestock producers who use the crops for feed and on farmers who do not elect to use the technology. The chapter concludes by examining the economic implications of gene flow from GE crops to non-GE crops and weedy relatives.

ECONOMIC IMPACTS ON ADOPTERS OF GENETICALLY ENGINEERED CROPS

GE crops have affected the economic status of adopters in several ways. The use of GE crops has had an effect on yields and their risk-management decisions. Genetic-engineering technology has also changed

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

BOX 3-1

Measuring Impacts

To evaluate the economic impacts of GE crops on adopters and non-adopters, the committee relied on the results of empirical analyses of farmer surveys and market data. Studies were peer reviewed, but the research approach and methods varied considerably with each study’s purposes and data. Each study has its own strengths and limitations. For example, some studies may use a different guideline in judging the significance (i.e., confidence level) of factors affecting the adoption of GE crops compared to other studies. The committee could not make the various studies comparable and accepted each set of findings as valid evidence. Some of the general approaches used to estimate economic impacts are explained here.

Empirical data. A comparison of means or averages is sometimes used to analyze results from experiments in which factors other than the item of interest are “controlled” by making them as similar as possible. For example, means of yield or pesticide use can be compared for two groups of soybean plots that are similar in soil type, rainfall, sunlight, and all other respects. One of the two groups is considered to have a treatment (e.g., soybean with a genetically engineered trait), and the other does not (e.g., conventional soy-bean). As an alternative to controlled experiments, the subjects that receive treatment and those that do not can be selected randomly with data collected through mail, phone, Internet, or personal surveys.

Survey data. Caution must be exercised in interpreting the results obtained by analyzing the differences in means from data from “uncontrolled experiments,” such as farm surveys. Conditions other than the “treatment” are not equal across the farms surveyed. For example, differences between mean estimates for yield and pesticide use from survey results cannot necessarily be attributed to the use of GE seeds because the different results are influenced by many other factors which are not controlled, including irrigation, weather, soil, nutrient and pest-management practices, other cropping practices, operator characteristics, and pest pressures.

Moreover, farmers are not assigned randomly to the two groups (adopters and nonadopters) but make the adoption choices themselves. Therefore, adopters and nonadopters may be systematically different as groups, and these differences may manifest themselves in farm performance. They could be confounded with differences due to the adoption of GE crops (i.e., the treatment). This situation, called self-selection, would bias the statistical results unless it is recognized and corrected.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

However, farmer surveys give a more accurate picture of the total farmlevel economic effects of GE-crop adoption in terms of the secondary behavioral changes resulting from adoption (e.g., adoption of conservation tillage and changes in the timing of pesticide application). Moreover, it is rarely the case that a farmer would or could choose to adopt a GE cultivar to replace a non-GE cultivar that is an isoline or near-isoline, so relying on agronomic experimental data to measure the economic differences can be biased. Also, only farmer surveys can reveal the value of the changes in nonpecuniary characteristics that can occur with the adoption of GE cultivars.

Social scientists often are able to statistically control for certain influencing factors for which there are data (apart from the GE-crop treatment) by using multiple regression techniques in econometric models. That is, differences in economic conditions and crop or management practices that also influence yield or other outcomes are held constant so that the effect of adoption can be isolated. For example, in research on GE crops, economists control for many factors, including output and input prices, pest infestation levels, farm size, operator characteristics, and management practices such as crop rotation and tillage. In addition, economists control for self-selection and simultaneity (of GE adoption and pesticide use decisions) using particular types of econometric models. To account for simultaneity of decisions and self-selectivity, a two-stage model may be used. The first stage consists of the adoption-decision model for GE crops. The second stage then uses the findings from the first stage to examine the impact of using GE crops on yield, farm profit, and pesticide use.

The Counterfactual. Ideally, measuring the impact of a treatment requires the observation of the results that would emerge in the absence of the treatment: a counterfactual. Aside from controlled experiments, it is not possible to observe this counterfactual outcome. Rather, the counterfactual is inferred by methods such as those summarized above (e.g., controlling for all other influencing factors). Moreover, regarding environmental impacts, Ferraro (2009) argues that “elucidating casual relationships through counterfactual thinking and experimental or quasi-experimental designs is absolutely critical in environmental policy and that many opportunities for doing so exist.” The use of the two-stage estimation procedure to correct for selection bias exemplifies such a quasi-experimental design. However, Ferraro also admits that “not all environmental programs are amenable to experimental or quasi-experimental design.” In those cases, firm conclusions cannot be drawn about the causative factors inducing GE-crop adoption or other outcomes of interest.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

farmers’ production expenses and altered their decisions related to time management. Furthermore, because of the widespread adoption of GE crops and their subsequent impact on yields, genetic-engineering technology has influenced the prices received by U.S. farmers.

Yield Effects

The first generation of GE varieties contains traits that control or facilitate the control of pest damage. A starting point for analyzing the productivity effect of such control is the damage-control framework (Lichtenberg and Zilberman, 1986) that was developed to estimate the effectiveness of the use of chemical pesticides and other pest-control activities. The framework recognizes that damage-control agents, like pesticides and GE traits for pest management, have an indirect effect on yield by reducing or facilitating the reduction of crop losses, in contrast with such inputs as fertilizers, capital, and labor, which affect yields directly. In particular, the framework assumes that

Potential yield is defined as the yield that would be realized in the absence of damage caused by pests (i.e., weeds, insects).1 It is a function of production inputs, such as water and fertilizer, and of agroecological conditions and seed varieties. The yield actually observed is called effective yield and is equal to potential yield minus damage. Damage is affected by the pervasiveness of pests, which may be controlled with pesticides, the adoption of GE varieties, or other control activities. With that framework, the yield effects of GE varieties can be analyzed, but spatial, temporal, and varietal factors must be taken into consideration.

Indirect Yield Effects

The indirect yield effects of the use of insect-resistant (IR) crops are most pronounced in locations and years in which insect-pest pressures are high. For example, it is generally recognized that the adoption of Bt corn for European corn borer (Ostrinia nubilalis) control resulted in annual average yield gains across the United States of 5–10 percent (Falck-Zepeda et al., 2000b; Carpenter et al., 2002; Fernandez-Cornejo and McBride, 2002; Naseem and Pray, 2004; Fernandez-Cornejo and Li, 2005). Empirical

1

Damage may also be caused by weather conditions, such as wind, rain, drought, and frost. For succinctness and convenience here, the definition of damage is restricted to pest problems.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

studies, however, have clearly indicated that the indirect yield effects of Bt corn hybrids for European corn borer control vary temporally and spatially. In years with high pressure—corn borer damage of more than one tunnel per plant that exceeds 2 inches in length (Baute et al., 2002; Dillehay et al., 2004)—the yield advantage for Bt hybrids relative to near-isolines2 was 5.5 percent in Pennsylvania and Maryland (Dillehay et al., 2004), 6.6 percent in Wisconsin (Stanger and Lauer, 2006), 8 percent in New Jersey and Delaware (Singer et al., 2003), 9.4 percent in Iowa (Traore et al., 2000), and 9.5 percent in South Dakota (Catangui and Berg, 2002). The yield advantage for Bt corn was negligible in those regions during years with low pest pressure (Traore et al., 2000; Catangui and Berg, 2002; Singer et al., 2003; Dillehay et al., 2004; Stanger and Lauer, 2006). Likewise, in regions where European corn borer is an occasional pest, there was no indirect yield advantage from the use of Bt hybrids in comparison to near-isolines (Cox and Cherney, 2001; Baute et al., 2002; Ma and Subedi, 2005; Cox et al., 2009). Most of the early empirical studies, however, included some Bt events3 that did not have season-long control of corn borer, and this may have muted the yield advantage of Bt hybrids (Traore et al., 2000; Catangui and Berg, 2002; Pilcher and Rice, 2003).

There have been fewer empirical studies of the yield effects of Bt corn for control of corn rootworm (Diabrotica spp.) than of the effects of Bt corn for control of European corn borer. Rice (2004) estimated potential annual benefits if 10 million acres of Bt corn for corn rootworm control were planted. They included

  • Intangible benefits to farmers (safety because of reduced exposure to insecticides, ease and use of handling, and better pest control).

  • Tangible economic benefits to farmers ($231 million from yield gains).

  • Improved harvesting efficiency due to reduced stalk lodging.

  • Increased yield protection (9 to 28 percent relative to that in the absence of insecticide use and 1.5 to 4.5 percent relative to that with insecticide use).

  • Reduction in insecticide use (a decrease of about 5.5 million pounds of active ingredient per 10 million acres).

2

Near-isolines are cultivars that have the same or near genetic constitution (except for alleles at one or a few loci) as the original cultivar from which they were developed. Near-transgenic isolines that have similar genetic makeup except for the transgenic trait allow a comparison of the cultivar with or without the transgene for its agronomic, quality, or nutritional aspects.

3

Each seed company has different events associated with different insertion places of the Bt gene and different promoter genes that allow a Bt toxin to be produced at different times of the season or in different plant parts.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×
  • Increased resource conservation (about 5.5 million gallons of water not used in insecticide application).

  • Conservation of aviation fuel (about 70,000 gallons not used in insecticide application).

  • Reduced farm waste (about 1 million fewer insecticide containers used).

  • Increased planting efficiency.

  • Improved safety of wildlife and other nontarget organisms.

A recent study by Ma et al. (2009) indicated spatial and temporal variability in indirect yield responses. Bt corn rootworm hybrids produced yields 11–66 percent larger than untreated near-isoline hybrids. Bt yields were also larger than yields of the non-Bt hybrid variety planted on clay soils and treated with insecticide in 1 of 3 years that had high infestations of western corn rootworm (Diabrotica virgifera virgifera). On sandy soils, where corn rootworm infestations are typically much lower than on clay soils, yield differences also occurred between Bt corn rootworm hybrids and their near-isolines with or without the standard soil-applied insecticide treatment in 1 of 2 years. The study reported low levels of western corn rootworm on droughty sandy soil, however, and attributed yield increase to improved drought tolerance from the finer, longer fibrous roots of the Bt hybrid corn. Cox et al. (2009) found no yield advantage for corn hybrids with Bt rootworm control compared with near-isolines in a dry year when rootworm damage did not occur.4

Gray et al. (2007) expressed concern that one of the Bt corn rootworm events was somewhat susceptible to injury by a variant of western corn rootworm in Illinois. Another Bt corn rootworm event, however, had superior control of western corn rootworm larvae in Iowa, Illinois, and Indiana (Harrington, 2006); this suggests that distinct Bt events from different seed companies may differ somewhat in corn rootworm control as they did initially in corn borer control. Cox et al. (2009) evaluated both Bt rootworm events on second-year corn in field-scale studies on four farms

4

As discussed in Chapter 1, all Bt rootworm corn hybrids are treated with a low level of insecticide and fungicide (typically a neonicotinoid). The low level (0.25 mg of active ingredient per seed) targets secondary pests but does not affect corn rootworm. In fields planted continuously with corn, the low level used with a soil-applied insecticide resulted in lower corn yields compared to a high level (1.25 mg of active ingredient per seed) with a soil-applied insecticide (Cox et al., 2007c). That is indirect evidence that the high level of seed-applied insecticide increases control of corn rootworm, but the low level does not. In addition, the low and high levels of seed-applied insecticides had no positive effects on corn grain (Cox et al., 2007b) or corn silage yields (Cox et al., 2007a) when following soybean, which suggests there is no yield enhancement of these seed-applied insecticides in the absence of pests.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

in New York and found that neither rootworm event provided a yield advantage because rootworm occurrence was low in all fields. As with Bt corn for corn borer, Bt corn for rootworm control did not provide an indirect yield benefit in the absence of pest pressure.

Piggott and Marra (2007), relying on 1999–2005 university field-trial data from North Carolina, found that Bt cotton with two endotoxins out-yielded conventional cotton by 128 more lbs of lint per acre (14 percent of average yield in the region) and out-yielded Bt cotton with one endotoxin by 80 lb/acre (8 percent of average regional yield). A study of Bt cotton varieties with two endotoxins in 13 southern locations that had mostly moderate to high infestations of cotton bollworm (Helicoverpa zea), with or without foliar-applied insecticides, showed that indirect yield effects had spatial variability. The Bt cotton cultivars without insecticide use provided consistent control of the Heliothines (cotton bollworm and tobacco budworm, Heliothis virescens), regardless of the magnitude of infestation (Siebert et al., 2008). Furthermore, supplemental insecticide applications to the Bt cotton cultivars rarely improved control of budworm and bollworm. In the low-infestation environments, however, the use of Bt cultivars with or without insecticides provided no yield improvement relative to the control of the non-Bt cultivar without insecticide application. In the moderate- to high-infestation environments, the Bt cultivars provided the same 30-percent yield increase in lint yield with or without insecticides compared with the control (Siebert et al., 2008). In a large-scale study of 81 commercial cotton fields conducted in 2002 and 2003, average yield did not differ among Bt cotton, Bt cotton resistant to glyphosate, and non-GE cotton (Cattaneo et al., 2006). However, after statistical control for variation in two factors significantly associated with yield (number of applications of synthetic insecticide and seeding rate), the yield of Bt cotton and Bt cotton with herbicide resistance was significantly larger (by 8.6 percent) than the yield of non-GE cotton. A total of eight GE cotton cultivars and 14 non-GE cultivars were included in the study. For those cultivars, it appears that Bt cotton (herbicide-resistant or not) would generally out-yield non-Bt cotton given similar production inputs and agronomic conditions.

The indirect yield effects of herbicide-resistant (HR) crops generally may have less spatial and temporal variability because weeds are ubiquitous and cause yield losses in most situations. For example, the use of HR soybean with timely glyphosate application almost always achieves yield gains relative to production without weed control (Tharp and Kells, 1999; Corrigan and Harvey, 2000; Mulugeta and Boerboom, 2000; Wiesbrook et al., 2001; Kneževič et al., 2003a, 2003b; Dalley et al., 2004; Scursoni et al., 2006; Bradley et al., 2007; Bradley and Sweets, 2008). Likewise, the use of HR corn and cotton varieties with timely glyphosate

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

application almost always results in yield increases (Culpepper and York, 1999; Johnson et al., 2000; Gower et al., 2002; Dalley et al., 2004; Richardson et al., 2004; Sikkema et al., 2004; Thomas et al., 2004; Cox et al., 2005; Myers et al., 2005; Sikkema et al., 2005; Cox et al., 2006; Thomas et al., 2007).

Yield Lag and Yield Drag

Despite properties that result in indirect yield benefits, some farmers observed a yield reduction when they first adopted HR varieties (Raymer and Grey, 2003). Indeed, shortly after the adoption of glyphosate-resistant soybean, university soybean trials reported lower yields of HR varieties (Oplinger et al., 1998; Nielsen, 2000). In a study that compared five HR varieties with five non-HR varieties in four locations in Nebraska, evidence of “yield lag” and “yield drag” was found (Elmore et al., 2001a, 2001b).5 A 5-percent yield lag was due to the difference in productivity potential between the older germplasm used to develop the HR varieties and the newer, higher yielding germplasm of the non-HR varieties.6 A 5-percent yield drag resulted from the reduced production capacity of the soybean plant following the presence or insertion process of the HR gene (Elmore et al., 2001b). Although not as pronounced as in the Nebraska study, Bertram and Petersen (2004) also presented data that indicated a potential yield lag at one location in Wisconsin with the early HR soybean varieties.

Fernandez-Cornejo et al. (2002b) reported that a national farm-level survey indicated that HR soybean showed a small advantage in yield over conventional soybean, probably because of better weed control.

5

Yield lag is a reduction in yield resulting from the development time of cultivars with novel traits (in this case, glyphosate resistance and Bt). Because of the delay between the beginning of the development of a cultivar with a novel trait and its commercialization, the germplasm that is used has lower yield potential than the newer germplasm used in cultivars and hybrids developed in the interim. Consequently, the cultivars with novel traits have a tendency to initially yield lower than new elite cultivars without the novel traits. Over time, the yield lag usually disappears.

Yield drag is a reduction in yield potential owing to the insertion or positional effect of a gene (along with cluster genes or promoters). This has been a common occurrence throughout the history of plant breeding when inserting different traits (e.g., quality, pest resistance, and quality characteristics). Frequently, the yield drag is eliminated over time as further cultivar development with the trait occurs.

6

During selection for a particular trait in a plant-breeding program, many other traits may also change. Such “correlated” changes may occur because a gene controls more than one trait (pleiotropy), because genes controlling two traits are in physical proximity on a chromosome (linkage), or because of random segregation (drift). The distinctions among the three causes are important because the solutions to them differ. Solutions may be necessary because some correlated changes are undesirable.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

A national survey of soybean producers in 2002 found that there was no statistical difference in yield between conventional soybean and HR soybean (Marra et al., 2004). A mail survey of Delaware farmers in 2001 found that HR soybean had a 3-bushel/acre yield advantage (Bernard et al., 2004). The survey data and results of empirical studies in Wisconsin indicate that the use of more elite germplasm in variety development has probably eliminated the yield lag or yield drag associated with the use of HR varieties (Lauer, 2006).

Similarly, early empirical studies of Bt corn hybrids indicated a potential yield lag, as indicated by the lower yield of Bt hybrids than of new elite hybrids (Lauer and Wedberg, 1999; Cox and Cherney, 2001). However, Bt hybrids yielded as well as or better than near-isolines (Lauer and Wedberg, 1999; Traore et al., 2000; Cox and Cherney, 2001; Baute et al., 2002; Dillehay et al., 2004), and this suggests that there was no yield drag or loss of yield because of the insertion of the Bt gene with the early Bt corn hybrids.

Furthermore, whether a yield loss or a yield increase materializes for a GE crop depends on the particular farming situation. For example, in their comparison of HR corn hybrids with non-HR varieties, Thelan and Penner (2007) reported that in low-yield environments HR hybrids yielded 5 percent more than non-HR hybrids and in high-yield environments non-HR hybrids yielded about 2 percent more than HR hybrids. An early study of cotton (May and Murdock, 2002) that compared first-generation glyphosate-resistant cultivars with nonresistant cultivars showed no yield lag in glyphosate-resistant cultivars and a yield advantage of using glyphosate instead of the standard conventional soil-applied herbicides. The results of the study suggested that the use of soil-applied herbicides resulted in some type of injury to cotton, whereas glyphosate application before the fourth leaf stage did not. A study at nine locations across the United States (May et al., 2004) showed that one of Monsanto’s later glyphosate-resistant cotton lines provided even greater yield than the first-generation glyphosate-resistant cotton when glyphosate was applied from the fourth to the 14th leaf stage; this resulted in an agronomic advantage of the later technology.

A 2002 U.S. Department of Agriculture (USDA) survey found that increases in cotton yields in the Southeast were associated with the adoption of HR cotton and Bt cotton in 1997: A 10-percent increase in HR-cotton acreage led to a 1.7-percent increase in yield and a 10-percent increase in Bt cotton acreage led to a 2.1-percent increase in yield if other productivity-influencing factors were constant (Fernandez-Cornejo and Caswell, 2006).

It was noted above that most of the yield studies of GE versus non-GE crops conducted in the United States used data from the late 1990s

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

and early 2000s.7 Any yield differences between GE and non-GE varieties found during the first 5 years of adoption could have diminished as seed companies developed new IR and HR events. One reason for the lack of recent studies on yields may be that it is increasingly difficult to find sufficient data on non-GE varieties owing to the predominance of GE varieties in major crops (see Chapter 4).

Improved Crop Quality and Risk Management

Bt corn has been found to decrease concentration of the toxic chemical aflatoxin (Wiatrak et al., 2005; Williams et al., 2005) and some other mycotoxins produced by fungi (fumonisins in particular) in the grain (Clements et al., 2003). In doing so, it decreases the risk of price dock-age to farmers because of poor crop quality and increases food safety for consumers. Bt crops also have reduced stalk lodging at harvest (Rice, 2004; Wu et al., 2005; Stanger and Lauer, 2006; Wu, 2006);8 this improves crop quality and increases harvest efficiency, thus reducing the farmers’ fuel and labor costs. A benefit of the use of HR soybean is that the presence of foreign matter (such as weed seeds) in the harvested crop has greatly decreased (from 5-25 percent to 1-2 percent in the southeastern states) (Shaw and Bray, 2003), reducing the need for handlers to blend soybean with high foreign matter with soybean with lower foreign matter to improve the overall quality of the crop.

The use of GE crops can also reduce agronomic risks for farmers. For example, in the case of HR crops, glyphosate breaks down quickly in the soil, removing the potential for the residual herbicide to injure a succeeding crop (Scursoni et al., 2006). Additionally, some Bt varieties may improve drought tolerance (Wilson et al., 2005). Empirical studies have not documented that the use of Bt corn for corn borer provides a yield benefit in the presence of drought (Traore et al., 2000; Dillehay et al., 2004; Ma et al., 2005), but Ma et al. (2009) found in an empirical study on Bt corn for corn rootworm that in a drought year on sandy soil, the Bt corn rootworm hybrid yielded 10 percent more than the near-isoline. The roots of the Bt corn rootworm hybrids were longer and more dense than those of the non-GE hybrid because the Bt trait kills the below-ground larvae that feed on the roots of the corn plant. Ma et al. (2009) speculated that Bt

7

More recent data from field trials are available but have not been published in peer-reviewed literature.

8

Stalk lodging is the permanent displacement of the stems of crops from their upright position, resulting in a crop that either leans or can be prostrate. A mildly lodged crop results in only a slight slowdown of harvest, whereas a severely lodged crop greatly slows down harvest (in some instances the crop can only be harvested in one direction, further reducing harvesting efficiency).

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

corn rootworm hybrids may have more drought tolerance than standard hybrids in drought years because the root system is more intact and therefore capable of taking up more water. Such risk reduction may explain in part farmers’ motivation to adopt these GE crops. A related risk posed by adoption of Bt corn in northern latitudes, however, is the potential for higher grain moisture at harvest because of improved plant health, which increases drying costs or delays harvest (Pilcher and Rice, 2003; Dillehay et al., 2004; Ma and Subedi, 2005; Cox et al., 2009).

Because GE crops have the ability to reduce yield loss, adopting farmers also have different insurance options for managing risk. In 2007, Monsanto developed a submission to the USDA Federal Crop Insurance Corporation for a new crop-insurance endorsement for corn that contains three traits: a Bt toxin that controls corn borer, one that controls corn rootworm, and herbicide resistance.9 The submission proposed a premium-rate discount for those hybrids based on several thousand on-farm field trials conducted over several years in the Corn Belt states of Illinois, Indiana, Iowa, and Minnesota. The trials demonstrated the yield and yield-risk reduction advantages of the hybrids compared with conventional or single-trait HR hybrids and showed that the current premium rates were no longer actuarially appropriate. A lower insurance premium became available in the 2008 crop year to farmers who adopted the triple-stacked hybrids. The rate discount was applied to the yield portion of the premium for actual production history of the field and based policies on crop-insurance units in which at least 75 percent of the acreage was planted to qualifying corn hybrids. The average premium-rate discount was 13 percent in 2008, or about $3.00/acre.

Comparable triple-stacked hybrids from seed companies Dupont/ Pioneer and Syngenta were approved for inclusion in the program for the 2009 crop year, and the premium-rate discount applies to all three companies’ and licensees’ seed brands that contain at least the above-mentioned traits for dryland corn in at least a subset of 13 Midwest states and irrigated corn in Kansas and Nebraska. This is the first approved crop-insurance innovation that has resulted in reduced premium rates, and it provides a saving for farmers and reduces the need for premium subsidies by the federal government. Cox et al. (2009), however, found no consistent yield or economic advantage for triple-stacked hybrids compared to double-stacked hybrids from both companies in second-year corn in New York, despite one of the years being dry and warm. In both years, corn rootworm damage was low, and corn borer damage was sporadic across locations.

9

These products are marketed by Monsanto as YieldGard® Plus, Roundup Ready 2®, and YieldGard VT Triple® hybrids.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Production Expenses

The use of GE crops triggers changes in several production expenses, particularly those related to seed technology, pesticide expenditures, labor and management requirements, and machinery operations.

Seed Prices

U.S. farmers pay for the GE traits in the seeds that they plant in the form of a technology fee because GE seeds are considered proprietary in the United States. The market price of seed, which includes the technology fee, incorporates the costs associated with development, production, marketing, and distribution (Fernandez-Cornejo and Gregory, 2004). The price must be responsive to farmers’ willingness to purchase the technology while ensuring an attractive return on capital to the seed development firms (technology provider and licensee seed companies or distributors) and their investors. The price also depends on the competitiveness of the particular seed market and on the pricing behavior of firms that hold large shares of the market.

In recent decades, private-sector research and development costs have risen with the application of new technologies. Much of the increase in seed prices paid by U.S. farmers has been associated with that general trend (Krull et al., 1998). The seed-price index has exceeded the average index of prices paid by U.S. farmers by nearly 30 percent since the introduction of GE seeds in 1996 (Figure 3-1). The contrast is even starker for cotton and soybean. After adjustment for inflation, the real average cotton seed price almost tripled between 1996 and 2007 (Figure 3-2), while the soybean seed price grew by more than 60 percent.

The rise in real seed prices can be accounted for by improvements in germplasm, by the increasing price premiums paid for GE seed, and by the growing share of GE seed purchased by U.S. farmers (as the share of seed saved by farmers correspondingly decreased). The price premium, which includes the technology fee, doubled in real terms for GE cotton seed between 2001 and 2007 (adjusted for inflation) (Figure 3-3). U.S. farmers also experienced similar price-premium increases for corn and soybean seed (Figures 3-4 and 3-5). Some of the increase reflects the larger number of services that the seed delivers to the buyers compared with conventional seed. For example, farmers who purchase Bt cotton receive the seed germplasm and an insecticide combined in one product, whereas for non-GE crops they must buy each separately and pay for costs related to applying the insecticide. The increase also reflects the additional value to the farmer provided by later GE cultivars with more than one type of trait or more than one mode of action for particular target pests. The rates of adoption noted in Chapter 1 indicate that the price premiums have not

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×
FIGURE 3-1 Seed-price index and overall index of prices paid by U.S. farmers.

FIGURE 3-1 Seed-price index and overall index of prices paid by U.S. farmers.

SOURCE: Fernandez-Cornejo, 2004; USDA-NASS, 2000, 2005, 2009a.

FIGURE 3-2 Estimated average seed costs for U.S. farmers in real (inflation-adjusted) terms.

FIGURE 3-2 Estimated average seed costs for U.S. farmers in real (inflation-adjusted) terms.

SOURCE: Fernandez-Cornejo, 2004; USDA-NASS, 2000, 2005, 2009a.

deterred many U.S. farmers from purchasing GE seeds and that non-GE seed options were less attractive or were not available.

Other Input Costs

If U.S. farmers who have adopted GE crops pay higher prices for the seed, have they experienced compensatory cost reduction for other

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×
FIGURE 3-3 Real (inflation-adjusted) cotton seed prices paid by U.S. farmers, 2001–2007.

FIGURE 3-3 Real (inflation-adjusted) cotton seed prices paid by U.S. farmers, 2001–2007.

SOURCE: USDA-NASS, 2000, 2005, 2009a.

FIGURE 3-4 Real (inflation-adjusted) corn seed prices paid by U.S. farmers, 2001–2008.

FIGURE 3-4 Real (inflation-adjusted) corn seed prices paid by U.S. farmers, 2001–2008.

SOURCE: USDA-NASS, 2000, 2005, 2009a.

inputs? With insect-resistance technology, a plant contains its own insecticide, whereas most HR crops are engineered to be used with the herbicide glyphosate. Have those conditions changed adopters’ farming practices and purchasing habits?

Economic reasoning suggests that the influence of genetic engineering on pesticide use depends on whether the GE cultivar and the pesticides are complementary or substitute inputs (Just and Hueth, 1993). Where IR or stacked GE cultivars substitute for other pesticides, chemical-pesticide

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×
FIGURE 3-5 Real (inflation-adjusted) soybean seed price paid by U.S. farmers, 2001–2008.

FIGURE 3-5 Real (inflation-adjusted) soybean seed price paid by U.S. farmers, 2001–2008.

SOURCE: USDA-NASS, 2000, 2005, 2009a.

use should decline. That is often the case with Bt crops (see Chapter 2, Figures 2-7 and 2-8). For HR crops, it often means reducing the use of less effective, more costly, and possibly more toxic herbicides although exceptions occur (Cattaneo et al., 2006). That substitution effect can produce cost savings as well as reductions in environmental and human health risks associated with chemical applications (Sydorovych and Marra, 2007). Several studies have attempted to establish whether the adoption of GE crops affects pesticide use. Some early investigations found evidence of a decline in pesticide use as adoption of GE crops increases (Heimlich et al., 2000; Hubbell et al., 2000; Carpenter et al., 2001; Marra et al., 2002). Some studies have found that most of the reduction in pesticide use resulting from adoption of an IR cultivar was in highly toxic chemicals, and average toxicity declined with adoption (Heimlich et al., 2000; Sydorovych and Marra, 2007). However, others have concluded that pesticide use increases in tandem with GE-crop production (Benbrook, 2004). Such contradictory findings have been attributed to the different approaches to measuring pesticide use, specifically

  • How pesticide use is recorded (pesticide active-ingredient volume, formulated volume, relative toxicity, or number of applications) (Sydorovych and Marra, 2007).

  • Which factors are controlled for (results would vary from region to region and from year to year depending on the extent of pest infestation, weather, cropping patterns, and so on).

  • The method of aggregation (Frisvold and Marra, 2004).

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

A general overarching effect cannot be discerned because of the variability in specific conditions on different farms and in different regions.

The observed change in pesticide use with IR crops depends on the crop and the pest. Changes in insecticide use for treatment of European corn borer were minimal because many farmers accepted yield losses rather than incur the expense and uncertain results of chemical control. A survey of corn growers in Iowa and Minnesota determined that only 30 and 17 percent, respectively, had managed European corn borer with insecticides during any season in the early 1990s because chemical use was not always profitable and timely application was difficult owing to the unpredictability of pest outbreaks (Rice and Ostlie, 1997).

In the case of Bt cotton, however, GE control greatly reduced expenditures on pesticides to treat tobacco budworm, pink bollworm (Pectinophora gossypiella), and cotton bollworm (Jackson et al., 2003; Cattaneo et al., 2006). Survey data indicated that the number of insecticide sprays and insecticide costs generally decreased with the adoption of GE cotton across the United States (Table 3-1). Where measurable, farm-level profit was also shown to have increased with the adoption of Bt cotton in all states (Piggott and Marra, 2007). Although the studies reported in Table 3-1 seem to suggest that insecticide costs increased after commercialization of Bt cotton in Arizona, detailed surveys of insecticide use and costs conducted since 1979 clearly show that use and costs were drastically reduced after 1996 (Ellsworth et al., 2009). One major factor in the reductions has been the efficient control of pink bollworm by Bt cotton (Carrière et al., 2003, 2004). However, other critical factors in reducing insecticide use and cost were the introduction of novel and highly efficient insecticides for the control of whitefly (Bemisia tabaci)in cotton (Carrière et al., 2004) and the success of the boll weevil eradication program (Fernandez-Cornejo et al., 2009). That illustrates an important point (see Chapter 2): Longitudinal data on pesticide use should not be taken at face value in assessing the effects of GE crops without controlling for other influences, as many factors can contribute to changes in patterns of insecticide use.

Bt corn is a preferred method for growers for controlling rootworm because of its simplicity and safety in applying it compared with soil-applied insecticides or with higher levels of active ingredient in seed treatments on non-Bt corn seed10 (Al-Deeb and Wilde, 2005; Vaughn et al., 2005; Ahmad et al., 2006). The adoption of Bt corn for rootworm control

10

As discussed in Chapter 1, Bt corn hybrid seed for corn rootworm control has 0.25 mg of active ingredient of insecticide and fungicide applied per seed compared to 1.25 mg of active ingredient applied to non-Bt corn hybrids.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

has resulted in a substantial reduction in insecticide use, by an estimated 5.5 million pounds of active ingredient per 10 million acres (Rice, 2004).

In addition to the pesticide quantity effects, the adoption of HR and IR crops lowers the demand of competing pesticides used on conventional varieties and may therefore lower the prices of these pesticides. Huso and Wilson (2006) shows that this effect benefits farmers who adopt the GE variety and those who plant the conventional variety.

Indirect cost differences between GE crops and conventional crops originate in the adoption of practices that are linked to the adoption of some GE crops. For example, if a GE crop reduces the need for till-age to control weeds, reductions in machinery, fuel, and labor for the avoided cultivation practices amount to indirect cost savings. The indirect cost differences are particularly important for HR crops because of the complementary relationship between their adoption and conservation tillage. That is, GE-crop adoption increased the probability of adoption of conservation tillage, and conservation tillage increased the probability of higher adoption of GE crops (for a more detailed discussion of conservation tillage, see Chapter 2).

The increased use of conservation tillage has been facilitated by the commercialization of more effective postemergence herbicides, such as glyphosate, that can be applied topically to crops and weeds. Glyphosate can supplement or replace tillage as a tool for controlling most weeds and in so doing can reduce the use of machinery and fuel and lower labor requirements (Harman et al., 1985; Chase and Duffy, 1991; Baker et al., 1996; Downs and Hansen, 1998; Boyle, 2006; Baker et al., 2007).. Mitchell et al. (2006) reported that a reduced-tillage system in the planting of California cotton reduced the number of tractors in operation by 41 to 53 percent, fuel use by 48 to 62 percent, and overall production costs by 14 to 18 percent. Sanders (2000) reviewed and summarized results of several studies and concluded that conservation tillage can reduce fuel costs by as much as 50 percent and labor costs by up to 40 percent. Those conclusions agree with USDA Natural Resources Conservation Service estimates that Iowa farmers would save 30–50 percent in fuel costs by adopting conservation-tillage practices (Table 3-2). Using Nebraska survey data for various row crops, Jasa (2000) showed that fuel use for no-till was 1.43 gal/acre compared with 5.28 gal/acre for moldboard-plow tillage and that labor requirements for no-till were 0.49 hours/acre, compared with 1.22 hours/acre for moldboard-plow use.

The financial returns to GE crops should vary directly with fuel prices if they save costly machinery passes over a field. HR crops do not necessarily save passes over a field, but they do substitute herbicide applications for more expensive and more fuel intensive methods of weed management, such as intensive tillage practices or the use of

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

TABLE 3-1 Summary of Farm-Level Impact Evidence for Genetically Engineered Cotton in the United States, 1996–1999

Transgene Type, State

Differences in:

Yield

Pesticide Cost

Number of estimates

Mean

Minimum

Maximum

Number of estimates

Mean

Minimum

Maximum

 

(count)(pounds lint per acre)

(count) (dollar/acre)

Bt cotton

 

 

 

 

 

 

 

 

Alabama

4

143.5

231.5

38.0

2

−32.4

3.1

−68.0

Arizona

8

116.7

917.0

−331.5

9

17.1

97.0

−24.6

Georgia

3

75.2

104.0

38.0

3

−23.4

27.5

−68.0

Louisiana

2

−7.5

22.0

−37.0

2

−20.0

−15.4

−24.6

Mississippi

8

22.6

92.0

−73.0

8

−5.1

13.8

−24.6

North Carolina

8

41.6

182.5

−35.7

2

−14.3

−1.2

−27.5

Oklahoma

4

168.0

203.0

123.0

 

 

 

 

South Carolina

2

90.5

119.0

62.0

2

−16.2

−1.2

−31.1

Tennessee

2

−79.0

85.0

−243.0

1

−5.6

 

 

Texas

3

116.6

177.5

81.0

 

 

 

 

Virginia

1

62.0

 

 

1

−1.2

 

 

RRa cotton

 

 

 

 

 

 

 

 

Arkansas

1

−150

 

 

 

 

 

 

Tennessee

1

−243

 

 

1

−145.3

 

 

Bt/RR cotton

 

 

 

 

 

 

 

 

Arkansas

2

292.8

–331.5

917.0

2

79.5

–269.0

159.0

aMonsanto markets its glyphosate-resistant varieties under the trademarked name Roundup Ready.

SOURCE: Adapted from Marra, 2001.

herbicides that require physical incorporation into the soil. Also, with potentially fewer passes over the field, tractor and spraying equipment lasts longer, and this results in savings in machinery and equipment costs over the long term.

Management Requirements and Nonpecuniary Benefits

Many of the commercially available GE products have consistently been shown to be profitable for U.S. farmers. For example, the profitability of Bt cotton in the Cotton Belt and Bt corn for controlling corn rootworm is well documented (Marra, 2001; Alston et al., 2002). However, the national evidence supporting the use of HR soybean is inconclusive (Bullock and

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Pesticide Use

Profit

Number of estimates

Mean

Minimum

Maximum

Number of estimates

Mean

Minimum

Maximum

(count) (sprays/acre)

(count) (dollars/acre)

2

−1.3

0.3

−3.0

2

77.6

116.5

38.7

3

−2.2

−1.8

−2.5

10

57.5

465.0

−104.0

3

−2.7

−2.5

−3.0

3

92.0

169.2

38.7

2

−2.4

−2.2

−2.5

2

16.5

36.0

−3.1

4

−2.4

−1.3

−3.3

6

34.5

79.5

−3.1

2

−2.4

−2.4

−2.5

8

20.5

95.1

−25.3

4

−3.4

−2.3

−6.5

4

53.8

85.5

25.5

2

−2.5

−2.5

−2.5

4

51.8

80.1

17.1

1

−1.8

 

 

2

67.5

74.3

60.7

 

 

 

 

1

46.0

 

 

1

−2.5

 

 

1

41.7

 

 

 

 

 

 

1

17.1

 

 

 

 

 

 

1

74.3

 

 

 

 

 

 

2

243.0

21.0

465.0

TABLE 3-2 Fuel Consumption by Tillage System (Gallons per Year)

Crop

Acres

Conventional Tillage

Mulch Till

Ridge Till

No-Till

Corn

1,000

4,980

3,710

3,330

2,770

Soybean

1,000

4,980

3,110

3,330

1,970

Total fuel use

 

9,960

6,820

6,660

4,740

Potential fuel savings over conventional tillage

 

 

3,140

3,300

5,220

Saving

 

 

32%

33%

52%

SOURCE: USDA-NRCS, 2008.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Nitsi, 2001; Gardner and Nelson, 2007). Fernandez-Cornejo et al. (2002b) and Fernandez-Cornejo and McBride (2002) evaluated 1997 field-survey data and 1998 whole-farm survey data, respectively, and found that the differences in net returns between adopters and nonadopters of HR soy-bean were not significant. This lack of significance is consistent with findings from other producer surveys (Couvillion et al., 2000; Duffy, 2001). In light of high overall adoption rates, those findings suggest that other considerations have motivated farmers to use genetic-engineering technology. The wide adoption of HR soybean despite the associated technology fee stimulated research to identify possible nonpecuniary benefits to GE adopters that motivate such a shift in technology use.

In addition to the substantially superior control of a broad spectrum of weeds (Scursoni et al., 2006), simplicity, flexibility, and increased worker safety have been suggested as root causes of herbicide-resistance technology adoption, in that growers can use one herbicide instead of several to control a wide array of broadleaf and grass weeds (Gianessi and Carpenter, 1999; Bullock and Nitsi, 2001). The convenience of HR soybean use may mean that farmers can reduce the time that they spend scouting fields for weeds and mixing and spraying different herbicides to address various weed problems (Bullock and Nitsi, 2001). Furthermore, the window of application for glyphosate is wider than that for other post-emergence herbicides. That application flexibility can effectively control weeds but often the weeds have already caused a loss in potential crop yield by the time glyphosate is applied.

However, quantifying the simplicity, flexibility, and safety of pest-control programs has been difficult. The inability to include a measure of management time in the evaluation of benefits of new technologies in agriculture is not unique to HR soybean. As Fernandez-Cornejo and Mishra (2007) observed, assessments of technology adoption using traditional economic tools pioneered by Griliches (1957) have proved insufficient to explain differing rates of adoption of many recent agricultural innovations. The standard measures of farm profits, such as net returns to management, give an incomplete picture of economic returns because they usually exclude the value of management time itself (Smith, 2002). HR soybean was adopted rapidly despite showing no statistically significant advantage in net returns over conventional soybean in most studies, but adoption of such strategies as integrated pest management has been rather slow even though it has explicit economic and environmental advantages (Fernandez-Cornejo and McBride, 2002; Smith, 2002). That inconsistency led to the hypothesis that HR adoption is driven by unquantifiable advantages—such as presumed simplicity, flexibility, and safety—that translate into a reduction in managerial intensity, which frees time for other pursuits, and into increased worker safety.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

An obvious use of managers’ time is off-farm employment; alternatively, a farmer could farm more acreage to increase farm income. Fernandez-Cornejo and collaborators examined the interaction of off-farm income-earning activities and adoption of different agricultural technologies of varied managerial intensity, including HR crops (Fernandez-Cornejo and Hendricks, 2003; Fernandez-Cornejo et al., 2005) and Bt corn (Fernandez-Cornejo and Gregory, 2004). They also estimated empirically the relationship between the adoption of those innovations and farm household income from on-farm and off-farm sources. To do that, they expanded the agricultural household model to include the technology-adoption decision and off-farm work-participation decisions by the operator and spouse (Fernandez-Cornejo et al., 2005; Fernandez-Cornejo and Mishra, 2007).

Those studies hypothesized that adoption of management-saving technologies frees operators’ time for use elsewhere, most notably in off-farm employment, and that leads to higher off-farm income. They found that the relationship between the adoption of HR soybean and off-farm household income is positive and statistically significant: After controlling for other factors, a 15.9-percent increase in off-farm household income is associated with a 10-percent increase in the probability of adopting HR soybean. The adoption of HR soybean is also positively and significantly associated with total household income from off-farm and on-farm sources. A 9.7-percent increase in total household income is associated with a 10-percent increase in the probability of adopting HR soybean. In contrast, and consistent with the lack of higher returns from this technology, adoption of HR soybean did not have a significant relationship with household income from farming. Those findings complement the findings of Gardner and Nelson (2007), who used national survey data from 2001–2003 and found that adopting HR soybean reduced household labor requirements by 23 percent.

Studies have also found that farmers value the convenience and reduced labor requirements of Bt cotton above and beyond the pecuniary benefits. Because conventional cotton faces heavy pest pressure, IR varieties decrease the time demands of spraying, and this leads to a 29-percent reduction in household labor requirements (Gardner and Nelson, 2007). Survey data of Marra and Piggott (2006) support the finding that farmers place a monetary value on the convenience, flexibility, and relative safety of GE crops. In a stated-preference approach, participants in four surveys placed values on such characteristics as saved time, operator and worker safety, and total convenience. In each survey that evaluated the total-convenience attribute of genetic-engineering technology, it made up over 50 percent of the total value placed on nontraded aspects of the GE crop (Table 3-3). The median total value of convenience ranged from $3.33/acre

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

TABLE 3-3 Value and Relative Importance of Nonpecuniary Benefits to Farmers

Characteristic

Rescaleda

Median (%)

Mean (%)

Std Dev (%)

Share (%)

Corn Rootworm Survey: n = 367

Time saving

0.588

0.997

1.390

23.86

Equipment saving

0.400

0.724

0.969

17.51

Operator and worker safety

0.429

0.991

1.623

17.12

Environmental safety

0.208

0.787

1.565

10.88

More consistent stand

0.800

1.773

2.862

30.63

Sum of the parts

3.000

5.272

6.222

 

National Soybean Survey: n = 113

Operator and worker safety

0.913

1.660

2.026

20.97

Environmental safety

1.304

1.961

2.201

24.89

Total convenience

3.333

4.158

3.690

54.14

Sum of parts

5.000

7.779

6.026

 

North Carolina Herbicide-Resistant Crop Survey: n = 52

Operator and worker safety

2.361

2.923

2.783

23.91

Environmental safety

1.666

2.720

2.660

20.45

Total convenience

5.000

7.793

7.818

55.63

Sum of parts

10.000

13.437

10.612

 

Roundup Ready®Flex Cotton Survey: n = 72

Operator and worker safety

1.875

3.056

4.061

23.90

Environmental safety

0.958

2.592

3.382

18.06

Total convenience

5.000

11.180

15.441

58.04

Sum of parts

10.000

16.828

17.383

 

aRescaled to conform the magnitude of the overall value, which is asked as a separate question.

SOURCE: Marra and Piggott, 2006.

per year for soybean to $5.00/acre per year for HR cotton. Survey respondents also placed a value on the improved operator and worker safety characteristics of GE crops. Farmers valued the reduction in handling and toxicity of the pesticides involved with those crops at $0.43–$2.36/acre per year. Although initially they increase the demand for GE seeds, the perceived management benefits may cause the demand for the seeds to become more inelastic (i.e., less responsive to price increases) over time. As farmers get accustomed to the characteristics and continue to place a value on them, increases in seed expenditures through either a price increase or an increase in user cost will not reduce the use of GE seeds by as large an amount as when the nonpecuniary attributes are not present (Piggott and Marra, 2008).

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Management benefits do not appear to influence the adoption of GE corn. Fernandez-Cornejo and Gregory (2004) did not find a statistically significant relationship between adoption of Bt corn (to control corn borer) and off-farm household income, and Gardner and Nelson (2007) noted no effect of adoption of Bt or HR corn on household labor. The lack of a significant relationship supports the observation that most farmers accepted yield losses rather than incur the expense and uncertainty of chemical control for European corn borer before the introduction of Bt corn (Fernandez-Cornejo et al., 2002a). For those farmers, the use of Bt corn was reported to result in yield gains rather than pesticide-related savings, and savings in managerial time were small. However, one of the benefits of adoption of Bt corn for rootworm control is that it makes it unnecessary to handle toxic insecticides at planting or to deal with high rates of insecticide-treated seeds.

Thus, the econometric results are consistent with anecdotal statements that many GE crops save managerial time because of the associated simplicity and flexibility of pest control. In the case of some GE crops, such as HR soybean, these nonpecuniary benefits provide incentives for adoption that counteract the additional cost of GE seeds. Indeed, the benefits increase demand for the GE seeds, and that in turn supports a higher price. In the case of other GE crops, such as Bt cotton, nonpecuniary benefits are accrued above and beyond additional farm profits.

Lower management costs and increased yield and nonpecuniary benefits have figured in the economic value of the natural refuge for cotton with two endotoxins for control of the bollworm-budworm complex. As discussed in Chapter 2, the Environmental Protection Agency (EPA) changed the refuge requirement for these IR cotton varieties from a 20-percent refuge treated with insecticide (or a 5-percent refuge not treated with insecticides) to a natural refuge where wild host plants constitute the refuges. The benefits of the refuge change were estimated for North Carolina to be $26.90 per year per impacted acre when pecuniary and nonpecuniary impacts were considered (Piggott and Marra, 2007).

Value and Market-Access Effects

In addition to the input-cost effects, the use of GE crops can affect the revenue potential of farmers. Two such effects can occur: foreign yield effects on the prices of products sold and market access to sell the GE crops.

Increase in grain and oilseed supplies should result in downward pressure on the prices received by farmers, all else being equal. Genetic-engineering technology helped to boost yields that had already been growing over the last 70 years through improved plant-breeding techniques.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

As a result, supply exceeded demand; the real price of food (adjusted for inflation) had fallen until 2006. However, over the period 2006–2008, corn and soybean prices increased rapidly because of various factors, including the rise in world incomes and the demand for renewable fuels made from agricultural feedstock. The increase in the global supply of those crops due to the adoption of GE crops and improvements in germplasm and plant breeding likely moderated the upward pressures on prices during this time.

Assessing the impact of new agricultural technologies on commodity prices is difficult because the effect on price cannot be measured directly. As Price et al. (2003) explain, once a new technology is introduced and adopted, only the world price that results from increasing global supply (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 the new technology had not been introduced (see Box 3-1). Therefore, the counterfactual world prices and demanded quantities of the commodities must be estimated from market equilibrium conditions by using econometric models, which generally are reliable in the short term and when systems are stable.

The approach to calculating the effect of genetic-engineering technology on commodity prices followed by most studies (Falck-Zepeda et al., 2000a, 2000b; Moschini et al., 2000; Price et al., 2003; Qaim and Traxler, 2005) is based on the theoretical framework developed by Moschini and Lapan (1997) to assess the impacts of an innovation on economic welfare when the innovator behaves as a monopolist under the protection of intellectual-property rights in an input market by pricing the new technology above marginal cost (the cost of producing one more unit of a good) (Price et al., 2003). Changes in the economic welfare of producers and consumers in a competitive output market can also be measured because some of the benefits generated by the innovation are passed on to them in the form of higher production efficiency and lower commodity prices.11

11

As Price et al. (2003) described it, the estimated total market benefit of adopting each of the GE crops depends on the extent to which the global commodity supply curve shifts outward after the introduction of the technology. In each case, the shift in supply reflects potential yield increases and/or decreases in 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. The empirical models calculate the preinnovation and postinnovation prices and quantities in an international market setting by using information on adoption rates, crop yields, costs, technology fees, and seed premiums. The framework also takes into account the adoption of biotechnology outside the United States. The counterfactual world price, the equilibrium world price without the innovation, is the sum of the observed market price and the vertical supply shift resulting from the adoption of GE crops. The equilibrium world price occurs at the intersection of the excess-supply and excess-demand curves.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Table 3-4 shows the estimates of the effect of GE-crop adoption (corn, soybean, and cotton) on crop prices. The price effects are different for each crop and technology and depend on the market penetration (the extent of adoption) of the new technology and on the details of the models used (particularly supply and demand parameters). For example, adoption of Bt cotton was associated with a decline in cotton prices of 0.65 percent for the first year of adoption in the United States only but with a price decline of 1.1 percent when adoption continued in the United States and took place in other countries. The effect of adoption of HR soybean varieties on soybean price ranged from a decline of 0.17 percent in 1997, when adoption had only occurred in the United States, to about a 2-percent decline following further adoption in the United States and Argentina and a 2.6-percent decline for world adoption in 2001. Simultaneous adoption of Bt corn and HR soybean could lead to a decline in corn prices of 2.5 percent and a decline in oilseed prices of 3.9 percent, all other things being equal.

Table 3-5 presents the estimated distribution of the tangible benefits among consumers, farmers, technology providers (biotechnology firms), seed firms, and consumers and producers in the United States and the rest of the world. The distribution of benefits varies by crop and technology because the economic incentives to farmers (crop prices and production costs), the payments to technology providers and seed firms, and the effect of the technology on world crop prices are different for each crop and technology. For example, farmer adoption of HR cotton benefits mainly consumers, whereas adoption of Bt cotton benefits farmers and technology providers. Innovators (technology providers and seed firms) are often the largest beneficiaries in the case of HR soybean, but producers and consumers also gain (Moschini et al., 2000). The aggregate net benefits to crop farmers depend on the aggregate cost saving relative to the estimated price decreases and increased production (sales). The lower output prices may deter some farmers who have relatively lower yield gains or higher costs from adoption. But farmers with sufficient yield gains and cost saving will adopt GE crops even when an increase in supply puts downward pressure on prices. Livestock producers primarily receive benefits from lower prices of feedstocks than would have occurred without GE-crop adoption. Analyses of the benefits of GE crops and their distribution have many nuances.

The studies mentioned above analyzed the economic effects of GE varieties during the early period of their adoption of these technologies (the latest study used data from 2001).12 Results of studies of adoption in

12

These studies were carried out before Brazil began producing large amounts of GE soybean. The entry of Brazil into the GE soybean market and the continued expansion of GE soybean in Argentina may have pushed considerable amounts of the benefits from producers to consumers.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

TABLE 3-4 Effect of Global Adoption of Genetically Engineered Crops on Commodity Prices

Technology and Crop

Adopting Areas

Commodity Name

Price Decline (%)

References

Bt cotton

United States (first year)

Cotton

0.65

Falck-Zepeda et al., 2000b

Bt cotton

United States, other producing countriesa

Cotton

1.11

Price et al., 2003

HR cotton

United States

Cotton

3.4

Price et al., 2003

HR soybean

United States

Soybean

0.17

Price et al., 2003

HR soybean

United States

Soybean

1.0

Moschini et al., 2000

HR soybean

United States, South America

Soybean

2.2

Moschini et al., 2000

HR soybean

World

Soybean

2.6

Moschini et al., 2000

HR soybean

United States, Argentina

Soybean

1.96c

Qaim and Traxler, 2005

HR soybean and canola, Bt cornb

United States, Canada, Argentina

Oilseeds

2.9

Anderson and Jackson, 2005

HR soybean and canola, Bt cornb

United States, Canada, Argentina

Corn

1.94

Anderson and Jackson, 2005

HR soybean and canola, Bt cornb

World

Oilseeds

3.08

Anderson and Jackson, 2005

HR soybean and canola, Bt cornb

World

Corn

2.09

Anderson and Jackson, 2005

Bt corn, HR soybean

United States Canada

Oilseeds

1.5

Fernandez-Cornejo et al., 2007

Bt corn, HR soybean

United States Canada

Corn

2.5

Fernandez-Cornejo et al., 2007

Bt corn, HR soybean

World

Oilseeds

3.87

Fernandez-Cornejo et al., 2007

aAssumes that countries other than the United States would have a 50-percent efficiency of technology transfer. Adoption is for 1997.

bAdoption rates assumptions vary by country and crop. See details in Anderson and Jackson (2005).

cPrice decline reported is for 2001. Qaim and Traxler (2005) also calculated price declines for other years; for example, 1.54 percent for 2000 and 1.25 percent for 1999.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

TABLE 3-5 Adoption of Genetically Engineered Crops and Their Distribution

Study

Year

Total Benefits ($million)

Share of Total Benefits (%)

U.S. Farmers

Innovators

U.S. Consumers

Net RoW

Bt cotton

 

 

 

 

 

 

Falck-Zepeda et al., 1999

1996

134

43

47

6

 

Falck-Zepeda et al., 2000a

1996

240

59

26

9

6

Falck-Zepeda et al., 2000b

1997

190

43

44

7

6

Falck-Zepeda et al., 1999

1998

213

46

43

7

4

Frisvold et al., 2000

1996–1998

131–164

5-6

46

33

18

US-EPA, 2001a

1996–1999

16–46

NA

NA

NA

NA

Price et al., 2003

1997

210

29

35

14

22

Herbicide-resistant cotton

 

 

 

 

 

 

Price et al., 2003

1997

232

4

6

57

33

Herbicide-resistant soybean

 

 

 

 

 

 

Falck-Zepeda et al., 2000b

1997-LEb

1,100

77

10

4

9

 

1997-HEc

437

29

18

17

28

Moschini et al., 2000

1999

804

20

45

10

26

Price et al., 2003

1997

310

20

68

5

6

Qaim and Traxler, 2005

1997

206

16d

49

35

NAe

Qaim and Traxler, 2005

2001

1,230

13d

34

53

NAe

NOTE: NA = not applicable; RoW = rest of the world (includes consumers and producers).

aLimited to U.S. farmers.

bLE = low elasticity; assumes a U.S. soybean supply elasticity of 0.22.

cHE = high elasticity; assumes a U.S. soybean supply elasticity of 0.92.

dInclude all soybean producers.

eIncluded in consumers and producers.

SOURCE: Fernandez-Cornejo and Caswell, 2006; Qaim and Traxler, 2005.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

agriculture (Feder et al., 1985) suggest that early adopters of new yield-increasing technologies gain early in the life of the technologies, but that their gains dissipate as prices go down. The United States was the dominant early adopter of GE varieties; James (2009) has since found a high rate of adoption of GE varieties more recently, mostly in developing countries. The agricultural products produced with genetic engineering are traded globally, and adoption of GE varieties worldwide affects prices that U.S. farmers receive.

According to James (2009), 331 million acres of land were planted to GE cultivars worldwide in 2009, of which nearly 95 percent was in six countries: the United States, Argentina, Brazil, Canada, India, and China. The total global acreage planted to GE crops in 2009 amounted to 8 percent of the world’s tillable cropland. The GE cultivars were mostly of four crops: soybean (52 percent), corn (31 percent), cotton (12 percent), and canola (5 percent). In 2009, 77 percent of the soybean area, 49 percent of the cotton, 26 percent of the corn, and 21 percent of the canola lands were grown with GE cultivars. Much of the adoption of GE corn and cotton has been in the United States, Argentina, and Brazil, but China and India are major adopters of Bt cotton. The majority of acres planted to GE crops were HR varieties, at approximately 62 percent, followed by stacked traits at 21 percent and IR varieties at 15 percent. Stacked traits grew at a 23-percent rate from 2007 to 2008, the highest rate of the three trait categories (James, 2009).

According to Sexton et al. (2009), the high increases in yield that resulted from adoption of Bt cotton in developing countries have contributed to the increase in the world cotton supply and to the relatively low prices of cotton from 1998–2008. They suggest that the decline in the price of cotton relative to the price of other agricultural commodities has contributed to the transition from cotton to other crops in California. The same shift away from cotton is taking place in other cotton-producing regions. Total upland cotton-planted acreage in the United States has declined by 36.8 percent since 2002 (USDA-NASS, 2009a, 2009b).

Soybean acreage began to increase in the United States in 1997 and stayed relatively high until 2002, in part because the commodity support prices in the Federal Agricultural Improvement and Reform Act of 1996 favored soybean over other program crops. Even though Sexton et al. (2009) found that average yield of soybean—the crop with the highest rate of adoption of GE cultivars—grew more slowly than that of cotton after the introduction of GE varieties, the introduction of GE soybean contributed to the expansion of harvested soybean area worldwide, which grew by nearly 30 percent from 1997 to 2007 (FAO, 2008). In Argentina alone, GE soybean enabled adoption of no-till practices, which facilitated double cropping of wheat and soybean and contributed to a 9.9-million-

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

acre increase in the soybean area from 1996 to 2003 (Trigo and Cap, 2003). The adoption of GE soybean in South America contributed to the increase in soybean supply, which also occurred because of the expansion of soy-bean acreage in Brazil. That supply shift caused downward pressure in soybean prices and had an adverse effect on growers in the United States, although the price effect was overwhelmed by the effect of increased global demand for soybean during the period 2006–2008.

Many of the analyses summarized in Tables 3-4 and 3-5 are based on partial-equilibrium models (in which the price of one good is examined and all other prices are held constant), but several studies have examined the effect of adoption of GE cultivars on producers and consumers by using a computable general-equilibrium approach (the prices of good are examined in relationship to one another). Some of the studies also attempted to assess the costs of access barriers imposed on GE crops by the European Union (EU), which has had a moratorium on the production and import of GE crops since 1999. Qaim (2009) has surveyed those studies and found that they predict an annual global welfare gain to consumers and producers from adoption of GE cultivars without restrictions, ranging from $1.4 billion from the adoption of Bt cotton to $10 billion from the adoption of GE oilseeds and corn. The results of the studies suggest that bans on imports of GE crops reduce the potential economic welfare of several parties, including U.S. farmers, but that European consumers suffer much of the loss.

Anderson and Jackson (2003) estimated that even under free trade—with global welfare gain from the introduction of GE cultivars of cotton, corn, and oilseeds that will enhance supply—farmers in the exporting countries will actually lose 0.07 percent of their income because of lower prices, whereas low-income consumers in North America will stand to gain from the introduction of GE cultivars because of lower food prices, all other things being equal. A moratorium on the export of GE crops to the EU will quadruple the losses to U.S. farmers. Such asynchronous conditions, when GE crops are approved at different times or not at all by different countries, could influence farmers’ planting decisions because of those losses. Yet at the same time that U.S. farmers suffer economically, U.S. consumers benefit. A more severe moratorium on GE exports by the EU and other developed economies, such as that of Japan, is estimated to reduce the income of North American farmers by 0.5 percent. Those bans will hurt European consumers but benefit European farmers. Nielsen and Anderson (2001) showed that the welfare costs of less drastic barriers, such as labeling and segregation requirements, are important but smaller than the cost of bans.

Lence and collaborators (Lence and Hayes, 2005a, 2005b, 2006; Lence et al., 2005) showed that, in addition to the cost saving and other benefits,

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

the overall welfare impact of genetic-engineering technology depends on the level of consumer concern with the technology and the costs of identity preservation. In particular, they state that their results suggest “the United States may have maximized welfare by not requiring labeling” of GE corn and soybean, but they claim that their results also suggest that “recently approved EU legislation enforcing labeling of GE crops also makes sense because consumer concern in the EU appears to be greater than that in the United States.”13

The literature suggests that adoption of GE cultivars puts downward pressure on crop prices and increases the earnings of adopting farmers in the early years of the adoption process and that barriers to access reduce grower income. But there is a paucity of studies of the welfare effects of genetic-engineering technology in recent years, when adoption has increased globally, and this is an important subject for future research.

ECONOMIC IMPACTS ON OTHER PRODUCERS

Livestock Producers

Much of the soybean and corn produced in the United States is fed to livestock (Figures 3-6 and 3-7), and byproducts are used in consumer products, so quality and nutritional characteristics of soybean and corn associated with GE crops have been closely examined. Most studies of soybean have reported no differences in animal performance (Hammond et al., 1996); in important nutritional qualities, such as isoflavones (Duke et al., 2003); or in other characteristics at the macroscopic level of HR soy-bean (Magaña-Gómez and Calderón de la Barca, 2009). Researchers (Cox and Cherney, 2001; Jung and Sheaffer, 2004) have reported that glypho-sate-resistant Bt corn does not affect feeding-quality characteristics of corn silage. Lutz et al. (2006) reported that the Bt protein Cry1Ab is degraded during the ensiling process. In feeding studies, there was no difference in milk production or milk composition between glyphosate-resistant corn, with or without the stacked Bt gene, and nontransgenic hybrids (Barrière et al., 2001; Phipps et al., 2005; Calsamiglia et al., 2007). There were no differences in body weight and feed use between rats fed grain from a Bt corn rootworm hybrid and rats fed grain from a nontransgenic hybrid (He et al., 2008). Likewise, no differences were observed in mortality, weight gain, feed efficiency, or carcass yield between broiler chickens fed grain from a Bt corn rootworm hybrid and chickens fed grain from a near-isoline (McNaughton et al., 2007). Thus, empirical studies have clearly

13

The welfare implications of different regimes of protection of intellectual-property rights in the seed industry have also been studied (Lence et al., 2005).

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×
FIGURE 3-6 U.S. corn use.

FIGURE 3-6 U.S. corn use.

NOTE: FSI = food, seed, and industrial.

SOURCE: USDA-ERS, 2009.

FIGURE 3-7 U.S. soybean use.

FIGURE 3-7 U.S. soybean use.

NOTE: Crush is used primarily for livestock feed.

SOURCE: USDA-ERS, 2009.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

indicated that there is no adverse effect on quality of livestock feed or on the output or quality of livestock products.

Furthermore, nutritional characteristics of GE and conventional corn hybrids—including fatty acid profiles, mineral and vitamin contents, lutein, and total phenol and antioxidant activity—were comparable (Venneria et al., 2008) although some slight differences in triglycerides and urinary phosphorus and sodium extractions were noted in male rats (Magaña-Gómez and Calderón de la Barca, 2009). Cotton seed is used as a byproduct in animal feed, and cottonseed oil is used for human consumption. Castillo et al. (2004) found that Bt cotton seeds were deemed nutritionally equivalent with no difference in feed intake, milk yield, or composition. Few studies have been conducted to assess the levels of the glyphosate metabolite aminomethylphosphonic acid (AMPA) in glyphosate-treated, glyphosate-resistant corn hybrids; however, one study by Reddy et al. (2008) reported no detection of AMPA. Duke et al. (2003) reported that AMPA was detected in glyphosate-treated, glyphosate-resistant soybean seeds; however, EPA has not established a tolerance for AMPA. Given that AMPA is not considered significantly toxic (Giesy et al., 2000), the discovery of AMPA in glyphosate-treated, glyphosate-resistant soybean is not considered to be an issue of importance at this time.

Feed costs constitute nearly half the variable costs of livestock production, so even moderate price fluctuations can seriously affect the trajectory of the livestock market (USDA-NASS, 2008). As mentioned above, livestock operators are the buyers of feed, and they are the major beneficiaries of reductions in the prices of corn and soybean, to which the adoption of GE crops has contributed. They also benefit from increased feed safety from the reduction of mycotoxins (Wu, 2006). We are not aware of any quantitative estimation of savings to livestock operators and final consumers due to the adoption of GE crops or of the resulting effect on the profitability of livestock operations. This is another subject on which future research is desirable.

Producers of Non-Genetically Engineered Crops

The adoption of GE crops affects production costs for non-GE farmers in several key ways. GE crops alter the demand for inputs, and this affects the cost of inputs to GE and non-GE crops alike.14 For example, Bt crop varieties that reduce insecticide use also lower the input costs for

14

As stated above, the introduction of GE crops will probably reduce pest damage and, in some cases, will reduce the commodity prices of corn, soybean, and cotton. In the damage-control framework, the demand for inputs other than the ones controlling pests (such as water and energy) is represented by (Lichtenberg and Zilberman, 1986)

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

producers who use insecticides that substitute for Bt because the lower overall demand for them puts downward pressure on their prices. In other cases, GE crops increase the demand for other inputs. HR varieties increase demand for broad-spectrum herbicides, like glyphosate, which can have mixed effects on the price. On the one hand, the increase in demand puts upward pressure on the prices of those herbicides and, everything else being equal, increases the profits of the firms that manufacture GE seeds. On the other hand, the expanded market for broad-spectrum herbicides compatible with HR crops may allow firms to reduce the price of the herbicide but still increase profits through greater sales. HR varieties also affect the demand and prices for the herbicides that were used before HR crop varieties became available, usually by lowering prices because of reduced demand.

We have observed in Chapter 2 that GE crops can affect production of non-GE crops favorably or unfavorably through externalities associated with pest-control activities. To the extent that genetic-engineering technology successfully reduces pest pressure on a field, farmers of adjacent or nearby fields planted with non-GE crops may benefit from reductions in costs for pest control associated with reductions in regional pest populations (Sexton et al., 2007). Such favorable externalities may exist for Bt crops, which control pests that target GE and non-GE crops equally (Ando and Khanna, 2000). HR crops may provide some benefits to non-GE crops on adjacent fields by reducing rates of pollination of weeds, but more certain benefits will accrue to crops planted in rotation with GE crops. Specifically, because HR crops permit the postemergent use of broad-spectrum herbicides, such as glyphosate, weed species that affect GE and non-GE crops may be controlled more effectively. In particular, glyphosate has proved effective in controlling perennial weeds that appear late in the principal crop season, persist, and impose losses on subsequent crops (Padgette et al., 1996; Shaw and Arnold, 2002). The reduction in pest pressure from the late-season use of effective chemicals on HR crops

This equation suggests that GE cultivars will contribute to increased demand for inputs—such as fertilizer, water, and capital—if adoption of GE cultivars increases the earning per unit of potential output, which is equal to (crop price)(1 – damage), assuming no acreage constraints. Thus, when the introduction of GE cultivars does not affect crop prices but reduces pest damage, adoption of GE crops increases the demand for other input use. That increases the demands for fertilizer, water, capital, and so on, and causes upward pressure on their market prices. When the introduction of GE cultivars reduces commodity prices substantially, it may lead to reduced demand for other inputs. We are not familiar with empirical studies that have tried to estimate the impact of GE crops on the demand for or prices of other inputs, and this is a subject for future work.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

may benefit the crop planted in the following season (Baylis, 2000; Tingle and Chandler, 2004) although empirical evidence of this effect is scarce. A massive field trial of crop rotation and herbicide application practices in Britain has provided evidence that the production systems used for HR canola can improve weed control in cereal crops planted in rotation (Sweet et al., 2004).

Farmers of non-GE crops may also experience adverse externalities associated with HR-crop weed control. Growers experience an adverse effect when an economically important amount of herbicide resistance builds up. As discussed in Chapter 2, resistance to broad-spectrum herbicides is a concern associated with adoption of HR varieties because use of other chemicals drastically declines in favor of the herbicide to which the crop is resistant (Shaner, 2000). When resistance in weeds evolves, farmers have resorted to managing those weeds with additional forms of control; they have either increased their use of the herbicide to which the HR crops are resistant, used additional and possibly more expensive forms of weed control (such as cultivation), or both. Such actions not only reduce or reverse the environmental benefits of HR crops reviewed in the previous chapter but also result in higher production costs for the grower compared to using glyphosate alone. To date, costs have not risen to the level of costs incurred in the conventional systems of weed control. If they had, a substantial reduction in the use of HR crops would have occurred. Resistance-management strategies, such as the use of refuges, can be expensive for individual farmers, though such strategies can provide long-run pest control benefits in the area that will offset the sum of individual costs if implemented correctly. Although Bt crops may be prone to resistance buildup because the toxins that target pests are always present in the field, the refuge requirements for Bt crops have thus far provided adequate protection from insect resistance buildup in the United States. The tradeoff is the requirement to plant some percentage of a crop to non-Bt cultivars, which may result in net economic costs to producers growing IR crops. Those costs, if they occur, are in the form of higher pesticide costs, foregone yield, or both. A benefit is the lower cost of seed for the refuge acres. A case in point is Bt cotton with the single trait for bollworm and budworm control, for which EPA requires a 20-percent refuge that can be treated with synthetic insecticides or a 5-percent refuge that cannot be treated with insecticides in the Southeast. Farmers who choose the 20-percent refuge can incur higher insecticide costs to treat insect infestations—more passes over the field and more labor to scout for insects—but have lower overall seed costs. Those who choose the 5-percent, untreated refuge can experience substantial yield loss on the refuge acres, though the cost of seed for those acres is lower. It is important to note that before the introduction of the Bt crops substantial

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

insect resistance to other classes of insecticides, such as pyrethroids, had been observed.

SOCIOECONOMIC IMPACTS OF GENE FLOW

Inadvertent gene flow from GE to non-GE crops can also have a variety of social and economic effects. Both the Ecological Society of America and the National Research Council have recognized that some degree of gene flow between sexually compatible GE and non-GE crops occurs regularly (NRC, 2004; Snow et al., 2005). Indeed, the presence of adventitious GE traits in the intended non-GE seed supply of canola, cotton, corn, and soybean and in the seed supply of GE crops (e.g., a Bt trait in crop seed that is intended as HR only) is well documented (Beckie et al., 2003; Friesen et al., 2003; Mellon and Rissler, 2004; Heuberger et al., 2008; Heuberger and Carrière, 2009). The probability of gene flow is similar in both directions between GE and non-GE varieties of a crop (Mallory-Smith and Zapiola, 2008); however, for farmers, consumers, and food distributors, the actual and perceived consequences of gene flow from GE to non-GE crops are greater than the consequences of gene flow from non-GE to GE crops.

Gene flow between GE and non-GE crops occurs via three routes: cross-pollination between GE and non-GE plants from different fields (as discussed in “Gene Flow and Genetically Engineered Crops” in Chapter 2), co-mingling of seed before the production year (in the presence of GE traits in seed bags of non-GE crops) or during the production year (mixing of seed at planting, at harvest, or during storage), and germination of seeds left behind (i.e., volunteers) after the production year (Owen, 2005; McHughen, 2006). Generally, GE and non-GE crops can coexist. However, given that some domestic and foreign consumers are willing to pay a premium for non-GE products, there are strong market incentives as well as some sociocultural reasons for farmers, seed distributors, and food processors to minimize the adventitious presence of GE traits in non-GE crops and derived products (Lin et al., 2003; Belcher et al., 2005; Furtan et al., 2007; Devos et al., 2008).

Gene flow between HR and non-HR crops can increase production costs if gene flow promotes weediness. For example, when volunteer seeds survive and germinate to the following season, field management costs increase because the volunteers will not be eliminated by glyphosate applications. Similarly, if HR traits cross into weedy relatives, weed-control expenses will be higher for all fields on to which these weeds spread, whether the farmer grows GE crops or not (Smyth et al., 2002).

Gene flow of GE traits could jeopardize the economic value of the entire harvest of non–GE-crop farmers by rendering their output unsuit-

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

able for high-value markets (Bullock and Desquilbet, 2002). They could also have unfavorable effects on the levels of trust that exist between market participants. Two groups of farmers could be impacted by gene flow: those farming non-GE crops conventionally and organic farmers. The U.S. government does not have thresholds for what level of purity is required to characterize a product as non-GE; the thresholds are instead determined by the market. The U.S. National Organic Program excludes GE methods from the organic process (Organic Foods Production Act of 1990). Because of adventitious gene flow, the organic process does not necessarily result in a non-GE product when it goes to market; whether adventitious presence is discovered depends on if testing for GE material is conducted. Therefore, if GE traits are discovered in organic crops intended for a non-GE market, the organic or non-GE status of a crop may be forfeited depending on the potential legal or market tolerances for the presence of GE traits (Gealy et al., 2007). Other governments have set thresholds for organic and non-GE crops; for example, Japan has a 5-percent threshold for corn while the EU has zero tolerance for non-approved GE material but a 0.9-percent permissible level for GE material that has been approved by the EU (Bradford, 2006; Ronald and Fouche, 2006). Tests can be performed to assess the presence of GE traits in grain to preserve the identity of non-GE grain; whether a positive test results in rejection of a product depends on the individual policies of buyers. Additional research is needed to determine the extent to which screening is used and its relationship to variation in consumer desires for purity in the food supply. Although non-GE products can lose market value because of the adventitious presence of GE material, the price of GE products is not affected by the adventitious presence of non-GE material. Accordingly, gene flow between GE and non-GE crops imposes costs primarily on consumers and producers of GE-free crops (Smyth et al., 2002; Belcher et al., 2005; Devos et al., 2008). Such a need to protect the market value of non-GE products probably contributed to the creation of GE-free zones in some regions of the United States and in the EU (Jank et al., 2006; Furtan et al., 2007). Widespread use of GE crops in the United States may have forced some corporations that were producing GE-free products to move their operations to countries where GE crops were less prevalent (Mellon and Rissler, 2004). Nevertheless, a survey published in 2004 suggested that 92 percent of U.S. organic growers who responded to the survey had not incurred any direct costs or suffered losses attributable to the adventitious presence of GE crops (Brookes and Barfoot, 2004). However, it must be noted that there have been considerable increases in the adoption of GE crops in the United States as well as growth in U.S. organic-crop production and the market for non-GE products since this survey was conducted, that so far GE traits have been incorporated into a small number of crops

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

that have few near-relatives in U.S. agriculture, and that few studies have analyzed trends in the socioeconomic impacts of gene flow.

A zero tolerance for the presence of GE traits in non-GE crops is generally impossible to manage and is not technically or economically feasible. Pollen transfer between sexually-compatible GE and non-GE crops is difficult, if not impossible, to prevent, and segregation between GE and non-GE products may be accomplished more easily and economically when nonzero thresholds for the adventitious presence of GE material in non-GE end-user products and seed are established. The goal of the thresholds is to set acceptable limits for the presence of GE traits that have been deemed safe and approved for human consumption. Accordingly, programs aimed at establishing such thresholds are analogous to seed-certification and food-labeling programs that have been used for decades to ensure the quality of seeds for agriculture and of food for consumers. The difficulty of maintaining the coexistence of GE and non-GE crops increases as the tolerance for the adventitious presence of GE traits in non-GE products becomes lower and the adventitious presence of GE traits in non-GE products becomes easier to detect even at very low levels due to technological advances.

The situation has a drastically greater impact when GE traits not approved for human consumption contaminate non-GE products. Such contamination can have strong adverse effects on market value, on the possibility of exporting crops, on the costs of remedial actions to remove contaminated supplies, and therefore on the profit margins of food producers and distributors (Lin et al., 2003; Vermij, 2006; Vogel, 2006). It can also undermine public confidence in the food system. The effects of the identification of a variety of Bt corn marketed under the name StarLink® in human food constitute an important example. StarLink® was approved only for use in animal feed but was discovered in products destined for human consumption. The resulting concerns about food safety led to the recall of more than 300 food products, and some major U.S. export markets, such as Japan and South Korea, imposed trade restrictions (Lin et al., 2003). The technology developer ultimately discontinued sale of StarLink® seed. Similarly, the accidental release of glufosinate-resistant rice in the United States in 2006 and the contamination of sulfonylurea-resistant flax in Canadian exports in 2009 imposed heavy costs on farmers, commodity traders, and processors.

Those examples of accidental releases, or any other low-level presence of unapproved GE material in the food supply, impose considerable costs on the food system that need to be accounted for in cost-benefit analyses of GE crops (Salazar et al., 2006). They also affect farmers’ planting decisions because of the risk of lost revenues and other economic and social costs. As more exotic GE crops (e.g., pharmaceuticals) enter the commer-

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

cialization phase, possible supply disruptions will multiply with greater potential for conflict between sectors in the food and nonfood industries and substantial economic costs. Such potential market and political repercussions indicate that a very low tolerance threshold set by U.S. regulatory authorities is appropriate for the presence of unapproved GE traits in food intended for human consumption.

Certain groups of consumers prefer GE-free products, a preference that is likely to increase the demand for products made with ingredients from organically grown crops. The NOP regulations require the certified organic producers must produce and handle their organic agricultural products without the use of GE methods (National Organic Program). However, the unintentional presence of GE material in organic products will not necessarily lead certifying agents to change the status of an organic product or operation (USDA-AMS, 2000). As explained above, because some level of gene flow between GE and non-GE crops is difficult to prevent, the adventitious presence of GE material has been detected in non-GE products, including certified organic products. Therefore, the process-based NOP standard that excludes GE methods in production and handling systems does not assure that organically grown crops with non-GE methods will be free of GE material for marketing.

The presence of GE material can affect the ability of growers to sell non-GE and organic crops in domestic and foreign markets with requirements beyond the process-based standard of the NOP. Accordingly, policies have been established to manage the potential for adventitious presence while enabling coexistence of GE, GE-free, and organic production systems. However, policy-established tolerance thresholds for the adventitious presences of traits from commercialized GE crops in non-GE or organic products vary considerably among countries. For example, in the United States, voluntary labeling of food as GE-free is allowed as long as a product contains less than 5-percent adventitious presence of GE material (Demont and Devos, 2008; Organic Foods Production Act of 1990). In contrast, the EU allows up to 0.9-percent adventitious GE material in non-GE food, animal feed, and products labeled as organic if the GE crop has been approved in the EU; otherwise, the threshold is zero (Demont and Devos, 2008). Certified non-GE seed sold to farmers in the United States is typically expected to contain less than 0.5-1 percent of seeds (depending on crop type) with GE traits (Mellon and Rissler, 2004; CCIA, 2007). Thresholds for commercial seed have been considered but have not yet been implemented uniformly in the EU (Kalaitzandonakes and Magnier, 2004; Devos et al., 2008).

GE-free or organic products lose their premium market value when the adventitious presence of GE material exceeds established govern-

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

ment or market thresholds. Anecdotal stories suggest that the crops of U.S. organic growers are being screened in the marketing chain for the presence of GE material and are being rejected if levels exceed market-determined levels. We do not have evidence to judge how widespread such testing is in the United States. This issue deserves more investigation to determine the extent of such market-led behavior and the social and other factors driving it. We do know that given the threshold criteria in the EU for GE material in organic products, food produced in the United States and labeled as organic by U.S. certifiers could be rejected in the EU as not organic because of adventitious presence of GE material even though no GE seed or crops were used in production by U.S. producers. The coexistence of GE and non-GE products is possible as long as measures are taken to ensure that the adventitious presence of GE traits remains below the thresholds set in receiving markets, either by governments or buyers. In general, threshold differences among regions contribute to creating barriers to the use of GE crops and trade in non-GE products (Smyth et al., 2002; Demont and Devos, 2008; Devos et al., 2008).

Separating GE and non-GE products at every step of the production process is expensive, and costs increase as thresholds for the presence of GE traits in non-GE products decrease (Lin et al., 2003; Kalaitzandonakes and Magnier, 2004). Growers must attend to details and apply considerable effort to achieve effective segregation between GE and non-GE crops (CBI, 2007). Grain segregation in normal production settings is difficult but can be accomplished and could effectively minimize the co-mingling of GE and non-GE crops. Given that co-mingling of seeds can be costly for growers, particularly for growers who have specific contracts that restrict GE traits, tactics for isolating GE crops from non-GE crops must be established effectively (Owen, 2000). Controlling volunteer GE crops in non-GE crops may not be difficult, depending on crop rotation but requires considerable diligence on the part of growers (Owen, 2005). When volunteer crops acquire a GE trait for herbicide resistance via unintended gene flow, weed-management costs for a grower may increase and potential crop yield may decline if the crop planted the following season is also resistant to glyphosate (Owen and Zelaya, 2005). Furthermore, the isolation distances required to maintain complete segregation for open-pollinated crops are often too large to be economically feasible (Matus-Cádiz et al., 2004).

An economic assessment based on data from major seed firms in the United States indicated that reducing the adventitious presence of GE traits in non-GE corn seed from 1 percent to 0.3 percent would raise seed production costs by about 35 percent (Kalaitzandonakes and Magnier,

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

2004).15 The increased costs would involve changes in field operations and in processing and result from new expenses for extra purity testing, storage, and transportation, but most of the increase in production costs would result from measures taken at the field level to minimize gene flow. Thus, programs that set levels of tolerance for the adventitious presence of GE traits in non-GE products probably have substantial impacts on growers directly and would increase the cost of non-GE seed and the market value of GE-free and organic products (Smyth et al., 2002; Kalaitzandonakes and Magnier, 2004; Belcher et al., 2005).

Barring the risk of contamination, GE crops can contribute to the creation of market opportunities for non-GE farmers. The organic market is a primary example. By virtue of the ban on the use of GE traits in the official USDA definition of organic production, the organic movement can market itself to, and collect a price premium from, consumers who prefer not to purchase food or fiber produced with genetic-engineering technology. Consumer preference for non-GE foods may be related to other traits associated with organic production, but the stated price premium for non-GE crops is substantial in some segments of the population (Huffman et al., 2003).

CONCLUSIONS

The widespread adoption of GE crops has had agronomic and economic implications for adopters and non-GE producers in the United States. For GE farmers, the general increase in yield, reduction in some input costs, improvement in pest control, increase in personal safety, and time-management benefits have generally outweighed the additional costs of GE seed. The use of HR crops has not greatly increased yields, but it has generally improved weed control, especially on farms where substantial weed resistance to the specific herbicide to which the HR crop is resistant has not developed, and it has improved farmers’ incomes by saving time thus facilitating more off-farm work or providing more management time on the farm. IR crops have increased yields in areas where economically damaging insect-pest pressures occur and have saved on expenditures for conventional pesticide. Thus, the use of HR and IR crops has mostly increased adopters’ incomes compared with the use of non-GE varieties.

It should be noted that the economic benefits have changed over time and probably will continue to change. Yield lag and yield drag were not

15

This study is a summary assessment over various GE-crop technologies and therefore should not be applied to specific situations. It is likely that the impacts would vary considerably over different GE cultivars and their specific farming situations.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

uncommon when HR crop varieties were first introduced, but GE traits have since been incorporated into high-yielding varieties, and improved GE events have replaced the initial events. Although research has identified those changes in farmers’ experience with GE crops, there has been little investigation of the economic impact of GE crops more recently. More research would improve the information available to farmers, plant breeders, and policy makers as market, environmental, and social conditions change.

The extent to which GE crops make it economical to expand production to lands not previously cultivated or to intensify production on existing cropland with double cropping has not been reported adequately in the literature. More research on the economic effects of GE-crop adoption on non–GE-crop producers would also be beneficial. Examples include the costs and benefits of shifts in pest management for non-GE producers due to the adoption of GE crops, the value of market opportunities afforded to organic farmers by defining their products as non-GE crops, the economic impacts of GE adoption on livestock producers, and the costs to farmers, marketers, and processors of adventitious presence or contamination from approved or unapproved GE traits and crops into restricted markets.

REFERENCES

Ahmad, A., G.E. Wilde, R.J. Whitworth, and G. Zolnerowich. 2006. Effect of corn hybrids expressing the coleopteran-specific Cry3Bb1 protein for corn rootworm control on aboveground insect predators. Journal of Economic Entomology 99(4):1085–1095.

Al-Deeb, M.A., and G.E. Wilde. 2005. Effect of Bt corn expressing the Cry3Bb1 toxin on western corn rootworm (Coleoptera: Chrysomelidae) biology. Journal of the Kansas Entomological Society 78(2):142–152.

Alston, J.M., J.A. Hyde, M.C. Marra, and P.D. Mitchell. 2002. An ex ante analysis of the benefits from the adoption of corn rootworm resistant transgenic corn technology. AgBioForum 5(3):71–84.

Anderson, K., and L.A. Jackson. 2003. Why are US and EU policies toward GMOs so different? AgBioForum 6(3):95–100.

———. 2005. Global responses to GM food technology: Implications for Australia. RIRDC Publication No. 05/016. Canberra, ACT: Rural Industries Research and Development Corporation. Available online at https://rirdc.infoservices.com/au/downloads/05-016.pdf. Accessed March 31, 2010.

Ando, A.W., and M. Khanna. 2000. Environmental costs and benefits of genetically modified crops: Implications for regulatory strategies. American Behavioral Scientist (3):435–463.

Baker, C.J., K.E. Saxton, and W.R. Ritchie. 1996. No–tillage seeding: Science and practice. Oxford, UK: CABI Publishing.

Baker, C.J., K.E. Saxton, W.R. Ritchie, W.C.T. Chamen, D.C. Reicosky, F. Ribeiro, S.E. Justice, and P.R. Hobbs. 2007. No-tillage seeding in conservation agriculture. 2nd ed. Oxford, UK: CABI Publishing/UN-FAO.

Barrière, Y., R. Vérité, P. Brunschwig, F. Surault, and J.C. Emile. 2001. Feeding value of corn silage estimated with sheep and dairy cows is not altered by genetic incorporation of Bt176 resistance to Ostrinia nubilalis. Journal of Dairy Science 84(8):1863–1871.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Baute, T.S., M.K. Sears, and A.W. Schaafsma. 2002. Use of transgenic Bacillus thuringiensis Berliner corn hybrids to determine the direct economic impact of the European corn borer (Lepidoptera: Crambidae) on field corn in eastern Canada. Journal of Economic Entomology 95(1):57–64.

Baylis, A.D. 2000. Why glyphosate is a global herbicide: Strengths, weaknesses and prospects. Pest Management Science 56(4):299–308.

Beckie, H.J., S.I. Warwick, H. Nair, and G. Séguin-Swartz. 2003. Gene flow in commercial fields of herbicide-resistant canola (Brassica napus). Ecological Applications 13(5):1276–1294.

Belcher, K., J. Nolan, and P.W.B. Phillips. 2005. Genetically modified crops and agricultural landscapes: Spatial patterns of contamination. Ecological Economics 53(3):387–401.

Benbrook, C. 2004. The impact of genetically engineered crops on pesticide use: The first nine years. October. Technical Paper No. 7. Ag BioTech InfoNet. Sandpoint, ID. Available online at http://www.organic-center.org/reportfiles/Full_first_nine.pdf. Accessed April 8, 2009.

Bernard, J.C., J.D. Pesek, Jr., and C. Fan. 2004. Performance results and characteristics of adopters of genetically engineered soybeans in Delaware. Agricultural and Resource Economics Review 33(2):282–292.

Bertram, M.G., and P. Pedersen. 2004. Adjusting management practices using glyphosate-resistant soybean cultivars. Agronomy Journal 96(2):462–468.

Boyle, K.P. 2006. The economics of on-site conservation tillage. West National Technology Support Center technical note. September. Econ 101.01. U.S. Department of Agriculture–Natural Resources Conservation Service. Portland, OR. Available online at ftp://ftp-fc.sc.egov.usda.gov/Economics/Technotes/ConservationTill_01.doc. Accessed August 2, 2009.

Bradford, K.J. 2006. Methods to maintain genetic purity of seed stocks. Agricultural biotechnology in California. University of California–Division of Agriculture and Natural Resources. Publication 8189. Available online at http://ucbiotech.org/resources/factsheets/8189.pdf. Accessed March 31, 2010.

Bradley, K.W., and L.E. Sweets. 2008. Influence of glyphosate and fungicide coapplications on weed control, spray penetration, soybean response, and yield in glyphosate-resistant soybean. Agronomy Journal 100(5):1360–1365.

Bradley, K.W., N.H. Monnig, T.R. Legleiter, and J.D. Wait. 2007. Influence of glyphosate tank-mix combinations and application timings on weed control and yield in glyphosate-resistant soybean. Crop Management. Available online at http://www.plantmanagementnetwork.org/pub/cm/research/2007/tank/. Accessed April 7, 2009.

Brookes, G., and P. Barfoot. 2004. Co-existence in North American agriculture: Can GM crops be grown with conventional and organic crops? PG Economics Ltd. Dorchester, UK. Available online at http://www.pgeconomics.co.uk/pdf/CoexistencereportNAmericafinalJune2004.pdf. Accessed May 15, 2009.

Bullock, D.S., and M. Desquilbet. 2002. The economics of non-GMO segregation and identity preservation. Food Policy 27(1):81–99.

Bullock, D.S., and E.I. Nitsi. 2001. Roundup Ready soybean technology and farm production costs: Measuring the incentive to adopt genetically modified seeds. American Behavioral Scientist (8):1283–1301.

Calsamiglia, S., B. Hernandez, G.F. Hartnell, and R. Phipps. 2007. Effects of corn silage derived from a genetically modified variety containing two transgenes on feed intake, milk production, and composition, and the absence of detectable transgenic deoxyribonucleic acid in milk in Holstein dairy cows. Journal of Dairy Science 90(10):4718– 4723.

Carpenter, J., L.L. Wolfenbarger, and P.R. Phifer. 2001. GM crops and patterns of pesticide use. Science 292(5517):637b–638.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Carpenter, J., A. Felsot, T. Goode, M. Hammig, D. Onstad, and S. Sankula. 2002. Comparative environmental impacts of biotechnology-derived and traditional soybean, corn, and cotton crops. Ames, IA: Council for Agricultural Science and Technology. Available online a http://www.soyconnection.com/soybean_oil/pdf/EnvironmentalImpactStudy-English.pdf. Accessed March 31, 2010.

Carrière, Y., C. Ellers-Kirk, M.S. Sisterson, L. Antilla, M. Whitlow, T.J. Dennehy, and B.E. Tabashnik. 2003. Long-term regional suppression of pink bollworm by Bacillus thuringiensis cotton. Proceedings of the National Academy of Sciences of the United States of America 100(4):1519–1523.

Carrière, Y., M.S. Sisterson, and B.E. Tabashnik. 2004. Resistance management for sustainable use of Bacillus thuringiensis crops in integrated pest management. In Insect pest management: Field and protected crops. eds. A.R. Horowitz and I. Ishaaya, pp. 65–95. Berlin: Springer.

Castillo, A.R., M.R. Gallardo, M. Maciel, J.M. Giordano, G.A. Conti, M.C. Gaggiotti, O. Quaino, C. Gianni, and G.F. Hartnell. 2004. Effects of feeding rations with genetically modified whole cottonseed to lactating Holstein cows. Journal of Dairy Science 87(6):1778–1785.

Catangui, M.A., and R.K. Berg. 2002. Comparison of Bacillus thuringiensis corn hybrids and insecticide-treated isolines exposed to bivoltine European corn borer (Lepidoptera: Crambidae) in South Dakota. Journal of Economic Entomology 95(1):155–166.

Cattaneo, M.G., C.M. Yafuso, C. Schmidt, C.-Y. Huang, M. Rahman, C. Olson, C. Ellers-Kirk, B.J. Orr, S.E. Marsh, L. Antilla, P. Dutilleul, and Y. Carrière. 2006. Farm-scale evaluation of the impacts of transgenic cotton on biodiversity, pesticide use, and yield. Proceedings of the National Academy of Sciences of the United States of America 103(20):7571–7576.

CBI (Council for Biotechnology Information). 2007. Can biotech and organic crops coexist? Washington, DC: Council for Biotechnology Information.

CCIA (California Crop Improvement Association). 2007. Certification standards. Davis: Parsons Seed Certification Center/California Crop Improvement Association. Available online at http://ccia.ucdavis.edu/. Accessed June 26, 2009.

Chase, C.A., and M.D. Duffy. 1991. An economic analysis of the Nashua tillage study: 1978–1987. Journal of Production Agriculture 4(1):91–98.

Clements, M.J., K.W. Campbell, C.M. Maragos, C. Pilcher, J.M. Headrick, J.K. Pataky, and D.G. White. 2003. Influence of Cry1Ab protein and hybrid genotype on fumonisin contamination and Fusarium ear rot of corn. Crop Science 43(4):1283–1293.

Corrigan, K.A., and R.G. Harvey. 2000. Glyphosate with and without residual herbicides in no-till glyphosate-resistant soybean (Glycine max). Weed Technology 14(3):569–577.

Couvillion, W.C., F. Kari, D. Hudson, and A. Allen. 2000. A preliminary economic assessment of Roundup Ready soybeans in Mississippi. May Research Report 2000–005. Mississippi State University. Starkville, MS. Available online at http://ageconsearch.umn.edu/bitstream/15783/1/rr00-005.pdf. Accessed April 28, 2009.

Cox, W.J., and D.J.R. Cherney. 2001. Influence of brown midrib, leafy, and transgenic hybrids on corn forage production. Agronomy Journal 93(4):790–796.

Cox, W.J., R.R. Hahn, P.J. Stachowski, and J.H. Cherney. 2005. Weed interference and glyphosate timing affect corn forage yield and quality. Agronomy Journal 97(3):847–853.

Cox, W.J., R.R. Hahn, and P.J. Stachowski. 2006. Time of weed removal with glyphosate affects corn growth and yield components. Agronomy Journal 98(2):349–353.

Cox, W.J., J.H. Cherney, and E. Shields. 2007a. Clothianidin seed treatments inconsistently affect corn forage yield when following soybean. Agronomy Journal 99(2):543–548.

Cox, W.J., E. Shields, and J.H. Cherney. 2007b. The effect of clothianidin seed treatments on corn growth following soybean. Crop Science 47(6):2482–2485.

Cox, W.J., E. Shields, D.J.R. Cherney, and J.H. Cherney. 2007c. Seed-applied insecticides inconsistently affect corn forage in continuous corn. Agronomy Journal 99(6):1640–1644.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Cox, W.J., J. Hanchar, and E. Shields. 2009. Stacked corn hybrids show inconsistent yield and economic responses in New York. Agronomy Journal 101(6):1530–1537.

Culpepper, A.S., and A.C. York. 1999. Weed management and net returns with transgenic, herbicide-resistant, and nontransgenic cotton (Gossypium hirsutum). Weed Technology 13(2):411–420.

Dalley, C.D., J.J. Kells, and K.A. Renner. 2004. Effect of glyphosate application timing and row spacing on weed growth in corn (Zea mays) and soybean (Glycine max). Weed Technology 18(1):177–182.

Demont, M., and Y. Devos. 2008. Regulating coexistence of GM and non-GM crops without jeopardizing economic incentives. Trends in Biotechnology 26(7):353–358.

Devos, Y., M. Demont, and O. Sanvido. 2008. Coexistence in the EU—return of the moratorium on GM crops? Nature Biotechnology 26(11):1223–1225.

Dillehay, B.L., G.W. Roth, D.D. Calvin, R.J. Kratochvil, G.A. Kuldau, and J.A. Hyde. 2004. Performance of Bt corn hybrids, their near isolines, and leading corn hybrids in Pennsylvania and Maryland. Agronomy Journal 96(3):818–824.

Downs, H.W., and R.W. Hansen. 1998. Estimating farming fuel requirements. Farm & ranch series. No. 5.006. Colorado State University Extension Service. Fort Collins, CO. Available online at http://www.cde.state.co.us/artemis/ucsu20/ucsu2062250061998internet.pdf. Accessed May 4, 2009.

Duffy, M. 2001. Who benefits from biotechnology? Paper presented at the American Seed Trade Association Annual Meeting (Chicago, IL, December 5–7, 2001). American Seed Trade Association. Available online at http://www.econ.iastate.edu/faculty/duffy/Pages/biotechpaper.pdf. Accessed February 21, 2009.

Duke, S.O., A.M. Rimando, P.F. Pace, K.N. Reddy, and R.J. Smeda. 2003. Isoflavone, glyphosate, and aminomethylphosphonic acid levels in seeds of glyphosate-treated, glyphosate-resistant soybean. Journal of Agricultural and Food Chemistry 51(1):340–344.

Ellsworth, P.C., A. Fournier, and T.D. Smith. 2009. Arizona cotton insect losses. Publ. No. AZ1183. University of Arizona–College of Agriculture and Life Sciences. Tucson, AZ. Available online at http://cals.arizona.edu/crops/cotton/insects/cil/cil.html. Accessed April 20, 2009.

Elmore, R.W., F.W. Roeth, R.N. Klein, S.Z. Knezevic, A. Martin, L.A. Nelson, and C.A. Shapiro. 2001a. Glyphosate-resistant soybean cultivar response to glyphosate. Agronomy Journal 93(2):404–407.

Elmore, R.W., F.W. Roeth, L.A. Nelson, C.A. Shapiro, R.N. Klein, S.Z. Knezevic, and A. Martin. 2001b. Glyphosate-resistant soybean cultivar yields compared with sister lines. Agronomy Journal 93(2):408–412.

Falck-Zepeda, J.B., G. Traxler, and R.G. Nelson. 1999. Rent creation and distribution from the first three years of planting Bt cotton. ISAAA Briefs No. 14. The International Service for the Acquisition of Agri-biotech Applications. Ithaca, NY.

———. 2000a. Surplus distribution from the introduction of a biotechnology innovation. American Journal of Agricultural Economics 82(2):360–369.

———. 2000b. Rent creation and distribution from biotechnology innovations: The case of Bt cotton and herbicide-tolerant soybeans in 1997. Agribusiness 16(1):21–32.

FAO (Food and Agriculture Organization). 2008. FAOStat: ResourceSTAT. Available online at http://faostat.fao.org. Accessed June 16, 2009.

Feder, G., R.E. Just, and D. Zilberman. 1985. Adoption of agricultural innovations in developing countries: A survey. Economic Development and Cultural Change 33(2):255–298.

Fernandez-Cornejo, J. 2004. The seed industry in U.S. agriculture: An exploration of data and information on crop seed markets, regulation, industry structure, and research and development. Agriculture Information Bulletin No. 786. U.S. Department of Agriculture–Economic Research Service. Washington, DC. Available online at http://www.ers.usda.gov/publications/aib786/aib786.pdf. Accessed May 26, 2009.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Fernandez-Cornejo, J., and M.F. Caswell. 2006. The first decade of genetically engineered crops in the United States. Economic Information Bulletin No. 11. April. U.S. Department of Agriculture–Economic Research Service. Washington, D.C. Available online at http://www.ers.usda.gov/publications/eib11/eib11.pdf. Accessed June 15, 2009.

Fernandez-Cornejo, J., and A. Gregory. 2004. Managerial intensity and the adoption of conservation tillage. Paper presented at the Northeastern Agricultural and Resource Economics Association Annual Meeting (Halifax, Nova Scotia, June 20–23, 2004).

Fernandez-Cornejo, J., and C. Hendricks. 2003. Off-farm work and the economic impact of adopting herbicide-tolerant crops. Paper presented at the American Agricultural Economics Association Annual Meeting (Montreal, Canada, July 27–30, 2003). Available online at http://ageconsearch.umn.edu/bitstream/22130/1/sp03fe01/pdf. Accessed June 28, 2009.

Fernandez-Cornejo, J., and J. Li. 2005. The impacts of adopting genetically engineered crops in the USA: The case of Bt corn. Paper presented at the American Agricultural Economics Association Annual Meeting (Providence, RI, July 24–27, 2005). Available online at http://ageconsearch.umn.edu/bitstream/19318/1/sp05fe01.pdf. Accessed February 19, 2009.

Fernandez-Cornejo, J., and W.D. McBride. 2002. Adoption of bioengineered crops. Agricultural Economic Report No. 810. May 1. U.S. Department of Agriculture–Economic Research Service. Washington, DC. Available online at http://www.ers.usda.gov/publications/aer810/aer810.pdf. Accessed July 25, 2009.

Fernandez-Cornejo, J., and A.K. Mishra. 2007. Off-farm income, production decisions, and farm economic performance. ERR#36. U.S. Department of Agriculture–Economic Research Service. Washington, DC. Available online at http://www.ers.usda.gov/publications/err36/err36_reportsummary.pdf. Accessed June 29, 2009.

Fernandez-Cornejo, J., C. Klotz-Ingram, and S. Jans. 2002a. Farm-level effects of adopting herbicide-tolerant soybeans in the U.S.A. Journal of Agricultural & Applied Economics 34(1):149–163.

Fernandez-Cornejo, J., C. Alexander, and R.E. Goodhue. 2002b. Dynamic diffusion with disadoption: The case of crop biotechnology in the USA. Agricultural and Resource Economics Review 31(1):112–126.

Fernandez-Cornejo, J., C. Hendricks, and A.K. Mishra. 2005. Technology adoption and off-farm household income: The case of herbicide-tolerant soybeans. Journal of Agricultural & Applied Economics 37(3):549–563.

Fernandez-Cornejo, J., R. Lubowski, and A. Somwaru. 2007. Global adoption of agricultural biotechnology: Modeling and preliminary results. Paper presented at the 10th Annual Conference on Global Economic Analysis (West Lafayette, IN, June 7–9, 2007).

Fernandez-Cornejo, J., R. Nehring, E.N. Sinha, A. Grube, and A. Vialou. 2009. Assessing recent trends in pesticide use in U.S. agriculture. Paper presented at the 2009 Annual Meeting of the Agricultural and Applied Economics Association (Milwaukee, WI, July 26–28, 2009). Available online at http://agecomsearch.umn.edu/handle/49271. Accessed June 16, 2009.

Ferraro, P.J. 2009. Counterfactual thinking and impact evaluation in environmental policy. New Directions for Evaluation 2009(122):75–84.

Friesen, L.F., A.G. Nelson, and R.C. Van Acker. 2003. Evidence of contamination of pedigreed canola (Brassica Napus) seedlots in Western Canada with genetically engineered herbicide resistance traits. Agronomy Journal 95(5):1342–1347.

Frisvold, G., and M. Marra. 2004. The difficulty with data: How sampling and aggregation can affect measures of pesticide use in biotech crops. Paper presented at the 8th Annual International Consortium on Agricultural Biotechnology Research Conference (Ravello, Italy, July 8–11, 2004).

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Frisvold, G.B., R. Tronstad, and J. Mortensen. 2000. Adoption of Bt cotton: Regional differences in producer costs and returns. In 2000 Proceedings Beltwide Cotton Conferences, pp. 337–340 (San Antonio, TX, January 4–8, 2000). eds. P. Dugger and D. Richter. National Cotton Council of America.

Furtan, W.H., A. Güzel, and A.S. Weseen. 2007. Landscape clubs: Co-existence of genetically modified and organic crops. Canadian Journal of Agricultural Economics 55(2):185–195.

Gardner, J.G., and C.H. Nelson. 2007. Genetically modified crops and labor savings in US crop production. Paper presented at the 2007 Southern Agricultural Economics Association Annual Meeting (Mobile, AL, February 4–7, 2007).

Gealy, D.R., K.J. Bradford, L. Hall, R. Hellmich, A. Raybould, J. Wolt, and D. Zilberman. 2007. Implications of gene flow in the scale-up and commercial use of biotechnology-derived crops: Economic and policy considerations. Council for Agricultural Science and Technology, December (Issue 37). Available online at http://www.cast-science.org/websiteUploads/publicationPDFs/CAST%20Issue%20Paper%2037%20galley-final-2149.pdf. Accessed October 21, 2007.

Gianessi, L.P., and J.E. Carpenter. 1999. Agricultural biotechnology: Insect control benefits. National Center for Food and Agricultural Policy. Washington, DC. Available online at http://www.ncfap.org/documents/insectcontrolbenefits.pdf. Accessed May 20, 2009.

Giesy, J.P., S. Dobson, and K.R. Solomon. 2000. Ecotoxicological risk assessment for Roundup® herbicide. Reviews of Environmental Contamination and Toxicology 167:35–120.

Gower, S.A., M.M. Loux, J. Cardina, and S.K. Harrison. 2002. Effect of planting date, residual herbicide, and postemergence application timing on weed control and grain yield in glyphosate-tolerant corn (Zea mays). Weed Technology 16(3):488–494.

Gray, M.E., K.L. Steffey, R.E. Estes, and J.B. Schroeder. 2007. Responses of transgenic maize hybrids to variant western corn rootworm larval injury. Journal of Applied Entomology 131(6):386–390.

Griliches, Z. 1957. Hybrid corn: An exploration in the economics of technological change. Econometrica 25(4):501–522.

Hammond, B.G., J.L. Vicini, G.F. Hartnell, M.W. Naylor, C.D. Knight, E.H. Robinson, R.L. Fuchs, and S.R. Padgette. 1996. The feeding value of soybeans fed to rats, chickens, catfish and dairy cattle is not altered by genetic incorporation of glyphosate tolerance. Journal of Nutrition 126(3):717–727.

Harman, W.L., D.C. Hardin, A.F. Wiese, P.W. Unger, and J.T. Musick. 1985. No-till technology: Impacts on farm income, energy use and groundwater depletion in the plains. Western Journal of Agricultural Economics 10(1):134–146.

Harrington, J. 2006. University research finds Herculex RW twice as effective as YieldGard RW Against Corn Rootworm. Crop Management. Available online at http://www.plant-managementnetwork.org/pub/cm/news/2006/YieldGard/. Accessed April 7, 2009.

He, X.Y., K.L. Huang, X. Li, W. Qin, B. Delaney, and Y.B. Luo. 2008. Comparison of grain from corn rootworm resistant transgenic DAS-59122-7 maize with non-transgenic maize grain in a 90-day feeding study in Sprague-Dawley rats. Food and Chemical Toxicology 46(6):1994–2002.

Heimlich, R.E., J. Fernandez-Cornejo, W. McBride, C. Klotz-Ingram, S. Jans, and N. Brooks. 2000. Genetically engineered crops: Has adoption reduced pesticide use? Agricultural Outlook 273:13–17.

Heuberger, S., and Y. Carrière. 2009. Pollen-mediated transgene flow in agricultural seed production. Paper presented at the 94th Ecological Society of America annual meeting (Albuquerque, NM, August 2–7, 2009).

Heuberger, S., C. Yafuso, G. Degrandi-Hoffman, B.E. Tabashnik, Y. Carrière, and T.J. Dennehy. 2008. Outcrossed cottonseed and adventitious Bt plants in Arizona refuges. Environmental Biosafety Research 7(2):87–96.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Hubbell, B.J., M.C. Marra, and G.A. Carlson. 2000. Estimating the demand for a new technology: Bt cotton and insecticide policies. American Journal of Agricultural Economics 82(1):118–132.

Huffman, W.E., J.F. Shogren, M. Rousu, and A. Tegene. 2003. Consumer willingness to pay for genetically modified food labels in a market with diverse information: Evidence from experimental auctions. Journal of Agricultural and Resource Economics 28(3):481–502.

Huso, S.R., and W.W. Wilson. 2006. Producer surplus distributions in GM crops: The ignored impacts of Roundup Ready® wheat. Journal of Agricultural and Resource Economics 31(2):339–354.

Jackson, R.E., J.R. Bradley Jr., and J.W. Van Duyn. 2003. Field performance of transgenic cottons expressing one or two Bacillus thuringiensis endotoxins against bollworm, Helicoverpa zea (Boddie). Journal of Cotton Science 7(3):57–64.

James, C. 2009. Global status of commercialized biotech/GM crops: 2009. ISAAA Brief No. 41 ed. The International Service for the Acquisition of Agri-biotech Applications. Ithaca, NY. Jank, B., J. Rath, and H. Gaugitsch. 2006. Co-existence of agricultural production systems. Trends in Biotechnology 24(5):198–200.

Jasa, P.J. 2000. Conservation tillage systems. Paper presented at the International Symposium on Conservation Tillage (Mazatlan, Mexico, January 24–27, 2000). Available online at http://agecon.okstate.edu/isct/labranza/jasa/tillagesys.doc. Accessed August 9, 2009.

Johnson, W.G., P.R. Bradley, S.E. Hart, M.L. Buesinger, and R.E. Massey. 2000. Efficacy and economics of weed management in glyphosate-resistant corn (Zea mays). Weed Technology 14(1):57–65.

Jung, H.G., and C.C. Sheaffer. 2004. Influence of Bt transgenes on cell wall lignification and digestibility of maize stover for silage. Crop Science 44(5):1781–1789.

Just, R.E., and D.L. Hueth. 1993. Multimarket exploitation: The case of biotechnology and chemicals. American Journal Agricultural Economics 75:936–945.

Kalaitzandonakes, N., and A. Magnier. 2004. Biotech labeling standards and compliance costs in seed production. Choices: The magazine of food, farm and resource issues 2nd Quarter:1–6. Available at http://www.choicesmagazine.org/2004-1/2004-2-01.pdf. Accessed March 31, 2010.

Kneževič, S.Z., S.P. Evans, and M. Mainz. 2003a. Row spacing influences the critical timing for weed removal in soybean (Glycine max). Weed Technology 17(4):666–673.

———. 2003b. Yield penalty due to delayed weed control in corn and soybean. Crop Management. Available online at http://www.plantmanagementnetwork.org/pub/cm/research/2003/delay/. Accessed April 8, 2009.

Krull, C.F., J.M. Prescott, and C.W. Crum. 1998. Seed marketing and distribution. In Maize seed industries in developing countries. ed. M.L. Morris, pp. 125–141. Boulder, CO: Lynne Rienner Publishers/CIMMYT.

Lauer, J. 2006. Performance of transgenic corn and soybean. Paper presented at the 2006 Annual ASA-CSSA-SSSA Meeting (Indianapolis, IN, November 12–16, 2006).

Lauer, J., and J. Wedberg. 1999. Grain yield of initial Bt corn hybrid introductions to farmers in the northern Corn Belt. Journal of Production Agriculture 12(3):373–376.

Lence, S.H., and D.J. Hayes. 2005a. Technology fees versus GURTs in the presence of spillovers: World welfare impacts. AgBioForum 8(2&3):172–186.

———. 2005b. Genetically modified crops: Their market and welfare impacts. American Journal of Agricultural Economics 87(4):931–950.

Lence, S.H., D.J. Hayes, A. McCunn, S. Smith, and W.S. Niebur. 2005. Welfare impacts of intellectual property protection in the seed industry. American Journal of Agricultural Economics 87(4):951–968.

Lence, S.H., and D.J. Hayes. 2006. EU and US regulations for handling and transporting genetically modified grains: Are both positions correct? EuroChoices 5(2):20–27.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Lichtenberg, E., and D. Zilberman. 1986. The econometrics of damage control—why specification matters. American Journal of Agricultural Economics 68(2):261–273.

Lin, W., G.K. Price, and E.W. Allen. 2003. StarLink: Impacts on the U.S. corn market and world trade. Agribusiness 19(4):473–488.

Lutz, B., S. Wiedemann, and C. Albrecht. 2006. Degradation of transgenic Cry1Ab DNA and protein in Bt-176 maize during the ensiling process. Journal of Animal Physiology and Animal Nutrition 90(3–4):116–123.

Ma, B.L., and K.D. Subedi. 2005. Development, yield, grain moisture and nitrogen uptake of Bt corn hybrids and their conventional near-isolines. Field Crops Research 93(2–3):199–211.

Ma, B.L., F. Meloche, and L. Wei. 2009. Agronomic assessment of Bt trait and seed or soil-applied insecticides on the control of corn rootworm and yield. Field Crops Research 111(3):189–196.

Ma, B.L., K. Subedi, L. Evenson, and G. Stewart. 2005. Evaluation of detection methods for genetically modified traits in genotypes resistant to European corn borer and herbicides. Journal of Environmental Science and Health - Part B Pesticides, Food Contaminants, and Agricultural Wastes 40(4):633–644.

Magaña-Gómez, J.A., and A.M. Calderón de la Barca. 2009. Risk assessment of genetically modified crops for nutrition and health. Nutrition Reviews 67(1):1–16.

Mallory-Smith, C., and M. Zapiola. 2008. Gene flow from glyphosate-resistant crops. Pest Management Science 64(4):428–440.

Marra, M.C. 2001. Agricultural biotechnology: A critical review of the impact evidence to date. In The future of food: Biotechnology markets and policies in an international setting. ed. P.G. Pardey, pp. 155–184. Washington, DC: International Food Policy Research Institute.

Marra, M.C., and N.E. Piggott. 2006. The value of non-pecuniary characteristics of crop biotechnologies: A new look at the evidence. In Regulating agricultural biotechnology: Economics and policy. eds. R.E. Just, J.M. Alston, and D. Zilberman, pp. 145–178. New York: Springer.

Marra, M.C., P.G. Pardey, and J.M. Alston. 2002. The payoffs to transgenic field crops: An assessment of the evidence. AgBioForum 5(2):43–50.

Marra, M.C., N.E. Piggott, and G.A. Carlson. 2004. The net benefits, including convenience, of Roundup Ready® soybeans: Results from a national survey. Technical Bulletin No. 2004-3. NSF Center for Integrated Pest Management. Raleigh, NC. Available online at http://cipm.ncsu.edu/cipmpubs/marra_soybeans.pdf. Accessed April 8, 2009.

Matus-Cádiz, M.A., P. Hucl, M.J. Horak, and L.K. Blomquist. 2004. Gene flow in wheat at the field scale. Crop Science 44(3):718–727.

May, O.L., and E.C. Murdock. 2002. Yield ranks of glyphosate-resistant cotton cultivars are unaffected by herbicide systems. Agronomy Journal 94(4):889–894.

May, O.L., A.S. Culpepper, R.E. Cerny, C.B. Coots, C.B. Corkern, J.T. Cothren, K.A. Croon, K.L. Ferreira, J.L. Hart, R.M. Hayes, S.A. Huber, A.B. Martens, W.B. McCloskey, M.E. Oppenhuizen, M.G. Patterson, D.B. Reynolds, Z.W. Shappley, J. Subramani, T.K. Witten, A.C. York, and B.G. Mullinix Jr. 2004. Transgenic cotton with improved resistance to glyphosate herbicide. Crop Science 44(1):234–240.

McHughen, A. 2006. The limited value of measuring gene flow via errant pollen from GM plants. Environmental Biosafety Research 5:1–2.

McNaughton, J.L., M. Roberts, D. Rice, B. Smith, M. Hinds, J. Schmidt, M. Locke, A. Bryant, T. Rood, R. Layton, I. Lamb, and B. Delaney. 2007. Feeding performance in broiler chickens fed diets containing DAS-59122-7 maize grain compared to diets containing non-transgenic maize grain. Animal Feed Science and Technology 132(3–4):227–239.

Mellon, M., and J. Rissler. 2004. Gone to seed: Transgenic contaminants in the traditional seed supply. Cambridge, MA: Union of Concerned Scientists.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Mitchell, J.P., D.S. Munk, B. Prys, K.M. Klonsky, J.F. Wroble, and R.L.D. Moura. 2006. Conservation tillage production systems compared in San Joaquin Valley cotton. California Agriculture 60(3):140–145.

Moschini, G., and H. Lapan. 1997. Intellectual property rights and the welfare effects of agricultural R&D. American Journal of Agricultural Economics 79(4):1229–1242.

Moschini, G., H. Lapan, and A. Sobolevsky. 2000. Roundup Ready® soybeans and welfare effects in the soybean complex. Agribusiness 16(1):33–55.

Mulugeta, D., and C.M. Boerboom. 2000. Critical time of weed removal in glyphosate-resistant Glycine max. Weed Science 48(1):35–42.

Myers, M.W., W.S. Curran, M.J. VanGessel, B.A. Majek, B.A. Scott, D.A. Mortensen, D.D. Calvin, H.D. Karsten, and G.W. Roth. 2005. The effect of weed density and application timing on weed control and corn grain yield. Weed Technology 19(1):102–107.

Naseem, A., and C. Pray. 2004. Economic impact analysis of genetically modified crops. In Handbook of plant biotechnology. eds. P. Christou and H.J. Klee, pp. 959–991. Hoboken, N.J.: John Wiley & Sons.

National Organic Program, Title 7 CFR 205.105.

Nielsen, C.P., and K. Anderson. 2001. Global market effects of alternative European responses to genetically modified organisms. Weltwirtschaftliches Archiv 137(2):320–346.

Nielsen, R.L. 2000. Transgenic crops in Indiana: Short-term issues for farmers. West Lafayette, IN: Purdue University. Available online at http://www.agry.purdue.edu/ext/corn/news/articles.00/GMO_Issues-000203.html. Accessed April 8, 2009.

NRC (National Research Council). 2004. Biological confinement of genetically engineered organisms. Washington, DC: National Academies Press.

Oplinger, E.S., M.J. Martinka, and K.A. Schmitz. 1998. Performance of transgenic soybeans: Northern United States. In Proceedings of the 28th soybean seed research conference, pp. 10–14 (Chicago, IL, December 1998). Alexandria, VA: American Seed Trade Association.

Organic Foods Production Act of 1990 7 U.S.C. sec 6501 et seq.

Owen, M.D.K. 2000. Current use of transgenic herbicide-resistant soybean and corn in the USA. Crop Protection 19(8–10):765–771.

Owen, M.D.K. 2005. Maize and soybeans—controllable volunteerism without ferality? In Crop ferality and volunteerism. ed. J. Gressel, pp. 149–165. Boca Raton, FL: Taylor & Francis.

Owen, M.D.K., and I.A. Zelaya. 2005. Herbicide-resistant crops and weed resistance to herbicides. Pest Management Science 61(3):301–311.

Padgette, S.R., D.B. Re, G.F. Barry, D.E. Eichholz, X. DeLannay, R.L. Fuchs, G. Kishore, and R.T. Fraley. 1996. New weed control opportunities: Development of soybeans with a Roundup ReadyTM Gene. In Herbicide-resistant crops: Agricultural, environmental, economic, regulatory, and technical aspects. ed. S.O. Duke, pp. 53–84. Boca Raton: Lewis Publishers.

Phipps, R.H., A.K. Jones, A.P. Tingey, and S. Abeyasekera. 2005. Effect of corn silage from an herbicide-tolerant genetically modified variety on milk production and absence of transgenic DNA in milk. Journal of Dairy Science 88(8):2870–2878.

Piggott, N.E., and M.C. Marra. 2007. The net gain to cotton farmers of a natural refuge plan for Bollgard II® Cotton. AgBioForum 10(1):1–10.

———. 2008. Biotechnology adoption over time in the presence of non-pecuniary characteristics that directly affect utility: A derived demand approach. AgBioForum 11(1):58–70.

Pilcher, C.D., and M.E. Rice. 2003. Economic analysis of planting dates to manage European corn borer (Lepidoptera: Crambidae) with Bt corn. Journal of Economic Entomology 96(3):941–949.

Price, G.K., W. Lin, J.B. Falck-Zepeda, and J. Fernandez-Cornejo. 2003. Size and distribution of market benefits from adopting biotech crops. November 20. TBN-1906. U.S. Department of Agriculture. Washington, DC.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

Qaim, M. 2009. The economics of genetically modified crops. Annual Review of Resource Economics 1(1).

Qaim, M., and G. Traxler. 2005. Roundup Ready soybeans in Argentina: Farm level and aggregate welfare effects. Agricultural Economics 32(1):73–86.

Raymer, P.L., and T.L. Grey. 2003. Challenges in comparing transgenic and nontransgenic soybean cultivars. Crop Science 43(5):1584–1589.

Reddy, K.N., A.M. Rimando, S.O. Duke, and V.K. Nandula. 2008. Aminomethylphosphonic acid accumulation in plant species treated with glyphosate. Journal of Agricultural and Food Chemistry 56(6):2125–2130.

Rice, M.E. 2004. Transgenic rootworm corn: Assessing potential agronomic, economic, and environmental benefits. Crop Management. Available online at http://www.plantman-agementnetwork.org/pub/php/review/2004/rootworm/. Accessed April 8, 2009.

Rice, M.E., and K. Ostlie. 1997. European corn borer management in field corn: A survey of perceptions and practices in Iowa and Minnesota. Journal of Production Agriculture 10(4):628–634.

Richardson, R.J., H.P. Wilson, G.R. Armel, and T.E. Hines. 2004. Mixtures of glyphosate with CGA 362622 for weed control in glyphosate-resistant cotton (Gossypium hirsutum). Weed Technology 18(1):16–22.

Ronald, P., and B. Fouche. 2006. Genetic engineering and organic production systems. Agricultural Biotechnology in California. University of California–Division of Agriculture and Natural Resources. Publication 8188. Available online at http://ucbiotech.org/resources/factsheets/8188.pdf. Accessed March 31, 2010.

Salazar, M.P., J.B. Miller, L. Busch, and M. Mascarenhas. 2006. The indivisibility of science, policy, and ethics: StarlinkTM corn and the making of standards. In Agricultural standards: The shape of the global food and fiber system. eds. R.J. Bingen and L. Busch, pp. 111–124. Dordrecht, The Netherlands: Springer.

Sanders, L.D. 2000. The economics of conservation and conservation tillage. Paper presented at the International Symposium on Conservation Tillage (Mazatlan, Mexico, January 24–27, 2000). Available online at http://agecon.okstate.edu/isct/labranza/sanders/mazecon00.doc. Accessed August 29, 2009.

Scursoni, J., F. Forcella, J. Gunsolus, M. Owen, R. Oliver, R. Smeda, and R. Vidrine. 2006. Weed diversity and soybean yield with glyphosate management along a north-south transect in the United States. Weed Science 54(4):713–719.

Sexton, S., D. Zilberman, D. Rajagopal, and G. Hochman. 2009. The role of biotechnology in a sustainable biofuel future. AgBioForum 12(1):130–140.

Sexton, S.S., Z. Lei, and D. Zilberman. 2007. The economics of pesticides and pest control. International Review of Environmental and Resource Economics 1(3):271–326.

Shaner, D.L. 2000. The impact of glyphosate-tolerant crops on the use of other herbicides and on resistance management. Pest Management Science 56(4):320–326.

Shaw, D.R., and J.C. Arnold. 2002. Weed control from herbicide combinations with glyphosate. Weed Technology 16(1):1–6.

Shaw, D.R., and C.S. Bray. 2003. Foreign material and seed moisture in glyphosate-resistant and conventional soybean systems. Weed Technology 17(2):389–393.

Siebert, M.W., S. Nolting, B.R. Leonard, L.B. Braxton, J.N. All, J.W. Van Duyn, J.R. Bradley, J. Bacheler, and R.M. Huckaba. 2008. Efficacy of transgenic cotton expressing CrylAc and CrylF insecticidal protein against heliothines (Lepidoptera: Noctuidae). Journal of Economic Entomology 101(6):1950–1959.

Sikkema, P.H., C. Shropshire, A.S. Hamill, S.E. Weaver, and P.B. Cavers. 2004. Response of common lambsquarters (Chenopodium album) to glyphosate application timing and rate in glyphosate-resistant corn. Weed Technology 18(4):908–916.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

———. 2005. Response of barnyardgrass (Echinochloa crus-galli) to glyphosate application timing and rate in glyphosate-resistant corn (Zea mays). Weed Technology 19(4):830–837.

Singer, J.W., R.W. Taylor, and W.J. Bamka. 2003. Corn yield response of Bt and near-isolines to plant density. Crop Management. Available online at http://ddr.nal.usda.gov/bitstream/10113/11882/11IND43806137.pdf. Accessed March 31, 2010.

Smith, K.R. 2002. Does off-farm work hinder “smart” farming? Agricultural Outlook 294: 28– 30. Available online at http://www.ers.usda.gov/publications/agoutlook/sep2002/ao2941.pdf. Accessed March 31, 2010.

Smyth, S., G.G. Khachatourians, and P.W.B. Phillips. 2002. Liabilities and economics of transgenic crops. Nature Biotechnology 20(6):537–541.

Snow, A.A., D.A. Andow, P. Gepts, E.M. Hallerman, A. Power, J.M. Tiedje, and L.L. Wolfenbarger. 2005. Genetically engineered organisms and the environment: Current status and recommendations. Ecological Applications 15(2):377–404.

Stanger, T.F., and J.G. Lauer. 2006. Optimum plant population of Bt and non-Bt corn in Wisconsin. Agronomy Journal 98(4):914–921.

Sweet, J., E. Simpson, J. Law, P. Lutman, K. Berry, R. Payne, G. Champion, M. May, K. Walker, P. Wightman, and M. Lainsbury. 2004. Botanical and rotational implications of genetically modified herbicide tolerance in winter oilseed rape and sugar beet (BRIGHT Project). Project report no. 353. Home-Grown Cereals Authority. Cambridge, UK.

Sydorovych, O., and M.C. Marra. 2007. A genetically engineered crop’s impact on pesticide use: A revealed-preference index approach. Journal of Agricultural and Resource Economics 32(3):476–491.

Tharp, B.E., and J.J. Kells. 1999. Influence of herbicide application rate, timing, and interrow cultivation on weed control and corn (Zea mays) yield in glufosinate-resistant and glyphosate-resistant corn. Weed Technology 13(4):807–813.

Thelen, K.D., and D. Penner. 2007. Yield environment affects glyphosate-resistant hybrid response to glyphosate. Crop Science 47(5):2098–2107.

Thomas, W.E., I.C. Burke, and J.W. Wilcut. 2004. Weed management in glyphosate-resistant corn with glyphosate and halosulfuron. Weed Technology 18(4):1049–1057.

Thomas, W.E., W.J. Everman, J. Allen, J. Collins, and J.W. Wilcut. 2007. Economic assessment of weed management systems in glufosinate-resistant, glyphosate-resistant, imidazolinone-tolerant, and nontransgenic corn. Weed Technology 21(1):191–198.

Tingle, C.H., and J.M. Chandler. 2004. The effect of herbicides and crop rotation on weed control in glyphosate-resistant crops. Weed Technology 18(4):940–946.

Traore, S.B., R.E. Carlson, C.D. Pilcher, and M.E. Rice. 2000. Bt and non-Bt maize growth and development as affected by temperature and drought stress. Agronomy Journal 92(5):1027–1035.

Trigo, E.J., and E.J. Cap. 2003. The impact of the introduction of transgenic crops in Argentinean agriculture. AgBioForum 6(3):87–94.

US-EPA (U.S. Environmental Protection Agency). 2001. Biopesticides registration action document—Bacillus thuringiensis plant-incorporated protectants. October 16. Office of Pesticide Programs–Biopesticides and Pollution Prevention Division. Washington, DC. Available online at http://www.epa.gov/oppbppd1/biopesticides/pips/bt_brad.htm. Accessed January 19, 2010.

USDA-AMS (U.S. Department of Agriculture–Agricultural Marketing Service). 2000. National Organic Program: Final Rule. Federal Register 65(246):80548–80596. Codified at 7 C.F.R. § 205.

USDA-ERS (U.S. Department of Agriculture–Economic Research Service). 2009. Corn: Market outlook, USDA feed grain baseline, 2009–2018. Washington, DC. Available online at http://www.ers.usda.gov/Briefing/corn/2009baseline.htm. Accessed September 2, 2009.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
×

USDA-NASS (U.S. Department of Agriculture–National Agricultural Statistics Service). 2000. Agricultural prices. 1999 summary. July. Pr 1-3 (00) a. Washington, DC. Available online at http://usda.mannlib.cornell.edu/usda/nass/AgriPricSu//2000s/2000/AgriPricSu-07-24-2000.pdf. Accessed April 14, 2009.

———. 2005. Agricultural prices. 2004 summary. July. Pr 1-3 (05) a. Washington, DC. Available online at http://usda.mannlib.cornell.edu/usda/nass/AgriPricSu//2000s/2005/AgriPricSu-08-16-2005.pdf. Accessed April 14, 2009.

———. 2008. Agricultural prices. 2007 summary. July. Pr 1-3 (08) a. Washington, DC. Available online at http://usda.mannlib.cornell.edu/usda/nass/AgriPricSu//2000s/2008/AgriPricSu-07-31-2008_revision.pdf. Accessed April 14, 2009.

———. 2009a. Agricultural prices. 2008 summary. July. Pr 1-3 (09) a. Washington, DC. Available online at http://usda.mannlib.cornell.edu/usda/nass/AgriPricSu//2000s/2009/AgriPricSu-08-05-2009.pdf. Accessed January 31, 2010.

———. 2009b. Data and statistics: Quick stats. Washington, DC. Available online at http://www.nass.usda.gov/Data_and_Statistics/Quick_Stats/index.asp. Accessed June 22, 2009.

USDA-NRCS (U.S. Department of Agriculture–Natural Resources Conservation Service). 2008. Energy Consumption Awareness Tool: Tillage. Washington, DC. Available online at http://ecat.sc.egov.usda.gov/. Accessed May 14, 2009.

Vaughn, T., T. Cavato, G. Brar, T. Coombe, T. DeGooyer, S. Ford, M. Groth, A. Howe, S. Johnson, K. Kolacz, C. Pilcher, J. Purcell, C. Romano, L. English, and J. Pershing. 2005. A method of controlling corn rootworm feeding using a Bacillus thuringiensis protein expressed in transgenic maize. Crop Science 45(3):931–938.

Venneria, E., S. Fanasca, G. Monastra, E. Finotti, R. Ambra, E. Azzini, A. Durazzo, M.S. Foddai, and G. Maiani. 2008. Assessment of the nutritional values of genetically modified wheat, corn, and tomato crops. Journal of Agricultural and Food Chemistry 56(19):9206–9214.

Vermij, P. 2006. Liberty Link rice raises specter of tightened regulations. Nature Biotechnology 24(11):1301–1302.

Vogel, G. 2006. Genetically modified crops. Tracing the transatlantic spread of GM rice. Science 313(5794):1714.

Wiatrak, P.J., D.L. Wright, J.J. Marois, and D. Wilson. 2005. Influence of planting date on aflatoxin accumulation in Bt, non-Bt, and tropical non-Bt hybrids. Agronomy Journal 97(2):440–445.

Wiesbrook, M.L., W.G. Johnson, S.E. Hart, P.R. Bradley, and L.M. Wax. 2001. Comparison of weed management systems in narrow-row, glyphosate- and glufosinate-resistant soybean (Glycine max). Weed Technology 15(1):122–128.

Williams, W.P., G.L. Windham, P.M. Buckley, and J.M. Perkins. 2005. Southwestern corn borer damage and aflatoxin accumulation in conventional and transgenic corn hybrids. Field Crops Research 91(2-3):329–336.

Wilson, T.A., M.E. Rice, J.J. Tollefson, and C.D. Pilcher. 2005. Transgenic corn for control of the European corn borer and corn rootworms: A survey of midwestern farmers’ practices and perceptions. Journal of Economic Entomology 98(2):237–247.

Wu, F. 2006. Mycotoxin reduction in Bt corn: Potential economic, health, and regulatory impacts. Transgenic Research 15(3):277–289.

Wu, F., J.D. Miller, and E.A. Casman. 2005. Bt corn and mycotoxin reduction: An economic perspective. In Aflatoxin and food safety. ed. H.K. Abbas, pp. 459–482. Boca Raton, FL: CRC Press.

Suggested Citation:"3 Farm-Level Economic Impacts." National Research Council. 2010. The Impact of Genetically Engineered Crops on Farm Sustainability in the United States. Washington, DC: The National Academies Press. doi: 10.17226/12804.
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Since genetically engineered (GE) crops were introduced in 1996, their use in the United States has grown rapidly, accounting for 80-90 percent of soybean, corn, and cotton acreage in 2009. To date, crops with traits that provide resistance to some herbicides and to specific insect pests have benefited adopting farmers by reducing crop losses to insect damage, by increasing flexibility in time management, and by facilitating the use of more environmentally friendly pesticides and tillage practices. However, excessive reliance on a single technology combined with a lack of diverse farming practices could undermine the economic and environmental gains from these GE crops. Other challenges could hinder the application of the technology to a broader spectrum of crops and uses.

Several reports from the National Research Council have addressed the effects of GE crops on the environment and on human health. However, The Impact of Genetically Engineered Crops on Farm Sustainability in the United States is the first comprehensive assessment of the environmental, economic, and social impacts of the GE-crop revolution on U.S. farms. It addresses how GE crops have affected U.S. farmers, both adopters and nonadopters of the technology, their incomes, agronomic practices, production decisions, environmental resources, and personal well-being. The book offers several new findings and four recommendations that could be useful to farmers, industry, science organizations, policy makers, and others in government agencies.

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