Perceptions of genetically modified crops among Danish farmers

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Perceptions of genetically modified crops among Danish farmersLartey G. Lawson a; Anders S. Larsen b; Søren Marcus Pedersen a; Morten Gylling a

a Institute of Food and Resource Economics, University of Copenhagen, Frederiksberg C, Denmark b

Food Industry Agency, Copenhagen K, Denmark

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To cite this Article Lawson, Lartey G., Larsen, Anders S., Pedersen, Søren Marcus and Gylling, Morten(2009) 'Perceptionsof genetically modified crops among Danish farmers', Food Economics - Acta Agriculturae Scandinavica, Section C, 6: 2,99 — 118To link to this Article: DOI: 10.1080/16507540903474699URL: http://dx.doi.org/10.1080/16507540903474699

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ORIGINAL ARTICLE

Perceptions of genetically modified crops among Danish farmers

LARTEY G. LAWSON1, ANDERS S. LARSEN2, SØREN MARCUS PEDERSEN1 &

MORTEN GYLLING1

1Institute of Food and Resource Economics, University of Copenhagen, Rolighedsvej 25, 1958 Frederiksberg C, Denmark, and2Food Industry Agency, Nyropsgade 30, 1780 Copenhagen K, Denmark

AbstractThe objective of this paper is to investigate what factors have an impact on farmers’ attitude toward accepting geneticallymodified (GM) crops. For this purpose, a farm survey was conducted and data were subjected to a multinomial logitregression analysis. The main results indicate that approximately 45%, 28%, and 27% of the farmers are positive, negative,and neutral, respectively, toward GM technology. Farm income is the main driver for adoption of the technology. More than25% of neutral as well as negative farmers will adopt GM crops if farm income improves. Farmers expect improved yieldsand reduction in the use of herbicides, insecticides, fungicides, and growth regulators. Neutral farmers are additionallyconcerned about the general risks and resistances that may be attributed to adopting GM crops. While positive farmers areadditionally concerned about environment, health hazards, and the limitations on biological diversity within the vicinity oftheir farms. A significant number of negative farmers would revise their choice if the chemical plant protection inputs arereduced. The age of the farmer has a less clear impact on the attitude toward GM technology.

Keywords: Pesticide-resistance, gene-technology, biological-diversity, farm income, survey.

1. Introduction

The first generations of genetically modified (GM)

crops (Killicoat, 2004) were designed to resist a

specific herbicide or specific insects and are as such

beneficial for farmers to reduce inputs to farm

management. On a global scale farmers have rapidly

adapted to the use of GM crops. In 2007, the total

area under tillage with GM crops increased by

12�114 million hectares (GMO Compass, 2008).

The first commercial GM crops were grown in

China in 1992 and large-scale adoption in the USA

began in 1996 (Enriquez, 2001). In 1995, there were

no commercial plantings of GM crops in the USA

(Hillyer, 1999). In a recent update on US agricul-

ture, the data were 87% for cotton, 73% for corn,

and 91% for soybean (USDA, 2007). Within USA,

the speed of GM adoption has been rather signifi-

cant. In 1999, Carpenter and Gianessi (1999) stated

that the adoption rate of Roundup resistant soybean

was limited only by the availability of seeds. Today

the world’s leading producers of GM crops are the

USA, Argentina, Brazil, Canada, India, and China.

Whereas the US farmers have been very keen to

adopt this new technology, adoption has been very

slow in Europe due to a strong polarization between

opponents and supporters of this new technology.

The public opposition has been so severe, that only

about 107,000 ha of arable land, primarily GM

maize grown in Spain, is currently cultivated in the

EU (GMO Compass, 2009).

So far, the debate and studies concerning the

perception of GM crops and GM food have mainly

been among consumers and public stakeholders.

A significant number of these studies have been

carried out to determine the consumers’ attitude

toward GM crops in Europe. They find that there is

a general concern among consumers with regard to

GM food. A significant number of studies in Europe

dealing with these issues are represented in Jonas

and Beckmann (1998), Bredahl (2001), and Saher

et al. (2006). Most of these studies conclude that the

Correspondence: L. G. Lawson, Institute of Food and Resource Economics, University of Copenhagen, Rolighedsvej 25, 1958 Frederiksberg C, Denmark.

E-mail: [email protected]

Food Economics � Acta Agricult Scand C, 2009; 6: 99�118

ISSN 1650-7541 print/ISSN 1651-288X online # 2009 Taylor & Francis

DOI: 10.1080/16507540903474699

Downloaded By: [Lawson, Lartey G.] At: 08:15 4 February 2010

majority of consumers have reservations about GM

food � and there appears to be a downward trend

over time (Frewer et al., 2004).

In accepting GM crops, focus has mainly been on

risks to health and the environment (Wagner et al.,

1997). The public concern, which goes much

deeper, involves perceived risks, benefits, and moral

concerns. Wagner et al. (1997) in the Eurobarometer

survey from 1996, indicated that in the first

place, usefulness is a precondition for support of

biotechnology; second, people seem prepared to

accept some risks as long as there is a perception

of usefulness and no moral concern; but third and

crucially, moral doubts act as a veto irrespective of

people’s views on use and risk.

Lassen and Jamison (2006) in a Danish study using

focus group interviews found that social, economic,

and cultural issues were relevant for public acceptance

of genetic technologies. Hence, focusing only on

economic costs and benefits of these technologies

and the short-term health and environmental risks is

considered insufficient to accept the technology.

In Denmark, the government initiated a strategy

work on co-existence between GM and Non-GM

crops back in 2002. Based on the recommendations

a co-existence act was passed through the Danish

Parliament (act. No. 436 of June 9, 2004). On the

one hand, it supports the opportunity to grow GM

crops and on the other hand it fulfills the demand for

a continued non-GM crop production. A number of

farmers have been educated to handle GM crops in

their crop rotation but so far no commercial scale

GM crop production has been initiated for the

growing season 2007, 2008, and 2009 in Denmark.

The farmers are largely not present in the debate

and yet their decisions about whether or not to

cultivate GM crops will be crucial for the future of

this technology in Europe (Hall, 2008). The aim of

this paper is to investigate what factors have an

impact on farmers’ decision to cultivate GM crops

and hence to understand farmers’ perception of the

new technology.

The rest of the paper is organized as follows:

Section 2 gives a short literature review of farmers’

attitude toward GM crops. Section 3 presents the

methodology and data collection, while Section 4

provides the results of this study. Discussion and

concluding remarks are presented in Sections 5 and

6, respectively.

2. Review on farmers’ attitude toward

genetically modified (GM) crops

What determines whether or not a farmer adopts a

new technology and what are the key drivers in

making farmers choose to grow a GM variety?

According to Hillyer (1999), this question can

mainly be related to two issues. Firstly, does it

work? Secondly, will it make money? (i.e. increase

net income) From a farmer’s perspective, technology

is successful only if it is profitable (Hillyer, 1999).

When GM crops were first marketed in the USA,

some surveys examined the motives for GM adop-

tion. In a 1997 survey conducted by the Agricul-

tural Resource Management Study, the majority

(54�76%) of farmers stated ‘‘increase yields through

improved pest control’’ as the main reason for

adopting GM crops. A second reason, ‘‘decreased

pesticide cost’’ was given by ‘‘19�42%,’’ and only

1.8�6.4% stated ‘‘increased planting flexibility’’

(e.g. ease crop rotation, reduced tillage systems, or

no-tillage systems) as their main reason for favoring

a GM crop, and 0�2% stated that they adopted the

technology for environmental reasons (Fernandez-

Cornejo & McBride, 2000).

In a 1998 Iowa crop survey, interviews were

conducted with 800 farmers. To the question, why

the farmers planted GM soybean; 53% stated

increased yields through improved pest control,

27% stated decreasing pesticide cost, 12% stated

increased flexibility in planting, and 3% listed a more

environmentally friendly practice (Duffy, 1999). For

the Bt corn, an overwhelmingly majority of the

farmers stated increased yields as the reason for

planting. Only 7% stated decreasing cost to pesticides

(Duffy, 1999).

In USDA’s Agricultural and Resource Manage-

ment Surveys (ARMS) conducted from 2001 to

2003, the majority of farmers adopting GM crops

did so because of expected profitability increases

through higher yields and/or lower costs, e.g. from

operator labor and pesticides use (Fernandez-

Cornejo & Caswell, 2006).

Kondoh and Jussaume (2006) investigated how

farmers’ expressed willingness to use a controversial

technology on their farms can be influenced by

a mixture of their personal characteristics, social

networks, and political�economic structures. Their

results show that farmers’ production practices and

market strategies may be at least as important as

their socio-economic characteristics in explaining

their potential attitude toward using GM technology.

They found that farmers’ interest in trying GM

crops are a result of complex thought processes

wherein they weigh their personal assessments of the

technology against the assessment of other actors in

their networks. Farmers with a formal academic

training and who are innovators in terms of direct

marketing or organic production are less enamored

with the idea of using GM technology than other

highly educated farmers. This suggests that farmers

may build their attitudes toward technologies and

100 L. G. Lawson et al.


farm management practices as a result of shared

experiences through the interactions with other

social actors.

Studies of GM farmers’ attitude toward GM crops

are less abundant in the EU than in the USA.

Breustedt et al. (2008) analyzed German farmers’

willingness to adopt GM oilseed rape prior to its

commercial release by using choice experiments.

Breustedt et al. (2008) found that farmers’ GM

adoption decisions are driven by profit expectations,

neighbors, and the public’s opinion along with

personal as well as farm characteristics. Monetary

determinants, such as lower gross margin for farms

using GM seeds, expected liability costs from cross

pollination, and restricted flexibility in returning to

conventional rape seed growing, all reduced the

propensity to grow the GM variety. They also find

that the seed price has a large influence on farmers’

demand for the new technology, and that a farmer’s

attitude toward growing GM is reduced if their

neighbors are negative toward the technology. They

further conclude that female farmers, older farmers,

farmers with children aged 16 years and below, as

well as farmers living close to a city are significantly

less likely to adopt the GM crops. Larger farm size

and a college degree or university degree is found to

have the opposite effect, with farmers being more

positive toward the GM variety.

The Swedish farmers’ attitude toward GM insect

resistant crops was investigated by Lehrman and

Johnson (2008). The reports showed that the

majority of the farmers were negative (56.7%),

although almost one-third claimed to be neutral to

GM crops. Benefits from GM crops were recognized

in terms of agricultural production and for the

environment, but farmers were highly concerned

about the consumers’ willingness to buy GM pro-

ducts. Dividing the farmers into positive, negative,

and neutral groups revealed differences in their

wishes and concerns. Farmers negative to GM crops

were more concerned than positive farmers about

the crops being dangerous for humans and livestock

consumption and mainly perceived no benefits from

growing the GM crop. The positive farmers (12.7%)

were concerned about potential problems with

growing a marketable crop and expensive seeds,

but saw a potential benefit in the reduced health risk

to the grower due to less use of pesticides. The

neutral farmers (30.6%) were mostly related to the

positive farmers’ attitudes, implying that they recog-

nize the advantages of the GM crop, but also fear

potential drawbacks which may prevent them from

accepting the technology. The study also revealed

that farmers who had a degree in agronomy or

agriculture and rural management were significantly

more positive toward GM crops. These farmers also

owned larger farms, and there was also a significant

correlation between increasing farm size and a more

positive attitude.

In a questionnaire study by Gomez-Barbero and

Rodrıguez-Cerezo (2007) with a focus on GM Bt

maize among Spanish farmers, it was found the three

main reasons for adopting GM crops were ‘‘reduc-

tion of risk of losses due to Maize Borer,’’ ‘‘higher

yields,’’ and that the GM crops (seeds) ‘‘ensure better

quality of the harvest.’’ The Corn Borer that the Bt

maize is resistant to is particularly difficult to control

with chemicals because the insecticide is only effec-

tive in a very narrow time span between egg hatch

and larvae stage (Gomez-Barbero & Rodrıguez-

Cerezo, 2007). Hence, it is suggested that the main

reason for adopting GM crops is risk aversion as is

the case for Spanish farmers. Farmers see GM maize

as an insurance against loss from pests, and farmers

who face more severe pests are likely to adopt the

GM technology (Alexander, 2006).

To sum up, it appears that farmers are likely to

adopt new practices and technologies if they expect

to benefit from them in monetary terms. From the

surveys, as mentioned above, expected profitability

from improved yields, reduced use of pesticides, and

reduced risk have been the main motivators for the

initial adoption of GM technology. This appears to

be so for the US farmers, though under a different

agricultural policy context, as well as for the EU

farmers although the data material are limited for the

EU.

3. Methodology, data, and analyses

3.1. Economic framework

The discussion in the previous section suggests that

farmers’ willingness to adopt the GM technology is

derived from their considerations of farm income,

biodiversity, and risks, as well as their perceptions of

consumers attitudes toward GM crops (Lehrman &

Johnson, 2008). The model for farmers’ decision to

adopt GM technology is proposed to depend on the

weight given to the various considerations such that

a farmer may select among three mutually exclusive

alternatives, such as adoption (yes), unsure (neu-

tral), and non-adoption (no). Generally technology

adoption decisions are modeled as an outcome of a

utility maximization problem (Hill, 1983; Breustedt

et al., 2008), which is derived from constrained

maximization of the indirect profit function (Basant,

1997). This implies that the farmer compares the

maximum utility attainable given each alternative

decision and selects the one which yields the max-

imum utility. Let Uyes, Uneutral, and Uno denote the

ith farmer’s expected utility from adoption, unsure,

Farmers’ perceptions of genetically modified crops 101


and non-adoption. The technological choice deci-

sion Yi is given as:

Yi�Yes if Ui yes �U i neutral and Ui yes �Ui no

Neutral if Ui neutral �Ui yes and Ui neutral �Ui no

No if Ui no �Ui yes and Ui no �Ui neutral

8<:

9=;:

(1)

The maximum utility, Uij of the farmer i, from his or

her choice decision j for yes, neutral, or no, can be

decomposed into non-stochastic (S) and stochastic

(o) parts such that these represent the function of

observable and unobservable variables, respectively,

hence,

Uij �Sij �oij : (2)

Modeling a choice decision following the discussion

in Maddala (1983), a multinomial logit specification

for the non-stochastic part Sij may be approximated

in linear form such that the econometric estimation

of the model is effected by taking the natural log

odds of the ratio of two probabilities. Given that

probability is the chance for an event to occur, the

odds is the ratio of two probabilities and the odds

ratio is the ratio of two odds when comparing two

groups, which measures the impact of a predictor

variable. Hence, with pno as the base, the two natural

log odds ratios estimated simultaneously are given

by:

ln

�pyes

pno

��b0 yes�b1yesxi1� � � ��bk yesxik; (3)

ln

�pneutral

pno

�

�b0 neutral�b1 neutralxi1� � � ��bk neutralxik: (4)

The bs are the estimated coefficients and reflect the

effects of the independent variables xk on the logit,

which expresses the likelihood of farmers responding

yes or being neutral, relative to the base response no.

The resulting three probabilities are estimated as:

Prob(Yi � j)

�exp(b

0

jXik)

exp(b0

yesXik) � exp(b0

neutralXik) � exp(b0

noXik);

j�yes; neutral; or no; (5)

where bj is a vector of parameters estimated from

Equations (3) and (4) for the vector of independent

variables Xk describing the choice probabilities.

Since the probabilities sum to one, the normal-

ization rule suggests that one of the parameter

vectors, say bno equals to zero. Following Green

(2002), the probabilities for the three alternative

choices become:

Pj �Prob(Yi � j)

�exp(b

0

jXik)

1 � [exp(b0

yesXik) � exp(b0

neutralXik)];

j�yes or neutral; (6)

Pno�Prob(Yi�no)

�1

1 � [exp(b0

yesXik) � exp(b0

neutralXik)]: (7)

The magnitude of the relative effects can be eval-

uated by the odds ratios (relative risk), which for a

unit change is exp(bjk). Following Green (2002), the

marginal effects di on the probabilities of choice with

respect to the Xkth vector of independent variables

can be estimated as:

dj �@Pj

@Xk

�Pj

bjk�

XJ

k�0

Pkb jk

�;

where j�yes; neutral; or no: (8)

Note that the sum of the product term, Pkbk

in Equation (8) is given by (Pyes�byes)�(Pneutral�bneutral)�(Pno�bno). However, due to the normal-

ization, which requires the sum of the probabilities

to be zero (Pno�bno) is set to zero, and dno is derived

as the negative of the sum of dyes and dneutral, i.e. �(dyes�dneutral). The sign or the magnitude of the

marginal effects need not bear any relationship to the

sign of the coefficients (Green, 2002).

3.2. Survey

A questionnaire survey was designed and forwarded

to 400 Danish farmers (respondents) by mail. The

selection of respondents was taken from an existing

farm database administrated by the Danish Institute

of Agricultural Sciences (DIAS, Aarhus University).

The sample collection was random but stratified on

farms with more than 100 ha and less than 100 ha

and represented both part-time and full-time farm-

ers to ensure the criteria for selection with equal

representation.

Mainly closed questions were used in the ques-

tionnaire to ensure that farmers’ answers were as clear

as possible and hence capture the knowledge of what

influences their perceptions of cultivating GM crops.

In the survey, farmers were asked to answer a number

of questions concerning expected costs and benefits

of GM crops, environmental considerations, and

their personal expectations about growing GM crops.

To determine the characteristics and the percep-

tions that influence the decision to cultivate GM

crops in the future (response variable), farmers were

requested to express their views on 30-item ques-

tions or statements, expressing expectations and

concerns about GM crops and provide information



on farm characteristics. The farm characteristics

include questions about their age group, farm type,

and farm size defined by the area of hectares

cultivated. Farmers were also asked to state whether

or not they expect an improvement in future profit,

defined by change in gross margins by a certain

amount. The expected change in gross margin, was

chosen to reflect a measure of farm size in terms of

the economy of size which might be a predictor for

adopting a new technology (Kondoh & Jussaume,

2006).

The 30-item questions are generally related to

farmers’ perceptions and pertain to:

(1) Whether they expected changes in the use of

various inputs (i.e. whether or not the use of

insecticides, herbicides, fungicides, growth

regulators, seeds, and fertilizer will be re-

duced) as well as risks and other matters that

potentially discourage them from cultivating

GM crops. These are referred to as the 12

items in the texts and reflect farmers’ own

direct expectations.

(2) Their general expectations concern environ-

mental and health hazards (i.e. risks to envir-

onmental and human health) and the

economic benefits of cultivating GM crops.

These are referred to as the 18 items (general

expectations) in the texts.

The 12-item questions pertaining to plant protection

and seed inputs as well as the risks and other issues

leading to the discouragement from adopting GM

are coded as dummy variables (zeros and ones). The

18-item question statements, which reflect farmers’

general expectations to the environment, resistance,

and risks associated with GM crops as well as

economic benefits, are scored using Likert scales

coded 1�5 for responses corresponding to ‘‘strongly

disagree,’’ ‘‘disagree,’’ ‘‘either or,’’ ‘‘agree,’’ or

‘‘strongly agree,’’ respectively. No replies contribute

zero to the responses.

Generally, these questions were formulated to

reflect income benefits and risk issues of relevance

for the discussion as to cultivating GM crops in

Denmark as well as suggested by the literature

(Duffy, 1999; Hillyer, 1999; Kondoh & Jussaume,

2006; Breustedt et al., 2008; Lehrman & Johnson,

2008).

3.3. Data

Out of the 400 questionnaires that were mailed to

farmers, 175 respondents returned a completed

questionnaire (44%). Among these respondents,

50% were above 50 years of age. The main farming

practices were well represented among the respon-

dents such that 31% had only crops, 63% had either

pigs or milk production along with crop production,

and only 6% did not grow crops on their farms. The

most frequent crops in rotation were wheat, rape-

seed, and barley. Seventy-eight farmers (45%) felt

that they would like to grow GM crops and 49

farmers (28%) stated that they would not. The

remaining group of 48 farmers (27%) was not clear

on the issue (neutral).

The questions and the distribution of respondents

by farm characteristics, as well as by the replies to

the 12-item and 18-item statements, are given in

Tables I and II.

3.4. Statistical analysis

To investigate the factors that have an impact on the

willingness or not to adopt GM crops in the future, a

four-step procedure was used. Firstly, a chi-square

test of independence between response variable and

the independent variables, as well as between in-

dependent variables were conducted to generate

information on the level of dependence and the

association between variables. Secondly, the 30-

item, i.e. the 12-item dummy variables, plus the

18-item Likert scale statements, were subjected to a

joint principal component analysis (PCA) using ones

as prior communality estimates (Hatcher, 1994).

The principal axis method was used to extract the

components and was followed by a varimax (ortho-

gonal) rotation. The first eight components (factors)

for the PCA analysis were retained for rotation.

Items with factor loadings of 0.60 or greater are

those of main relevance for a particular factor

component. Hence, information from the original

30-item responses was reduced to eight uncorrelated

variables. Thirdly, the weighted factor scores were

calculated.

Finally, farm characteristics as well as the eight

weighted factor scores were subjected to a multi-

nomial logit regression analysis to identify the

variables that significantly impact on the willingness

or not to adopt GM crops in the future. Following

the economic framework in Section 3.1, the multi-

nomial logit regression model (Green, 2002) was

specified as:

Logit(pj ½no)� log

�pj

pno

�

�a0�a1jkage�a2jlfarm type

�a3jmhasize�a4jnprofit

�bqj f scores�oj : (9)

From the model specification in Equation (9), pj are

the probabilities of responding ‘‘yes’’ or ‘‘neutral’’ to



Table I. Frequency count and percent distribution of farm characteristics and 12-item responses.

Respondents Attitude

Characteristics and statements Count Count (%) Yes (%) Neutral (%) No (%)

Farm types

Only crops 54 31 37 28 35

Pig and crop production 60 34 50 30 20

Cattle and crop production 50 29 40 30 30

Other type 11 6 73 0 27

Farmer age group, years

20�40 39 22 54 31 15

�40�50 45 26 58 11 31

�50�60 47 27 36 36 28

�60 44 25 32 32 36

Farm size (ha)

580 74 42 24 31 45

�80�120 26 15 35 38 27

�120 75 43 68 20 12

Expected increase in gross margin (EUR/ha)

0 94 54 24 29 47

�0�27 18 10 50 44 6

�27�81 63 36 73 21 6

Statement: what would make you not grow GM crops (six of the 12-item statements)?

Risk of gene dispersal to other fields

No 53 30 53 25 23

Yes 122 70 41 29 30

Health hazards

No 53 30 42 25 34

Yes 122 70 46 29 25

Risk of deteriorated biological diversity

No 84 48 50 25 25

Yes 91 52 40 30 31

Relations to neighboring farms

No 115 66 48 25 27

Yes 60 34 38 32 30

High cost of seeds

No 136 78 41 27 32

Yes 39 22 56 28 15

Low selling price of crops

No 116 66 36 24 40

Yes 59 34 61 34 5

Statements: about the decrease in inputs if GM crops are cultivated (six of the 12-item statements)

Use of fungicides

No 70 40 24 27 49

Yes 105 60 58 28 14

Use of herbicides

No 60 34 18 28 53

Yes 115 66 58 27 15

Use of insecticides

No 62 35 21 29 50

Yes 113 65 58 27 16

Use of growth regulators

No 89 51 33 28 39

Yes 86 49 57 27 16

Use of fertilizer

No 152 87 42 28 30

Yes 23 13 61 22 17

Use of seeds

No 156 89 44 28 28

Yes 19 11 53 21 26



Table II. Frequency count percent distribution of 18-item statements and percent attitude toward GM.


Statements/responses Count Count (%) Yes (%) Neutral (%) No (%)

It is important that GM crops improves the gross margin

No answer 17 10 0 35 65

Strongly disagree 7 4 14 14 71

Disagree 5 3 20 0 80

Either or 25 14 16 20 64

Agree 52 30 48 38 13

Strongly agree 69 39 68 23 9

It is important that GM crops improves the yield

No answer 17 10 6 29 65



Either or 29 17 24 28 48

Agree 69 39 51 35 14


It is important that quality of the crops is improved

No answer 18 10 0 33 67



Either or 22 13 41 27 32

Agree 69 39 46 32 22


It is important that the risk of gene dispersal from GM crops to neighboring fields is minimal

No answer 15 9 0 27 73



Either or 11 6 73 27 0

Agree 43 25 63 23 14


It is important to distinctly label GM products

No answer 19 11 5 32 63


Disagree 12 7 100 0 0

Either or 33 19 61 33 6

Agree 46 26 50 35 15


It is important that there is no health risk associated with the GM crops

No answer 13 7 0 31 69


Disagree 0 0 10 6 0

Either or 3 2 33 33 33

Agree 47 27 55 30 15


It is important that GM crops do not have an effect on the surrounding environment

No answer 12 7 0 25 75



Either or 7 4 71 14 14

Agree 47 27 57 30 13


It is important that GM crops are resistant to insects

No answer 13 7 8 23 69


Disagree 4 2 50 25 25

Either or 35 20 40 31 29

Agree 68 39 50 29 21


It is important that GM crops are resistant to fungi

No answer 13 7 8 23 69



Either or 19 11 16 47 37



Table II. (Continued).



Agree 75 43 51 27 23


It is important the GM crops are Roundup resistant

No answer 15 9 0 33 67


Disagree 17 10 47 24 29

Either or 49 28 39 35 27

Agree 49 28 53 29 18


It is important to maintain/improve the biological diversity

No answer 15 9 0 27 73



Either or 29 17 55 28 17

Agree 65 37 54 31 15


GM crops will be useful in the future

No answer 14 8 0 36 64



Either or 47 27 28 40 32

Agree 55 31 64 24 13


The GM technology is itself exciting

No answer 14 8 7 21 71



Either or 33 19 39 27 33

Agree 74 42 54 32 14


GM technology holds the potential for an improved gross margin

No answer 14 8 7 29 64


Disagree 8 5 25 13 63

Either or 50 29 28 34 38

Agree 62 35 58 31 11


GM crops give potential of simpler farm management

No answer 14 8 0 29 71


Disagree 10 6 50 0 50

Either or 59 34 39 36 25

Agree 60 34 53 32 15


The environment will benefit from the GM crops

No answer 16 9 13 25 63


Disagree 19 11 21 11 68

Either or 55 31 40 40 20

Agree 44 25 66 30 5


The selling price of the GM crop will increase

No answer 14 8 0 29 71


Disagree 35 20 57 14 29

Either or 90 51 50 32 18

Agree 18 10 56 28 17




cultivating GM crops against ‘‘no’’ for not cultivat-

ing GM crops. The ajs, and the bjs are the parameters

to be estimated simultaneously for the two (yes and

neutral) regression equations represented by Equa-

tion (9) and oj are the corresponding residual terms.

The variable age classified into 4 k levels in the

questionnaire are divided into groups of 20�40, 40�50, 50�60, and �60 years. The variable age repre-

sents the joint effect of the levels of farming education

and experience. It is expected that young farmers with

modern formal education in farming might be

inclined to respond yes to adopt the cultivation of

GM crops. However, being less experienced they may

be inclined to wait by responding neutral to the

cultivation of GM crops. At the other end of the age

scale, farmers with substantial farming experience

might be inclined to respond no or neutral if the

benefits associated with GM crops are less than the

perceived risks that might be incurred by themselves

or society. The farmers in the middle of the age

groups might respond positive to the cultivation of

GM crops given the combined effect of their level of

education and moderate experience.

Farm type is categorized into four (l) levels; only

crops, pig and crops, cattle and crops, as well as

‘‘other type’’ (pig, cattle, crops, and other) farms.

The variable is of interest because some poultry

farmers are, for example, paid a premium for not

using GM feedstuff by their slaughterhouse. Addi-

tionally, crops meant for human consumption, e.g.

for bred-making are expected to be labeled (EU,

2003). Hence, crop farmers might not be willing to

adopt GM crop cultivation if their market situation

is threatened.

Farm size, ‘‘hasize,’’ which is measured as total

hectare of farm area has three (m) levels divided into

groups of less than 80, 80�120, and larger than 120

ha. Although the sample selection was stratified by

less and more than 100 ha farm area, the question was

constructed with three levels to account for a better

variation in the variable. It is expected that the

benefits from the reduction in the use of plant

protection inputs herbicide, insecticides, fungicides,

and growth regulators will accrue to owners of large

farms. Therefore, these farmers will be more inclined

to adopt GM crops than those with small farms.

The expected amount by which the gross margin,

i.e. the short-term profit (sales�variable costs), is

expected to increase per ha, has three (n) levels: 0, 0�27, and 27�81 EUR. The expected change repre-

sents the improvement in the economy of size. But it

also corresponds to a monetary threshold at which

farmers will be willing to adopt GM crops. A higher

profit level is expected to be a strong motivation for

adopting GM crops.

The ‘‘fscores’’ represent the eight q, weighted

factor scores estimated from the PCA analysis for

the responses of the 30-item statements. The eight

weighted factor scores, of which two cover the

18-item Likert responses, represent issues related

to and are referred to in short as ‘‘improved farm

income’’ (F1) as well as ‘‘risk and resistance’’ (F2).

The next six weighted factor scores covering the

12-item dummy responses are ‘‘reduced chemical

plant protection inputs’’ (F3), ‘‘high seed cost and

low crop price’’ (F4), ‘‘deteriorating biodiversity’’

(F5), ‘‘health hazard’’ (F6), ‘‘reduced demand for

fertilizer’’ (F7), and ‘‘reduced demand for seed’’

(F8).

4. Results

4.1. Descriptive analyses

4.1.1. Chi-square tests. Table III shows the pairwise

chi-square tests of independence. The tests of

independence between GM cultivation in the future

and each of the independent variables suggest that

the cultivation of GM crop depends on all farm

characteristics except for farm type (Row 1 under

column titles). However, because farm type is

correlated with farm size and chemical plant protec-

tion inputs, the variable is dropped from the

statistical analysis.

Table III further shows that among the 12-item

variables, future adoption of GM crops depends on

Table II. (Continued).



GM crops will reduce the use of input factors

No answer 17 10 12 24 65



Either or 75 43 43 29 28

Agree 54 31 52 31 17


Note: The 18-item statements are related to general environmental consequences, health risks, and economic benefits.



Table III. Chi-square test results of association between the dependent and independent variables as well as between independent variables.

Farm characteristics and plant protection inputs Refrain from GM cultivation due to:

/

Farm

ers

age

/

Typ

eof

farm

/

Farm

size

(ha)

/

Gro

ssm

arg

in

/

Fer

tilize

r

/

Her

bic

ide

/

Inse

ctic

ide

/

Fu

ngic

ide

/

See

ds

/

Gro

wth

regu

lato

rs

/

Ris

kof

gen

ed

isper

sals

/

Hea

lth

haza

rds

/

Ris

kof

det

erio

rate

dbio

logic

al

div

ersi

ty /

Rel

ati

on

sto

nei

ghbori

ng

farm

s

/

Hig

her

pri

ceon

seed

s

/

The

sellin

gpri

ceof

the

crops

/

Farm

chara

cter

isti

csan

dpla

nt

pro

tect

ion

inpu

ts

Cultivate GM a x ns xxx xxx ns xxx xxx xxx ns xxx ns ns ns ns ns xxx

Farmers age � xxx ns ns x x xx ns xx xxx xxx � � ns xx

Type of farm xx ns ns � x x x ns ns ns ns ns ns ns

Farm size (ha) � ns xx xxx xxx ns xx ns ns ns ns ns ns

Gross margin ns xxx xxx xxx ns xx ns � ns ns ns ns

Fertilizer xxx xxx xx xx xxx ns ns � ns x x

Herbicide xxx xxx � xxx x xx � ns ns x

Insecticide xxx � xxx xx xx � ns ns xx

Fungicide � xxx � xx x ns ns xxx

Seeds � x ns ns ns x ns

Growth regulators xxx x ns ns ns xx

/

Ref

rain

from

GM

cult

ivati

on

du

eto

:

Risk of gene dispersals xxx xxx xxx x ns

Health hazards xx x ns �Risk of deteriorated

biological diversity

xx ns ns

Relations to neighboring farms xx ns

Higher price on seeds xxx

The selling price of the crops

aIs the dependent variable;��pB0.10; x�pB0.05; xx�pB0.01; xxx�pB0.001; ns�non-significant.

108

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perceptions pertaining to the use of chemical plant

protection inputs of herbicides, insecticides, fungi-

cides, and growth regulators, as well as on ‘‘high seed

cost’’ and ‘‘low crop price.’’ Furthermore, among

the 12-item variables there is a strong pairwise

association between variables (see the diagonals).

This, in summary, calls for a PCA (factor analysis) to

reduce the number of variables to be included in the

multinomial logit model.

4.1.2. Factor analysis. The eight-factor components

identified and retained from the PCA for the 30-item

variables are presented with their respective loadings

in Table IV.

For farmers’ opinion about the 30-item variables,

the eight factor components account for 76% of the

total variation with an alpha coefficient of 0.95 for

the internal consistency reliability index. The index

measures how the individual items correlated with

one another. A value close to one is most preferred

and above 0.70 is conventionally accepted (Hatcher,

1994). The measure suggests that the extracted

factors, and hence their weighted factor scores,

reasonably account for the variations in the data

and are useful for inclusion as independent variables

in the multinomial logit model.

4.2. Statistical results

4.2.1. Multinomial logit model. The multinomial logit

estimation based on Equations (3) and (4), and made

operational in Equation (9) examines the simulta-

neous impact of the independent variables on the

future adoption decision on cultivating GM crops.

The model is estimated using the statistical software

SAS (2008); and the LIMDEP logit software (Green,

2002) is used to estimate the marginal changes using

Equation (8). The fitted model was evaluated by the

Log likelihood ratio. The test where all independent

variables are simultaneously zero was rejected (x2�171; df�30; pB0.0001). The analysis of the effects

suggests that all independent variables except for the

age of farmers, farm size, and the use of fertilizer

impact significantly on the adoption decision (at

pB0.10 or pB0.05).

Table IV. Summary results of the 30-items principal components analysis.

Eigenvalue/variance (%) Factor name Set of items with ordered factor loadings of 0.60 or greater Loadings

18-items group

F1:6.7/30 Improved farm income (F1) GM technology holds the potential for an improved gross margin 0.84

GM crops will benefit the environment 0.78

GM crops will be useful in the future 0.77

GM crops provide potentials for simpler farm management 0.74

GM technology is itself exciting 0.71

GM crops will benefit from increase sales price 0.69

Important that GM crops improves the gross margin 0.65

Important that GM crops improves the yield 0.65

GM crops will reduce the use of input factors 0.64

F2:5.8/25 Risk and resistance (F2) It is important that GM crops do not have an effect on the

environment

0.83

It is important that there is no health risk associated with the

GM crops

0.81

It is important that GM crops are resistant to insects 0.74

It is important that GM crops are resistant to fungi 0.74

It is important to minimize the risk of gene dispersal of GM

crops to other fields

0.73

It is important to distinctly label GM products 0.73

It is important to maintain/improve the biological diversity 0.63

12-items group

F3:3.6/16 Reduced chemical plant

protection inputs (F3)

Decreased demand for insecticides 0.91

Decreased demand for fungicides 0.87

Decreased demand for herbicides 0.83

Decreased demand for growth regulator 0.63

F4:1.6/7.0 High seed cost and low crop

price (F4)

High cost for GM-seed 0.83

Low price for GM-crop 0.71

F5:1.5/6.5 Deteriorating biodiversity (F5) Biodiversity risk 0.82

F6:1.1/5.2 Health hazards (F6) Health risk 0.78

F7:1.1/5.2 Reduced demand for

fertilizer (F7)

Less demand for fertilizer 0.81

F8:1.1/5.1 Reduced demand for seed (F8) Less demand for seed 0.90



The goodness-of-fit-test was also conducted to

evaluate the model’s ability to predict farmers’

response to the future cultivation of GM crops, i.e.

the classification accuracy rate. The calculated

accuracy rate of 71% suggests that the responses to

the decision to cultivate GM crops in the future were

highly predicted. The comparable accuracy rate is

44.1%. The 44.1% is referred to as the proportional

by chance accuracy criteria. The proportional by

chance accuracy rate is calculated as the sum of the

square of the proportions in each GM response

group multiplied by 1.25 (i.e. (0.44572�0.28002�0.27432)�1.25), where 0.4457, 0.2800, and 0.2743

are the proportions of the respondents replying

‘‘yes,’’ ‘‘no,’’ or ‘‘neutral’’ to the cultivation of GM

crops. Operationally, this suggests that the classifica-

tion accuracy rate should be at least 25% (i.e. 1.25)

higher than the proportional by chance accuracy rate

(Schwab, 2003). The two tests described confirm

the reasonability of the estimated model.

Table V shows the estimated coefficients and the

corresponding t-statistic as well as the odds ratios of

the two regression equations for the likelihood of

farmers responding yes or being neutral relative to

responding no to the cultivation of GM crops.

Hence, the no response to the cultivation of GM

crops is the base to which the yes and the neutral

responses are compared. However, Table VI presents

the marginal effects of the independent variables on

the probability of responding yes, neutral, or no to

the cultivation of GM crops.

4.2.2. Farm characteristics and stated preferences. Table

V shows that farmers responding ‘‘yes’’ relative to

‘‘no’’ respondents and anticipating an increased

short-term profit (gross margin) of above 27 EUR

per hectare have a higher preference for adopting

GM technology. Their odds ratio of 15.6 suggests a

15.6 times increased likelihood of adopting GM

crops in the future compared to farmers stating that

there will be no change in profit.

4.2.3. Improved farm income. From the survey, the

potential increase in farm income for growing GM

crop is a major argument for accepting the technol-

ogy when farmers respond positive compared to

negative respondents. The same is the case for

farmers responding neutral to cultivation of GM

crops compared to negative respondents. As shown

in Table V, those GM positive and neutral farmers

are expressing their expectations for improved farm

income (F1) by affirming to: ‘‘GM technology holds

the potential for an improved gross margin,’’ ‘‘GM

crops will improve the environment,’’ ‘‘GM crops

will be useful in the future,’’ ‘‘GM crops provide the

potentials for simpler farm management,’’ ‘‘the GM

technology is itself exciting,’’ ‘‘it will increase product

sales price,’’ ‘‘it is important that GM crops improve

the yield,’’ ‘‘it is important that GM crops improve

the gross margin,’’ and ‘‘it will lead to reduction in

the use of input factors, i.e. herbicides, insecticides,

fungicides, and growth regulators.’’ Hence, these

farmers have 22.9 and 3.9 times higher likelihood

to adopt or remain neutral to GM crops compared to

farmers who declined to adopt GM crops in the

future. Examples of the expectations for improved

farm income are also illustrated in Figure 1.

In Figure 1, the upper half, farmers who are positive

toward the cultivation of GM crops suggested that

improvement in yield and gross margin, respectively,

are important for adopting GM crops account for

87% and 92%, respectively. The similar distributions

for the 48 farmers responding neutral to the cultiva-

tion of GM crops are 71% and 75%, respectively.

Even among the 49 farmers responding negative to

adoption, more than 25% agreed that it is important

with an improvement in yield and gross margin as a

source of motivation for adopting GM crops.

From the survey data, yes and neutral respondents

agreed that the cultivation of GM crops holds

potential for improvement in profits and simpler

farm management. The distribution of responses

suggested that 78% and 64% of ‘‘yes,’’ and 54% and

48% of ‘‘neutral’’ farmers pointed to the importance

of profits and simpler farm management, respec-

tively. The corresponding percentages for farmers

responding ‘‘no’’ are 18 and 24%. However, as

shown in Figure 1 (lower half), the responses are

less optimistic for price increases for GM crops.

Figure 1 (lower half, first bars) shows that only 15%

of the ‘‘yes’’ farmers responded affirmatively to the

increase in sales price of GM crops, but 53% of these

farmers responded affirmatively to the reduction in

the use of inputs. Similar percentages for ‘‘neutral’’

farmers are 13% and 46%, respectively. Hence, it is

suggested that the improvement in profit should

originate from the reduction in the use of inputs.

4.2.4. GM crop risk and resistance. Table V shows that

the likelihood of farmers cultivating GM crops does

not depend on the risk and resistance perceptions

(i.e. F2) when positive as well as neutral farmers

are compared to farmers responding negative to

the cultivation of GM crops. This suggests that the

relative distribution of farmers replying to the

statements comprising F2 in Table IV ‘‘It is im-

portant that the risk of gene dispersal from GM

crops to neighboring fields is minimal,’’ ‘‘It is

important to distinctly label GM products,’’ ‘‘It is

important that there is no health risk associated with



Table V. Results of the multinomial logit regression analysis with no respondents as base.

Estimates of yes relative to no Estimates of neutral relative to no

Independent variables df Estimate SE

Chi-

square P-wald OR LCI UCI Estimate SE

Chi-

square P-wald OR LCI UCI

Farmer age groups (years)

20�40 � � � � 1.00 � � � � � � 1.00 � ��40�50 1 1.3156 1.14 1.34 0.247 3.73 0.40 34.5 �0.2374 1.05 0.05 0.821 0.79 0.10 6.1

�50�60 1 0.4421 0.96 0.21 0.644 1.56 0.24 10.1 0.4551 0.85 0.29 0.591 1.58 0.30 8.3

�60 1 �1.1574 1.01 1.32 0.250 0.31 0.04 2.3 �0.1656 0.87 0.04 0.850 0.85 0.15 4.7

Farm size (ha)

580 � � � � 1.00 � � � � 1.00 � ��80�120 1 0.9475 1.00 0.90 0.342 2.58 0.37 18.2 0.0714 0.81 0.01 0.930 1.07 0.22 5.2

�120 1 1.7202 0.88 3.84 0.050 5.59 1.00 31.2 0.1339 0.76 0.03 0.860 1.14 0.26 5.1


0 � � � � 1.00 � � � � 1.00 � ��0�27 1 1.0161 1.42 0.51 0.475 2.76 0.17 44.9 1.8611 1.33 1.96 0.162 6.43 0.47 87.3

�27�81 1 2.7507 0.91 9.21 0.002 15.65 2.65 92.5 1.1734 0.81 2.08 0.150 3.23 0.66 16.0

Factor from the 30-item statements

Of which from the 18-item Likert responses

Improved farm income

(F1)

1 3.1317 0.62 25.36 0.000 22.91 6.77 77.5 1.3614 0.37 13.27 0.000 3.90 1.88 8.1

Risk and resistance (F2) 1 0.3443 0.53 0.42 0.515 1.41 0.50 4.0 �0.4448 0.24 3.31 0.069 0.64 0.40 1.0

Of which from the 12-item dummy responses

Chemical plant protection

inputs (F3)

1 1.0487 0.39 7.09 0.008 2.85 1.32 6.2 0.5325 0.31 3.02 0.082 1.70 0.93 3.1

High seed cost and low

crop price (F4)

1 0.9972 0.40 6.11 0.013 2.71 1.23 6.0 0.8173 0.37 4.89 0.027 2.26 1.10 4.7

Deteriorating biodiversity

(F5)

1 �0.9952 0.39 6.40 0.011 0.37 0.17 0.8 �0.3478 0.33 1.10 0.294 0.71 0.37 1.4

Health hazard (F6) 1 �0.7539 0.35 4.60 0.032 0.47 0.24 0.9 �0.0537 0.27 0.04 0.840 0.95 0.56 1.6

Reduced demand for

fertilizer (F7)

1 0.5435 0.38 2.10 0.148 1.72 0.83 3.6 0.2818 0.34 0.70 0.404 1.33 0.68 2.6

Reduced demand for seed

(F8)

1 �0.8429 0.36 5.50 0.019 0.43 0.21 0.9 �0.6383 0.31 4.32 0.038 0.53 0.29 1.0

Constant 1 �1.3876 0.98 1.99 0.158 � � � 0.4776 0.82 0.34 0.558 � � �

Note: df, degrees of freedom; SE, standard error; OR, odds ratio; LCI, lower confidence interval; UCI, upper confidence interval.

Farm

ers’percep

tions

ofgen

etically

mod

ifiedcrop

s111


Table VI. Multinomial logit marginal effect estimates of the attitude toward future cultivation of GM crops.

Partial derivative of probability of responding

Yes Neutral No

With respect to: Estimate SE T-stats p-Value Estimate SE T-stats p-Value Estimate SE T-stats p-Value Mean

Farmer age group (years)

20�40 � � � � � � � � � � � � ��40�50 0.3324 0.18 1.87 0.061 �0.2827 0.17 �1.62 0.105 �0.0497 0.13 �0.38 0.706 0.26

�50�60 0.0209 0.14 0.15 0.884 0.0387 0.14 0.27 0.787 �0.0595 0.11 �0.54 0.591 0.27

�60 �0.2288 0.15 �1.51 0.132 0.1551 0.15 1.02 0.307 0.0737 0.12 0.64 0.523 0.25

Farm size (ha)

580 � � � � � � � � � � � � ��80�120 0.1983 0.17 1.15 0.249 �0.1430 0.16 �0.87 0.383 �0.0552 0.11 �0.52 0.606 0.15

�120 0.3592 0.14 2.64 0.008 �0.2586 0.13 �1.92 0.055 �0.1006 0.10 �0.99 0.321 0.43


0 � � � � � � � � � � � � ��0�27 �0.0904 0.16 �0.56 0.578 0.2926 0.17 1.70 0.089 �0.2022 0.17 �1.17 0.242 0.10

�27�81 0.4115 0.14 2.97 0.003 �0.1738 0.14 �1.23 0.219 �0.2377 0.10 �2.38 0.017 0.36

Factors from the 30-item statements

Of which from the 18-item Likert responses

Improved farm income (F1) 0.4641 0.09 5.19 0.000 �0.1915 0.09 �2.10 0.036 �0.2726 0.08 �3.38 0.001 0.00

Risk and resistance (F2) 0.1520 0.10 1.50 0.134 �0.1696 0.09 �1.98 0.048 0.0176 0.04 0.49 0.624 0.00

Of which from the 12-item dummy responses

Chemical plant protection inputs (F3) 0.1424 0.06 2.25 0.025 �0.0450 0.06 �0.74 0.457 �0.0974 0.04 �2.24 0.025 0.00

High seed cost and low crop price (F4) 0.0826 0.05 1.63 0.103 0.0349 0.05 0.65 0.517 �0.1175 0.05 �2.41 0.016 0.00

Deteriorating biodiversity (F5) �0.1619 0.06 �2.57 0.010 0.0821 0.06 1.35 0.177 0.0798 0.04 1.85 0.065 0.00

Health hazard (F6) �0.1583 0.06 �2.45 0.014 0.1146 0.06 1.87 0.062 0.0437 0.04 1.21 0.225 0.00

Reduced demand for fertilizer (F7) 0.0728 0.05 1.36 0.175 �0.0219 0.05 �0.40 0.687 �0.0510 0.04 �1.17 0.243 0.00

Reduced demand for seed (F8) �0.0788 0.06 �1.40 0.162 �0.0164 0.06 �0.29 0.772 0.0952 0.04 2.26 0.024 0.00

Constant �0.3892 0.15 �2.59 0.010 0.3549 0.15 2.30 0.021 0.0342 0.11 0.31 0.753 �

Note: df, degrees of freedom; SE, standard error; OR, odds ratio; LCI, lower confidence interval; UCI, upper confidence interval.

112

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the GM,’’ ‘‘It is important that GM crops do not

have an effect on the surrounding environment,’’ ‘‘It

is important that GM crops are resistant to insects,’’

‘‘It is important that GM crops are resistant to

fungi,’’ and ‘‘It is important to maintain/improve the

biological diversity’’ turn out to be equal with regard

to the attitude toward the future cultivation of GM

crops. The survey data suggested that over 90%

of GM positive and neutral farmers, as well as 80%

of GM negative farmers, expressed the need that

no health risks as well as no environmental effects

should be associated with the cultivation of GM

crop. Similar percentages for insect and fungi

resistances are over 65% and 55%, respectively.

These characteristics are typical for first generation

GM crops and underline that the prime benefits

perceived by the farmers are reduced crop inputs.

A clearer picture of the impact of the replies to these

statements on the attitude toward future cultivation

of GM crops is provided in Table VI (see later).

4.2.5. Reduced demand for chemical plant protection

inputs. Farmers who respond affirmatively to culti-

vate GM crops and anticipate a reduction in the use

of insecticides, fungicides, herbicides, and growth

regulators (F3, four items of the 12-item dummy

responses) are 2.85 times more likely to adopt GM

crops compared to farmers responding no (see odds

ratio column, Table V). However, there is no

difference when farmers who responded neutral

are compared to the no respondents. It is noted

that most farmers tend to believe that the cultiva-

tion of GM crops will reduce the chemical plant

protection inputs although the number is fewer for

farmers responding negative to the cultivation of

GM crops.

4.2.6. High seed cost and low crop price. The weighted

factor scores representing the high cost of GM seed

and the low price for GM crops (i.e. F4, 2-items of

the 12-item dummy responses) increase with the logs

of the ratio of probabilities of both positive and

neutral to no respondents by 2.7 and 2.3, respec-

tively (odds ratio column, Table V). This suggests

that the impact of the factor is higher for affirmative

and neutral farmers compared to the no respon-

dents.

4.2.7. Risk of deteriorating biological diversity and

health hazards. As shown in Table V, if the risk of

deteriorating biological diversity (i.e. F5) increases

the odds for adopting GM crops will decrease by 63%

(1�0.37) for yes farmers compared to no respondents.

Similarly, a unit increase in the factor weighted scores

for health hazard (F6) decreases the odds for cultivat-

ing GM crops by 53% (1�0.47) for positive com-

pared to no respondent farmers. However, for the

two factors, there are no differences when farmers

It is important that GM improves the yield

0

20

40

60

80

100

Attitude towards GM

It is important that GM improves the gross margin

0

20

40

60

80

100

Attitude towards GM

The price of GM crops will increase

0

20

40

60

80

100

Attitude towards GM

Agree Either or Disagree No answer

GM crops will reduce input factors

0

20

40

60

80

100

Yes Neutral No Yes Neutral No

Yes Neutral No Yes Neutral No

Attitude towards GM

Agree Either or Disagree No answer

Figure 1. Attitude toward GM crops by 78, 49, and 48 farmers responding yes, no, or neutral, respectively.



respond neutral compared to those farmers who

respond negative to future adoption of the GM crops.

4.2.8. Reduced demand for fertilizer and seed. Table V

shows that the weighted factor scores for the

anticipated reduction in the demand for fertilizer

(F7, 1-item of the 12-item dummy responses) do not

have a significant effect on the likelihood to cultivate

GM crops in the future. Hence, the survey data

showed 18, 10, and 8% of yes, neutral, and no

respondents suggesting that the use of fertilizer

will decrease. However, Table V shows that the

weighted factor scores for the anticipated reduction

in the demand for GM seed (F8) suggest that

the odds for cultivating GM crops decrease by

57% (1�0.43) when comparing positive to negative

respondent. For neutral respondents compared to

farmers responding no the decrease in odds for

cultivating GM crops is 47% (1�0.53).

4.3. Marginal effects

The relative interpretations of results, as above,

reflect the impact of changes in the independent

variables on the logit. Hence, the estimates do not

imply anything about the magnitude and direction of

effects on the attitude toward the cultivation of GM

crops caused by changes in the explanatory variables.

From Equation (8), the estimated marginal effects

for an apparent effect, i.e. the partial derivatives of

the probability of responding yes, neutral, or no with

respect to the independent variables estimated from

the average values, are reported in Table VI.

4.3.1. Farm characteristics and stated preferences. Table

VI shows that the age of the farmer does not have a

significant impact on the attitude toward the cultiva-

tion of GM crops (at 5% significance level). How-

ever, at a moderate level of significance (pB0.10),

the marginal effect of being a farmer within the ages

of 40�50 increases the probability of cultivating GM

crops in the future by approximately 33% compared

to those younger than 40 years. For similar groups of

farmers (40�50 years) the probabilities of responding

neutral or no decreases by 28% and 5%, respectively,

although these marginal effects are not significantly

different from zero.

The marginal effect of farm size suggests that

being a farmer with more than 120 ha of farmland

compared to having less than 80 ha of farmland

increases the probability of responding yes to culti-

vating GM crops significantly by 36% (pB0.01).

While the probability of responding neutral or no

decreases by 26% (pB0.10) and 10% (pB0.32),

respectively.

For the marginal effect of the stated expected

profit, being a farmer with anticipated increased

profit of more than 27 EUR per ha compared to

zero expected profit increases the probability of

responding yes to the cultivation of GM crops by

41% (pB0.01). While the probability of responding

no or neutral decreases by 24% (pB0.05) and 17%

(pB0.22), respectively.

4.3.2. Weighted factor scores. For the eight weighted

factor scores estimated from the 30-item statements,

marginal effects of the use of fertilizer on the attitude

toward the cultivation of GM crops are not signifi-

cantly different from zero (Table VI, F7).

Specifically, Table VI shows that a unit increase in

the weighted factor score for improved farm income

(F1) increases the probability of responding yes to

the cultivation of GM crops by 46% (pB0.0001).

While the probability of responding no or being

neutral decreases by 27% (pB0.001) and 19%

(pB0.05), respectively. This suggests that state-

ments reflecting improved farm income are strong

motivations for the choice farmers make relative to

adopting GM crops. For the marginal effects of the

statements reflecting increased risks and resistance

issues (F2), a unit increase in the weighted factor

score of these statements reduces the probability of

responding neutral to the cultivation of GM crops by

17% (pB0.05). The marginal effects of these state-

ments on responding yes or no are not significantly

different from zero.

For the marginal effects of farmers’ responses

reflecting anticipated reduction in the use of chemi-

cal plant protection inputs (F3), a unit increase in

their weighted factor score increases the probability

of responding yes by 14% (pB0.05) or decreases the

probability of responding no to cultivating GM crops

by 10% (pB0.05). Negative farmers indicating that

low crop price and high seed cost (F4) will make

them refrain from the cultivation of GM crops will

only do so 88% (100�12%) of the time (pB0.05).

This suggests that the factor is of less importance to

respondents replying ‘‘no’’ to the cultivation of GM

crops. The marginal effect of the risk of deteriorated

biological diversity for the yes group will decrease

the probability of adopting GM crops by 16%

(pB0.05). But the probability of non-adoption is

increased by 8% (pB0.10). Similarly, the marginal

effect of health hazard is to decrease the probability

of adopting the cultivation of GM crops by 16%

(pB0.05) and increase the probability of being

neutral to the cultivation of GM crops by 11%

(pB0.10). Furthermore, Table VI shows that the

marginal effect of an anticipated reduction in the use

of GM seeds is the increase in probability of

responding ‘‘no’’ to the cultivation GM crops by



10% (pB0.05). This is contrary to our expectation

and is discussed in the discussion.

5. Discussion

The purpose of this study was to investigate what

factors underline farmers’ attitude toward accepting

GM crops. Based on the DIAS database, a ques-

tionnaire was forwarded to 400 farmers. The

response rate was 44%, which is approximately

12% less than reported in a Swedish case study,

which used a sample of 564 out of 1000 (Lehrman &

Johnson, 2008) but similar to the 44% (255/575)

reported by Breustedt et al. (2008) in the German

case study.

The distribution of the respondents by farm

characteristics reflected the representativeness of

the sample well. Of the 175 farms used in the

analysis, pig and cattle farms accounted for 63% of

the farms, crop farms for 31%, and the remaining

6% represent other farms. This distribution is

similar to the national distribution of farms in

2004 where the total number of farms was 45,525

of which pigs and cattle accounted for 61%, crop

farms for 32% with the remaining 7% representing

other farms (DST, 2008). With regards to the farm

size, the 175 farms were distributed such that 42, 15,

and 43% accounted for farms with less than 80 ha,

80�120 ha, and above 120 ha of farmland, respec-

tively. However, according to DST (2008), the

corresponding distribution for Denmark was 73%,

13%, and 14%, respectively, in 2004. Hence, our

distribution is biased toward large farms but this was

due to the desired stratification, i.e. to have an equal

number of farms below and above 100 ha of farm-

land. The decision to stratify as has been done was

based on the knowledge and expectation that farms

are getting larger in the future. Therefore, we believe

the data used in the analysis reasonably reflects the

farm structure in Denmark. Factor analysis was

applied to reduce the 30-item response statements

to eight-factor variables, which were utilized to

conduct the multinomial logit estimation and the

results used to estimate the marginal change effects.

5.1. Farm characteristics

In the present study, farm characteristics such as

farmers’ age and hectares under cultivation did not

reveal a clear significant relationship to the propen-

sity of growing GM crops when the relative compar-

ison with a base (‘‘no’’ responds) was evaluated

(Table V). However, the estimated marginal effects

reported in Table VI suggest otherwise. For the

variable ‘‘age,’’ the middle age farmers between the

ages of 40 and 50 years turn out to be moderately

more inclined toward adopting GM crops compared

to farmers of less than 40 years. The 40�50-year-old

farmers might benefit from their combined experi-

ence and formal agricultural education (Breustedt

et al., 2008; Lehrman & Johnson, 2008). The

German study by Breustedt et al. (2008), from a

choice set of 4731 responses, reported that older

farmers were less keen to adapt to the GM technol-

ogy. While the Swedish study by Lehrman and

Johnson (2008), with data from year 2005, reported

that age has no effect on the attitude toward the

cultivation of a GM insect resistant crop. In our

study, evaluating the direction of estimate for farm-

ers above 60 years, they are less likely to adopt GM

crops compared to those less than 40 years (although

the estimate is not significant). It is, however, noted

that due to the high investment cost of establishing a

farm business the younger generation of farmers in

Denmark, who are less than 30 years old, were not

well represented in the present study. The attitude of

the future farm owners among students at farm

colleges may provide useful insights. In the case of

the variable ‘‘farm size’’ in hectares, the estimated

marginal effects in Table VI suggest that large farms

are more inclined to adopt the cultivation of GM

crops in the future compared to small farms. This

finding is consistent with those reported by Breus-

tedt et al. (2008) and Lehrman and Johnson (2008).

5.2. Improving farm income

It is clear from the survey that the potential increase

in farm income from GM crops is a major argument

for accepting the technology. Farmers who expect an

improvement in gross margin by more than 27 EUR

per ha is by far more likely to adopt GM crops on

their farms. This is in line with the studies conducted

when the GM technology was first introduced in the

USA, although under different agricultural policy

contexts than in Europe (Duffy, 1999; Fernandez-

Cornejo & McBride, 2000; Fernandez-Cornejo &

Caswell, 2006). Similarly, our results are consistent

with the studies conducted in Europe (Breustedt

et al., 2008; Lehrman & Johnson, 2008). Most of the

USA studies were conducted after the GM crops

have been introduced on farms while this study and

the other European studies are based on farmers’

expectations. The improved profitability of the

farming business expressed by the Likert responses

(9-items from the 18-items) is thought of in terms of:

Simpler management for higher yields, less demand for

chemical inputs, which benefits the environment and

should lead to improved gross margin, hence an exciting

technology that may be useful for the future. It is noted,

following Lassen et al. (2007), that possible environ-

mental benefits from GM crops are recognized



although benefits for the farmers are mainly thought

of in monetary terms. Farmers, although they may

wish for it, mainly have little faith in higher prices for

GM crops. Hence, it is suggested that economic

benefits to the farmers is perceived to come from

reduced use of inputs.

The economic benefits from GM crops may,

however, not be as straight forward as farmers tend

to believe. In an overview of the literature reflecting

the post-cultivation experiences regarding farmers

decision-making toward GM crops, Alexander

(2006) concludes that adopters of GM crops in

the USA do not significantly earn more profit than

non-GM adopters. According to Fernandez-Cornejo

and Caswell (2006), the use of herbicide tolerant

cotton and herbicide tolerant corn have been asso-

ciated with increased net return, but the corn area

has been limited and grown on areas of special

advantage for the trait. Fernandez-Cornejo and

Caswell (2006) also suggested that the positive

return from the GM corn may be caused by lower

prices for the seeds as part of a marketing strategy for

the crop.

Of further interest, the rapid adoption of the GM

soybean in the USA may not be explained by

increased gross margins. In the first years (1997�1998) of adoption of GM crops among the US

farmers there were no increased net return reported

for GM soybeans (Fernandez-Cornejo & Caswell,

2006). It appears that other factors have driven this

development. Carpenter and Gianessi (1999) state

that by most accounts, the popularity of Roundup

ready soybeans is primarily due to the simplicity and

flexibility of a weed control program that provides

broad spectrum weed control (Carpenter & Gianessi,

1999).

Fernandez-Cornejo (2005) stated in his study that

the adoption of herbicide tolerant soybeans did not

have a significant economic impact on farm earnings.

It did however have an impact on the household

economy because of the simplicity and flexibility of

the technology. Farmers were now able to make

money from off-farm activities. This is presented as

a plausible explanation for the impressive growth

rates in the area cultivated with GM soybean.

5.3. GM crop risks and resistance

The GM crop labeling, which reflects farmers con-

cern for the risk associated with the consumers,

especially in the European population, could suggest

that some farmers would be less in favor of GM crops.

Products of animals fed with GM crops do not have to

be labeled whereas crops for human consumption by

law have to be labeled (EU, 2003). The latter could

prevent some producers from accepting a GM variety.

Likewise processing units could request suppliers to

refrain from using GM feed in their animal produc-

tion. In contrast, animal farmers could consider GM

crops as a necessity in order to obtain cheap feed for

the livestock and compete on the international

markets. In the present study the relative comparisons

of ‘‘yes to no’’ and ‘‘neutral to no’’ for risks and

resistance did not show any difference in the attitude

of farmers. However, the estimated marginal effect

suggests that if risk and resistance issues are mini-

mized, quite a number of indecisive farmers would be

positive toward adoption. Hence, for non-decisive

Danish farmers, a risk of unintended gene dispersal

and health risks reduced the propensity to grow GM

crops. In the German case study by Breustedt et al.

(2008), the willingness to grow GM rapeseed was

reduced out of fear of possible liability from GM gene

dispersal. Denmark has in contrary to other Eur-

opean countries a mandatory insurance scheme

compensating the non-GM grower in case of con-

tamination. The hesitance related to cultivating GM

crops because of gene spreading is thus hardly related

strictly to concerns of economic liability.

5.4. Reduced chemical plant protection inputs

From the survey it is clear that GM positive farmers

expect reduction in the use of herbicides, insecti-

cides, as well as growth regulators which underlines

the fact that farmers are focusing on first generation

GM crops (Killicoat, 2004) and further underlines

the fact that economic benefits are thought of as

reduced inputs. The fact that 10% of the negative

farmers (Table VI) also agreed that a reduction in

the use of chemical inputs will encourage them to

refrain from being negative suggests that this group

have deeper reservations about the technology,

which may have to receive more attention.

5.5. Risk of deteriorating biological diversity and health

hazard

The issues of deteriorating biological diversity and

health risk of direct concern to the farmers may

strongly influence their adoption decision. Farmers

responding affirmatively to the cultivation of GM

crops will refrain from adopting it. This is consistent

with Lehrman and Johnson (2008) who reported

that the risk of potential harm to other organism and

the potential of genes spreading to non-GM crop

varieties or wildlife relatives were frequently named

as negative consequences. They further reported

that positive farmers were more likely to see the

benefits of reduced health risks for themselves

compared to neutral or negative farmers.



5.6. Reduced demand for fertilizer and seeds

First generation GM crops do not offer reductions

in fertilizers (F7) and the quantity needed of seeds

(F8). This is in line with the survey data, which

shows that only a few farmers have stated that GM

crops will reduce these inputs but that demand will

remain the same. However, the direction of and the

significance of estimated coefficients for reduced

demand for seeds suggest that the probability of

negative farmers will increase even though they

expect a potential reduction in its use. This is

contrary to what should be expected, i.e. a reduction

in its use should encourage the negative farmers to

refrain from being negative. This showed to be the

case for the few respondents classified as being

negative. A stratified correlation analysis between

the weighted factor scores for the few farmers who

anticipate a reduction in the demand for seed and

predicted probability is as expected negative but

highly non-significant. For the majority, who are not

expecting a change in the demand for seeds, the

correlation is positive and highly non-significant.

Hence, the level of demand for seed may not have an

impact on the probability of the attitude toward GM

crops. Therefore, the 10% increase for ‘‘no’’ respon-

dents reflects the proportion that will consistently be

negative toward GM crop even though the demand

for seed is reduced.

Generally, our study confirmed the results from

other similar studies. However, a comparison of our

Danish and the Swedish studies revealed some

notable observations. The data for these two

studies were collected in 2004 and 2005, respec-

tively, but the concerns and hopes of the respon-

dent profiles (i.e. responding yes, no, or neutral)

turn out to be pointing in other directions. Firstly,

positive respondents in Denmark and Sweden made

up 45% and 13%, respectively, and the neutral

respondents were quite similar, i.e. 27% and 30%,

respectively. Secondly, a significant portion of the

28% negative Danish farmers might revise their

choice if income is improved and the use of

chemical plant inputs, herbicides, insecticide, fun-

gicides, and growth regulators are reduced. But the

57% negative Swedish relative to positive farmers

are more concerned about GM crops being danger-

ous for humans and livestock to consume and

mainly perceived no benefits from growing GM.

On the other hand, the positive Danish farmers are

additionally concerned about the environment,

health hazards, and the potential limitations posed

to biological diversity within the vicinity of their

farms. The positive Swedish farmers, however, were

concerned about potential problems with growing a

marketable crop and expensive seeds and the hope

of using fewer pesticides. The reasons for these

differences are not very clear to us and we leave

that for debate.

In the survey, some of the 12-item and the 18-item

statements were quite similar, which might pose some

problems for farmers when answering the questions.

However, it is noted that the applied PCA factor

analysis allocated these statements into different

factor score groups. This suggests that farmers were

somehow able to separate their responses.

6. Conclusion

The purpose of this study was to explore Danish

farmers’ perceptions of GM crops. The main con-

clusion from this survey is that farmers who are

positive toward growing GM crops are mainly driven

by a firm belief in positive economic gains from

improved yields and reduced cost of farming inputs.

This group of positive farmers (45% of the sample)

confirms Hillery’s hypothesis that a farmer will

adopt a new technology if it works and generates

income. This is well reflected by the observation that

more than a quarter of the farmers from the

indecisive or negative group may react positively

toward the new technology. Farmers who believe in

the economic benefits are likely to adopt GM crops.

Apart from the cost reductions, these benefits

include the indirect farm income expressed as the

benefit for the environment (which may be linked to

the control costs of leaching) and the future poten-

tials of the technology.

The farmers’ belief in improved gross margin from

GM crops is not strictly supported by the literature

review of post-adoption. Farm benefits may also be

related to simpler management, flexibility, and also

greater off-farm income. Thus, there seems to be a

discrepancy between farmers’ initial expectation to-

ward GM crops and the current reality. The relation-

ship between economic benefits and GM crops should

receive further attention by the EU farmers.

Health and environmental hazards directly related

to individual farms will induce the positive farmers

especially to refrain from adopting GM crops but

risk and resistance issues are of major concern for

indecisive farmers.

There are only few studies of European farmers’

perception of GM crops. However, their perceptions

and actions in relation to the technology might be

crucial for the future development of European

agriculture.

Acknowledgements

We wish to thank the two anonymous reviewers and

the editors for their useful comments.



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Documents

Perceptions of genetically modified crops among Danish farmers