Final Report on Consumer Preferences for Cloning

Submitted to:

U.S. Department of Agriculture

Economic Research Service

1800 M Street, NW

Washington, DC 20036-5831

Submitted by: Jayson L. Lusk

Professor and Willard Sparks Endowed Chair

Department of Agricultural Economics

Oklahoma State University

Phone: (405)744-7465

Email: jayson.lusk@okstate.edu

Date:

October 1, 2008

Table of Contents

Content Page Executive Summary i

1. Introduction 1

2. Previous Research on Consumer Acceptance of Cloning 2

3. Study Objectives 3

4. Methods and Procedures 3

4.1 The Survey Samples 3

4.2 Experimental Treatment: Early Information 6

4.3 Experimental Treatment: Length of Information 6

4.4 The Survey and Statistical Methods 8

5. Results from the Randomly Recruited Sample 22

5.1 Awareness of Animal Cloning and Other Animal Breeding Techniques 22

5.2 Willingness to Eat Cloned Meat and Milk 22

5.3 Beliefs about Safety and Acceptability of Cloned Meat and Milk 23

5.4 Beliefs about Federal Government and Cloned Meat and Milk 23

5.5 Why Are People Concerned about Animal Cloning? 24

5.6 Preferences for Cloning Policies 27

5.7 Ground Beef Market Simulator 28

5.7 Milk Market Simulator 29

6. Comparing Results across Three Survey Samples 31

6.1 Sample Characteristics 31

6.2 Food Values 31

6.3 Awareness of Animal Cloning and Other Animal Breeding Techniques 32

6.4 Willingness to Eat Cloned Meat and Milk 32

6.5 Beliefs about Safety and Acceptability of Cloned Meat and Milk 33

6.6 Beliefs about Federal Government and Cloned Meat and Milk 33

6.7 Relative Importance of Competing Objections to Cloning 33

6.8 Relationship between Milk/Meat Purchases and 34

Willingness to Eat Cloned Food

6.9 Preferences for Cloning Policies 35

6.10 Ground Beef Choice-Based Conjoint Estimates 36

6.11 Milk Choice-Based Conjoint Estimates 36

7. Conclusions 37

8. References 39

9. Tables and Figures 41

i

Executive Summary

In the summer of 2008, three surveys were administered to over 6,000 U.S. consumers to gauge

the public‟s attitude toward the use of cloning in meat and milk production. One survey was

administered to a true probability-based random sample of 2,256 people, and two other surveys

were administered to “opt in” panels of consumers for which actual meat and milk purchase

behavior was known. A variety of survey methods and statistical techniques were used to

provide a comprehensive investigation of people‟s preferences for animal cloning. Unless

otherwise noted the results reported in the executive summary are from the probability-based

random sample. Key results from the study are as follows:

As compared to other assisted reproductive technologies, such as artificial insemination

and biotechnology, people have a higher level of awareness of animal cloning.

Providing people a week to digest information about cloning versus providing

information only at the time the survey was taken had virtually no impact on people‟s

attitudes toward cloning.

People provided a one-half page information statement about cloning including the

FDA‟s statement about the safety of cloned meat and milk, are somewhat less concerned

about cloning as compared to people who only received a two sentence definition of

cloning. For example, 32% of people from the true probability-based random sample that

were provided the lengthy information indicated that animal cloning was unacceptable,

whereas 40% respondents in one of the opt-in panels that were only provided a two

sentence definition indicated that animal cloning was unacceptable.

Attitudes toward cloning are neither overwhelmingly positive nor negative. About 31%

are willing to eat meat and drink milk from a cloned animal, about 43% are unwilling,

and 26% are neither willing nor unwilling. About 32% of the public believes animal

cloning is unacceptable, about 34% believes animal cloning is acceptable, and the

remaining 34% is neutral.

There is virtually no difference in people‟s willingness to drink cloned milk and eat

cloned meat. Furthermore, there is virtually no difference in people‟s willingness to eat

milk/meat from cloned animals and milk/meat from the offspring of cloned animals.

Although 64% believe that the meat and milk they buy is safe to eat, only 30% think the

U.S. government is doing everything it can to ensure the safety of food.

Less than 30% expressed trust in information about cloning from U.S. federal agencies.

People were relatively more trusting of information on cloning from University scientists,

the USDA, the FDA, and then the EPA.

Females and those with only a high school education are less supportive of eating

meat/milk from cloned animals than are males and those with a bachelor‟s degree or

higher level of education.

Actual purchase behavior, determined via at-home scans of grocery purchases, is related

to people‟s stated willingness to eat meat/milk from cloned animals obtained from the

opt-in panels. People who tend to primarily buy organic milk are significantly less

willing to drinking milk from cloned animals and are willing to pay more for “clone free”

milk than people who tend to primarily purchase non-organic milk. People who buy few

ii

packages of fresh beef throughout the year are less willing to eat meat from cloned

animals than people who are frequent purchasers of beef.

Of eight potential objections to cloning, the two most prominent are: (i) “cloning is

“unnatural” because it is not a process that occurs in nature” and (ii) “animal cloning will

lead to human cloning.” People are relatively unconcerned about the safety of eating

meat/milk from cloned animals or their offspring.

Although people are willing to pay relatively large premiums for non-cloned meat and

milk when grocery shopping (about $4 per purchase), this does not necessarily translate

into high willingness-to-pay for policies related to cloning. People did not support bans;

results from all three survey samples imply that willingness-to-pay for a ban on animal

cloning is effectively zero. There is mixed support for a policy related to mandatory

tracking of cloned animals; people provided lengthier information on animal cloning are

willing to pay much smaller amounts than people only given a two-sentence definition.

A majority of people in all three samples support a mandatory labeling policy on cloned

meat/milk, even if it causes a food price increase of 30%.

People‟s choices were used to construct a market simulator for fresh ground beef and a

market simulator for unflavored fluid milk. The simulators can be used to forecast

market shares of and willingness-to-pay for ground beef and milk options that differ

according to a variety of user-defined product characteristics including price, fat content,

and use of cloning. The market simulators can be accessed at:

http://agecon.okstate.edu/faculty/publications/3103.xls and

http://agecon.okstate.edu/faculty/publications/3104.xls. Market share simulations

indicate: o When faced with a choice between ground beef from a cloned and a non-cloned

animal, more than 75% of shoppers would choose the non-cloned beef even if

sold at a $1.50 price premium over ground beef from a cloned animal. o When faced with a choice between milk from a cloned and a non-cloned animal,

more than 65% of shoppers would choose the non-cloned milk even if sold at a

$1.50 price premium over milk from a cloned animal. o If faced with a choice of only being able to buy ground beef from a cloned animal

or no ground beef at all, the majority of consumers would choose to buy cloned

beef (assuming the price of ground beef was $3.50/lb or lower). At a price of

$2.00/lb., almost two-thirds of shoppers would buy ground beef from a cloned

animal if it were the only option available. o If faced with a choice of only being able to buy milk from a cloned animal at

$3.00/gallon or no milk at all, only about 47% of consumers would choose to buy

the milk from the cloned animal. o Although consumers are concerned about other product attributes, such as fat

content, price, and use of rBST, use of animal cloning is the most important

attribute to consumers.

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1. Introduction

Farmers and ranchers have utilized assisted reproductive techniques for decades with little

controversy. For example, commercial embryo transfers have occurred in dairy and beef cattle

since the 1970‟s. Nevertheless, the relatively new reproductive technique of animal cloning has

sparked controversy. Animal cloning is a process by which scientists can copy the genetic or

inherited traits of an animal. Clones are similar to identical twins only born at different times.

Like other assisted reproductive breeding techniques, cloning is appealing to some ranchers and

farmers because it enables them to more quickly breed desirable traits into their herds. Such

improvements have the potential to lower the price and increase the quality of meat and milk

products. Despite these advantages, some consumer groups have expressed concern and even

outrage over the use of meat and milk from cloned animals and their offspring. The controversy

over cloning stems from moral and ethical objections to the technology, concerns about food

safety, and concerns about potential harm to the cloned animals and their surrogate mothers.

In January 2008, after years of detailed study and analysis, the U.S. Food and Drug

Administration (FDA) concluded that, “meat and milk from clones of cattle, swine, and goats,

and the offspring of clones from any species traditionally consumed as food, are as safe to eat as

food from conventionally bred animals.” The FDA‟s science-based risk assessment, which was

peer-reviewed by a group of independent scientific experts in cloning and animal health,

concluded:

1. Cloning poses no unique risks to animal health compared to the risks found with other

reproduction methods including natural mating.

2. The composition of food products from cattle, swine, and goat clones, or the offspring

of any animal clones, is no different from that of conventionally bred animals.

3. Because of the preceding two conclusions, there are no additional risks to people

eating food from cattle, swine, and goat clones or the offspring of any animal clones

traditionally consumed as food.

A copy of FDA‟s report can be found at: http://www.fda.govcvm/cloning.htm.

Despite this news, many consumers appear to be either unaware of the technology or find the

technology unacceptable. As such, important questions exist regarding consumer reaction to and

the market impacts of the presence of cloned meat and milk in the food supply chain. Indeed, in

late 2007 the U.S. Senate passed legislation intended to prohibit the FDA from approving cloned

products until further research is conducted.

These developments suggest the need for an in-depth study of consumer attitudes toward cloning.

For example, at present it is difficult to precisely identify consumers‟ potential objections to the

technology, but such information is needed to forecast how demand for meat and milk from

cloned animals will develop and respond to information and advertising campaigns. Further, it is

unclear whether, to what extent, and under what conditions consumers are willing to accept the

new technology. For example, how much lower priced or higher quality must cloned meat and

milk be to remain competitive with non-cloned meat and milk? Does the public desire stronger

regulation on the practice of animal cloning? Answering such questions with existing market

data is impossible, and as such, a consumer survey is needed to address these issues.

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2. Previous Research on Consumer Acceptance of Cloning

Some previous opinion polls have been conducted on the issue of animal cloning, and in what

follows, some of the previous findings are briefly summarized. In a 2005 survey, Sosin and

Richards (2005) reported that 29% of consumers surveyed believed that animal cloning is

currently used by farmers and ranchers to breed animals whereas 64% believed that it would be

used in the future. Storey (2006) reported that about 50% of consumers surveyed believed that

use of animal cloning to breed animals for meat and milk production is possible. The survey

found that 73% of consumers had not heard about the FDA issuing a report on the use of animal

cloning to breed animals for meat and milk. A study conducted for the Pew Initiative on Food

and Biotechnology in 2004 found that about 65% of consumers had heard about animal cloning

(The Mellman Group, 2006).

The Pew study found that 29% of consumers indicated that they would purchase meat and milk

from the offspring of cloned animals, but 35% indicated that they would never buy meat and

33% would never buy milk from the offspring of cloned animals. This is similar to the study

conducted in 2006 by the International Food Information Council. IFIC (2006), which found that

about 41% of consumers said they would purchase meat, milk, or eggs from the offspring of

cloned animals. IFIC found that this latter figure increased slightly to 46% in 2007. Storey

(2006) found that approximately 33% of consumers indicated they would continue to purchase

meat and milk products if they came from cloned animals or their offspring.

Although these opinion polls indicate most consumers have heard about animal cloning, they are

somewhat uncomfortable with the technology. Storey (2006) found 32% of consumers felt

animal cloning was morally wrong and 26% were unsure of the safety of meat and milk from

clones and their offspring. The KRC Research study found that consumers found cloning more

acceptable if it improved the overall health of animals, improved nutrition of meat and milk, and

saved rare animal breeds (Sosin and Richards, 2005). The study also found that consumers are

more comfortable with animal cloning when told that it is carefully regulated by the FDA, the

USDA, and the EPA. Consumers are most likely to trust the USDA, FDA, veterinarians, and

physicians when it comes to animal cloning (Sosin and Richards, 2005). Consumers are less

likely to trust groups like the Consumer Federation of America and The Sierra Club when it

comes to animal cloning (Sosin and Richards, 2005).

Most of these previous opinion polls simply asked people to indicate purchase intentions or

attitudes on a five-point scale. A wealth of evidence indicates such data often poorly predicts

actual retail behavior (Morrison, 1979; Morwitz, 1997). Furthermore, such scales do not force

people to make trade-offs between concerns, and as such, it is common for people to rate many

issues as “very important.” This research will utilize “best-worst” or paired comparison

questions to determine the relative degree of concern for cloning and to determine which issues

are most unacceptable to consumers (see Lusk and Briggeman (2008) for a recent use of these

methods in the agricultural economics literature). Furthermore, this research will utilize

contingent valuation and conjoint questions to determine consumers‟ trade-offs between

concerns for cloning, food prices, and food quality in a manner that will permit estimation of

willingness-to-pay, demand elasticities, and market shares.

3

3. Study Objectives

The primary objectives of this study are to:

1) determine consumer awareness of and attitudes toward cloned meat and milk,

2) determine whether consumers‟ preferences for cloned meat and milk are affected by the

length of time they are given to digest unbiased, educational information about the

technology,

3) explore whether consumers‟ preferences for cloned meat and milk are affected by the

length of information given about cloning,

4) determine the effect of survey sample (i.e., opt-in panels with food purchase data vs.

randomly recruited representative sample) on preference for cloning.

5) determine the relationship between people‟s actual purchases of meat and milk and their

stated level of concern for cloning,

6) determine consumer willingness-to-pay for several policies related to animal cloning,

7) determine the trade-offs consumers are willing to make between use of cloning in meat

and milk production and other food attributes such as price and quality, and

8) develop market simulators to forecast market share and willingness-to-pay for ground

beef and milk products that differ according to a number of product characteristics

including use of cloning.

4. Methods and Procedures

4.1 The Survey Samples

A web-based survey was developed and administered by three sub-contractors, each of whom

utilize different recruitment methods and have their own relative advantages and disadvantages.

The first subcontractor, Knowledge Networks (KN) administered the survey to a sample that was

selected using random digit dialing techniques, and as such, represents a true probability sample

based on the general U.S. population. Although KN uses a web-based platform,

representativeness is ensured by providing randomly selected respondents with computers and

on-line access if they do not already have it. Although KN has the advantage of providing a true

probability based sample, they do not have data on consumers‟ actual food purchases. To

remedy this deficiency, identical surveys were administered by two additional sub-contractors,

Nielsen and IRI, which both maintain panels of consumers who record food purchasing history.

The advantage of these panels is that actual food purchases of the consumers are known, but the

disadvantage is that these panels are not true probability-based samples; they are comprised of

opt-in panels with people who volunteer to participate. By combining the results across all three

subcontractors, not only can it be determined whether sampling considerations affect results, but

a better and more in-depth picture of consumer preferences for cloning can be obtained.

It should be emphasized that because only KN uses a true random recruitment method, it is the

only sample which has a firm basis in statistically theory, and as such it is the only sample that

can legitimately be used to make inferences about the U.S. population at large. As such, we give

disproportionate attention to the results from the KN sample.

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Despite the preceding argument, it should be noted that a random sample of the U.S. population

is not the same thing a random sample of meat eaters or milk drinkers, and as such, it is

worthwhile to study preferences for cloning in the IRI and Nielsen samples and investigate how

such preferences for cloning relate to actual meat and milk purchases.

A key factor that needs to be considered when comparing results across the three survey samples

is that the samples may differ in terms of the characteristics of the people surveyed. As such,

observed differences in concern for cloning across survey samples may be a result of differences

in factors such as race, gender, education, etc. and not a result of opt-in vs. random panels per se.

As such, after each survey was conducted, we created sample-specific, post-stratification weights

to reduce the effects of non-response and non-coverage bias. This was accomplished by

comparing the geographic location and demographic characteristics (age, race, gender, and

education) of each sample to the most recent data from the U.S. Census Bureau, Current

Population Survey. Iterative proportional fitting techniques were used to create weights which,

when applied to the data, force the proportions in each sample to match the proportions in the

population – at least in terms of geographic location, age, race, gender, and education. These

post-stratification weights are used in all results presented in this report.

4.1.1 Probability-Based Sample: Knowledge Networks

The company Knowledge Networks (KN) was contracted to administer a web-based survey to

their panel of respondents. Their panel is the only existing online panel that is representative of

the U.S. population. Probability sampling is used to recruit participants, avoiding well known

problems with “opt in” panels. The Knowledge Networks panel is representative of the U.S.

population, and to ensure representativeness, members of the panel are randomly recruited by

telephone (using both listed and unlisted numbers) and are provided with access to the Internet if

the household does not have ready availability. Thus, the panel is comprised of both Internet and

non-Internet households, all of which are provided the same equipment for participation in

Internet surveys. More information on the panel, recruitment methodology, studies comparing

the Knowledge Network panel to other sampling techniques, and a bibliography of published

academic papers which have employed the Knowledge Network panel can be found at

http://www.knowledgenetworks.com/ganp/.

In June 2008, the survey was sent to 3,222 individuals, 2,256 of whom completed at least a

portion of the questions, implying a response rate of 70%. This sample size implies a sampling

error of about 2.06%. That is, we can be 95% confident that the sampled percentage of people

falling in a particular category is within ± 2.06% of the true percentage of people in the particular

category in population. Table 1 (and table 18) reports the raw (unweighted) and weighted means

for selected socio-economic and demographic variables describing the sample of people

surveyed. As can be seen, the raw (original) sample matched the U.S. population quite well, and

as such, there are only slight differences in the weighted and unweighted means. By

construction, the weighted means for age, gender, race, and education exactly match the U.S.

population means.

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4.1.2 Opt-In Panel with Scanner Data: Information Resources Inc

Information Resources Inc (IRI) was contracted to provide their so-called AttitudeLink™ panel

survey service, which enabled the linking of our survey with IRI‟s U.S. household panel, a group

of U.S. households who use a handheld scanner to report their bar-coded product purchases.

The IRI panel is designed to be demographically representative at the total U.S. In addition to

the answers to the survey questions, IRI is able to provide, for each household who completed a

survey, data on purchases of milk (organic and non-organic), breakfast meat, and lunch meat.

Importantly, these measures are not based on consumers‟ potentially unreliable memories of past

purchasing behavior, but instead represent actual purchase histories. IRI was unable to provide

data on purchases of fresh meat products because such products often to not have a bar code that

specifies package weight. IRI does not possess information on such “random weight” products.

In late June, early July 2008, the survey was sent to 4,000 individuals, 1,691 of whom completed

the survey questions, implying a response rate of 42.3%. This sample size implies a sampling

error of about 2.38%. That is, we can be 95% confident that the sampled percentage of people

falling in a particular category is within ± 2.38% of the true percentage of people in the particular

category in population. Table 18 reports the raw (unweighted) means for selected socio-

economic and demographic variables describing the sample of people surveyed and compares

them to the U.S. Census data. The IRI sample has a much lower level of education and has a

high share of females as compared to the U.S. population. By construction, after the weights are

applied to the data, then the sample proportions for the various age, gender, race, education, and

location categories exactly match the U.S. population proportions.

4.1.3 Opt-In Panel with Scanner Data: The Nielsen Company

Nielsen was contracted to administer the survey to their so-called Homescan panel. The

Homescan panel is comprised of households who “opt in” or volunteer to participate in the panel.

Panelists agree to scan the barcodes on their purchases and to occasionally complete surveys.

Although panelists “opt in,” Nielsen attempts to select volunteering households such that the

panel is representative of the U.S. population. In addition to answers to the survey questions,

Nielsen is able to provide, for each household who completed a survey, data on units purchased

for milk and beef. Because beef is a random weight item, we only know units purchased and not

the total pounds purchased. Like the IRI sample, this purchase data is not based on consumers‟

memories of past purchasing behavior, but instead represent actual purchase histories.

In late July and early August 2008, the survey was sent to 2,992 individuals, 2,120 of whom

completed the survey questions, implying a response rate of 70.9%. This sample size implies a

sampling error of about 2.13%. That is, we can be 95% confident that the sampled percentage of

people falling in a particular category is within ± 2.13% of the true percentage of people in the

particular category in population. Table 18 reports the raw (unweighted) means for selected

socio-economic and demographic variables describing the sample of people surveyed as

compared to the U.S. Census data. By construction, after the weights are applied to the data,

then the sample proportions for the various age, gender, race, education, and location categories

exactly match the U.S. population proportions.

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4.2 Experimental Treatment: Early Information

There are several concerns with asking people about their preferences for a new and

controversial technology for which they are likely unfamiliar, including: (i) people are unlikely

to provide well reasoned or consistent answers, (ii) people‟s responses may largely be driven by

a “shock value” or “gut reaction,” and (iii) people‟s answers may be unduly influenced or easily

swayed by the information presented. Because of these concerns, it is of interest to determine

whether giving people some period of time (one week in our case) between the provision of

information about cloning and the administration of the survey substantively influences behavior.

To investigate this issue, one half of the people in the KN sample were sent an email requesting

that they read a brief information statement about cloning. Participants were directed to a web

page, where they had to click a button to proceed. The “proceed” button was added in an attempt

to ensure the information was actually read by each participant. Then, one week later, the same

subjects were sent another email directing them to complete the survey. In the content of the

survey, the information was provided again. For the other half of the participants in the KN

sample, they only received the information at the time when they took the survey.

By comparing responses across these two treatments in the KN sample, we can identify whether

the early provision of information influenced people‟s attitudes toward cloned meat and milk.

Importantly, this is a test of the effect of the timing of information, not an effect of information

per se. All participants received the exact same information statement regardless of the

treatment to which they were randomly assigned. In the content of the survey, the information

was provided on the third screen; the only questions preceding the information statement were in

regards to people‟s knowledge and awareness of several animal breeding techniques including

cloning and questions aimed at measuring people‟s general food values.

4.3 Experimental Treatment: Length of Information

Because cloning is likely a topic unfamiliar to many survey respondents, people must be

provided some information. In developing an information statement, a difficult balance must be

struck between providing a concise yet informative discussion of the issues. People cannot be

expected to spend a great deal of time reading a wealth of information on the topic. For the KN

sample, we chose to construct an information statement by surveying the literature on cloning

and selecting the key issues (pro and con) to presented to subjects in as neutral a way as possible.

The information statement focused primarily on the information provided by the FDA because it

is a source most people would likely find credible and because it is information that has already

been widely disseminated in the press.

The precise information statement given to subjects in the KN and the Nielsen samples was:

Animal cloning is a process in which scientists can copy the genetic or inherited traits of

an animal. Clones are similar to identical twins only born at different times. Similar to in

vitro fertilization, cloned animals begin in a laboratory, but then are born to surrogate

mothers in the usual way and grow up just like other animals.

7

This reproductive breeding technique is appealing to some ranchers and farmers

because it enables them to create “identical twins” of their best breeding stock – allowing

them to more quickly breed desirable traits into herds. The technique is also appealing to

some consumers because it has the potential to lower the price and increase the quality of

meat and milk.

This reproductive breeding technique is opposed by some people on moral and

ethical grounds. Other people are opposed to animal cloning because, given current

technology, only a small percentage of attempts at cloning are successful and many of the

clones die during all stages of gestation and birth and the procedures may carry risks for

the mother. Although these symptoms are a downside to cloning, they are not necessarily

unique to cloning in comparison to other reproductive techniques.

In January 2008, after years of detailed study and analysis, the U.S. Food and

Drug Administration (FDA) concluded that, “meat and milk from clones of cattle, swine,

and goats, and the offspring of clones from any species traditionally consumed as food,

are as safe to eat as food from conventionally bred animals.” The FDA‟s science-based

risk assessment, which was peer-reviewed by a group of independent scientific experts in

cloning and animal health, concluded:

1. Cloning poses no unique risks to animal health compared to the risks found

with other reproduction methods including natural mating.

2. The composition of food products from cattle, swine, and goat clones, or the

offspring of any animal clones, is no different from that of conventionally

bred animals.

3. Because of the preceding two conclusions, there are no additional risks to

people eating food from cattle, swine, and goat clones or the offspring of any

animal clones traditionally consumed as food.

A copy of FDA‟s report can be found at: http://www.fda.gov/cvm/cloning.htm.

Recall that one-half the participants in the KN sample received this information statement one

week prior to taking the survey, and all KN participants, regardless of treatment, also received

the information statement in the third section of the survey.

Of course, there are some situations in which it would be desirable to utilize an even more

concise information statement. If the sole purpose of this project was to forecasting purchase

behavior, a very brief information statement would be appropriate as it would only give people

that information which they normally have when shopping. However, in the current context,

where inferences are being made about welfare effects of various policies and where elicited

values may be used in cost/benefit analysis or other policy-related analysis, then it is prudent that

people should reasonably informed prior to their attitudes/preferences being elicited. This view

is consistent with the standard recommendations on survey design for contingent valuation

including that of the “blue ribbon” NOAA panel (e.g., Arrow et al., 1993; Boyle, 2004). For this

reason, the true probability-based sample (the KN panel) was given the more complete

information statement shown above.

Recognizing the interest in how such information may affect behavior, we chose to present two

different information statements to the two “opt in” panels, IRI and Nielsen. For the Nielsen

panel we gave respondents, at the time of the survey, the exact information statement shown

8

above – the exact same statement shown to the KN sample. For the IRI sample, we restricted the

information statement to two sentences only providing definitional information. The precise

information statement given to subjects in the IRI sample was:

Animal cloning is a process in which scientists can copy the genetic or inherited traits of

an animal. Cloned animals are similar to identical twins only born at different times.

One question that might arise is whether the approach followed in this research can clearly

identify the effects of (i) early vs. simultaneous provision of information, (ii) long vs. short

information, and (iii) random vs. opt in recruitment method. Under the maintained assumption

that the Nielsen and IRI samples are essentially equivalent, the table below indicates that each of

these effects is indeed identified. Testing for the effect of early vs. simultaneous provision of

information involves a comparison of cell A. to cell B., which holds the recruitment method

constant at “random” and the information length constant at “long.” The effect of long vs. short

information can be tested by comparing cell C. to cell D., which holds the recruitment method

constant at “opt in” and timing of information constant at “simultaneous.” Finally, the effect of

random vs. opt in recruitment method can be tested by comparing cell B. to cell C., which holds

information constant at “long” and “simultaneous.”

Information

Recruitment Method Long,

Early

Long,

Simultaneous

Short,

Simultaneous

Random A. KN

sample 1

B. KN

sample 2

Opt in C. Nielsen

sample

D. IRI

sample

4.4 The Survey and Statistical Methods

As previously indicated, a web-based survey was developed. The survey consisted of nine

sections. Although the nine sections appeared in the same order for all surveys, individual items

within a section were randomly ordered across surveys to prevent an order effect. Except for the

differences in information described above, the surveys administered by all three subcontractors

were identical. What follows is a description of the questions asked in each survey section along

with details on statistical techniques employed to make use of the data.

4.4.1 Food Values

The first section of the survey was designed to measure people‟s general food values. Such

information is helpful in identifying why people find certain food technologies more or less

acceptable. The idea is to identify a set of a values that relate specifically to people‟s food

choices that are perhaps more stable than people‟s preference ranking of a specific set of foods or

food attributes such as cloning. Following Lusk and Briggeman (2008), we selected 11 food

values that are reasonably comprehensive in covering the breadth of issues likely to motivate

consumer food choice. The eleven food values and the associated descriptions are:

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1. Naturalness (extent to which food is produced without modern technologies)

2. Taste (extent to which consumption of the food is appealing to the senses)

3. Price (the price that is paid for the food)

4. Safety (extent to which consumption of food will not cause illness)

5. Convenience (ease with which food is cooked and/or consumed)

6. Nutrition (amount and type of fat, protein, vitamins, etc.)

7. Tradition (preserving traditional consumption patterns)

8. Origin (where the agricultural commodities were grown)

9. Fairness (the extent to which all parties involved in the production of the food equally

benefit)

10. Appearance (extent to which food looks appealing)

11. Environmental Impact (effect of food production on the environment)

Asking people to rate the importance of each food value on a 5-point or 7-point scale is

problematic because: (i) people are likely to rate several issues as “very important” because no

tradeoffs must be made and (ii) people do not always use measurement scales identically,

causing difficulties in inter-personal and cross-cultural comparisons (Steenkamp and

Baumgartner 1998). As such, we utilized a paired comparison approach, which has been popular

since its introduction by Thurstone‟s (1927) and has been increasing in popularity due to the rise

of “best-worst” scaling techniques, e.g., see Finn and Louviere (1992), Marley and Louviere

(2005), and Flynn et al. (2007). This approach permits the measurement of food values on a

ratio scale by observing people‟s choices of which values are picked as more important.

To implement the approach, people were asked eleven repeated questions of the form, “Is X or Y

more important when you purchase foods?,” where the two food issues X and Y were randomly

chosen from the list of 11 issues shown above. For example, one question might read, “Is

Naturalness (extent to which food is produced without modern technologies) or Taste (extent to

which consumption of the food is appealing to the senses) more important when you purchase

foods?”

In total, there are (11*11-11)/2=55 possible questions that that can be created by pairings of the

issues listed above. Each person randomly received 11 of these pairings and made discrete

choices of which values were deemed more important. When responding to each discrete choice

question, people can be conceptualized as choosing the item that is highest on an underlying

scale of importance. Formally, let αj represent the location of value j on the underlying scale of

importance, and let the true or latent unobserved level of importance for individual i be given by

Iij = αj + εij, where εij is a random error term. The probability that the consumer chooses, say,

item j over item k, as most important is the probability that Iij is greater than Iik. If the εij are

distributed iid type I extreme value, then this probability takes the familiar logit form.

In particular, in each choice set, an individual chose whether issue j or issue k was more

important. The probability that issue j is more important than issue k is:

(1) Prob[issue j is more important than issue k] = kj

j

ee

e

where αj and αk are parameters identifying the relative importance of issue j and issue k, and β is

an overall constant term that corresponds to an order effect (i.e., the propensity to choose the

10

food value presented first in the pairing). In a sample of N individuals making C choices, with

each choice involving a differing pairing of food values, the log-likelihood function is

(2) N

i

C

c

ijcijckj

k

kj

j

ee

ey

ee

eyLogL

1 1

ln)1(ln

where yijc = 1 if issue j is chosen by individual i as most important in choice set c, and where yijc

= 0 if issue k is chosen by individual i as most important in choice set c. In this framework, one

of the 11 parameters must be normalized to zero for identification purposes, and as such we

arbitrarily selected the value “environmental impact” and normalized the parameter to zero such

that the estimated effect of the other issues can be interpreted as the importance of the particular

value relative to the importance of environmental impact.

To ease interpretation and to provide a measurement of the importance of food values on a ratio

scale, the parameters obtained from equation (2) are substituted into the multinomial logit

formula to calculate “shares of preference” or “importance scores” which indicate, of the 11

issues, the percentage of people that would choose issue j as most important as shown in

equation 3.

(3) Importance Score = Share of people believing issue j is most important = J

k

k

j

e

e

1

.

One of the primary objectives of asking these survey questions is to determine how values relate

to preferences for cloning, and as such, we need information on each individual‟s values.

Unfortunately, the logit described in equation (1) assumes that all individuals in the sample place

the same level of importance on each value (i.e., there is no i subscript on αj). To overcome this

weakness of the logit, we also estimated a random parameters logit model (RPL). In particular,

let the importance parameter for individual i and issue j be specified as ijjjij~ , where

j and ζj are the mean and standard deviation of αj in the population, and μi is a random term

normally distributed with mean zero and unit standard deviation. Such a specification implies

that the importance of food value j is assumed to be distributed according to a normal

distribution with mean j and standard deviation ζj. Substituting ijjjij~ into equation

(1) yields a probability statement that depends on the random term in μij. Rather than attempting

to explicitly integrate over these random terms, following Train (2003), the model was estimated

via simulation. In particular, the parameters were estimated by maximizing a simulated log-

likelihood function, evaluated at 100 pseudo-random Halton draws for μij. The random draws

are individual-specific, which takes into consideration the panel nature of the data resulting from

the fact that each person answered 11 repeated choice questions. Train (2003) provides more

information on computational details for the RPL.

As shown by Train (2003) and Huber and Train (2001), once the parameters from the RPL are

estimated, so-called individual-specific estimates can be obtained by using the estimated

parameters as a prior and using each person‟s actual choices to form an individual-specific

posterior estimate. These posterior estimates of food values for each individual can be compared

with each person‟s preferences for cloning to determine if relationships among the variables exist.

11

4.4.2 Awareness of Animal Breeding Techniques

The second section of the survey included five simple questions designed to gauge people‟s

knowledge and awareness of five assisted reproduction technologies that are sometimes used to

breed animals for meat and milk production: artificial insemination, in vitro fertilization,

biotechnology, embryo transfer, and cloning. People were asked, “Overall, how much have you

heard or read about each of the following assisted reproduction technologies that are sometimes

used to breed animals for meat and milk production?” Response categories were: 1 = nothing at

all, 2 = a little, 3 = a moderate amount, 4 = quite a bit, and 5 = a great deal. An exact copy of the

question, as presented in the KN web survey, is shown below.

4.4.3 Information Statement

Information about animal cloning was provided to respondents in the third survey section. As

indicated in section 4.3 above, the KN and Nielsen samples were given an information statement

conveying the key issues (pro and con) on cloning, using information primarily provided by the

FDA. Recall that one-half the participants in the KN sample received this information statement

12

one week prior to taking the survey, and all participants, regardless of treatment, also received

the information statement in the third section of the survey. The IRI sample was simply given a

two-sentence definition of cloning in this section of the survey.

4.4.4 Likert Scale Questions related to Animal Cloning

In section four, respondents were asked to indicate the extent to which they agreed or disagreed

with 20 statements related to animal cloning and government involvement in animal cloning.

Examples of statements appearing in this section included:

“I am willing to eat meat from cloned animals,”

“I am willing to consume milk products from cloned animals,” and

“I trust the U.S. government to properly regulate the use of animal cloning.”

People were asked to respond to each statement on a five-point scale: 1=strongly disagree, 2=

somewhat disagree, 3=neither agree nor disagree, 4= somewhat agree, and 5=strongly agree.

Each of the 20 statements was randomly ordered across surveys.

4.4.5 Preferences for Cloning Policies Measured by Contingent Valuation

Given the controversy surrounding animal cloning, several interest groups have proposed

policies to regulate animal cloning. To gauge the public‟s interest in such policies, three

contingent valuation questions were asked. One question focused on a mandatory tracking

system for cloned animals, another focused on a mandatory labeling system for meat and milk

from cloned animals, and the final question focused on a ban on the practice of animal cloning.

Although people answered three questions, they were asked to assume that the particular policy

in question was the only one on the ballot and were asked to answer each of the three questions

individually assuming only one policy option was under consideration. The three questions were

randomly ordered across surveys.

Following the convention in contingent valuation literature, and the suggestions of the NOAA

panel, the questions were posed as dichotomous choice referendum questions. Rather than using

federal taxes as the payment vehicle, as is typically the practice in contingent valuation, we felt it

would be less objectionable to respondents and more straightforward to use an associated

increase in food prices as the payment vehicle.

The exact phrasing of the three contingent valuation questions was as follows:

1. Suppose the next time you went to vote, there was a referendum on the ballot that would

require the U.S. government to implement a policy that required a tracking system on all

cloned animals. Would you vote in favor of this policy if the policy would increase the

price you would pay for meat and milk products by X% due to the added enforcement

and oversight required by the policy?

13

2. Suppose the next time you went to vote, there was a referendum on the ballot that would

require firms to place a label on all meat and milk products derived from cloned animals

or the offspring of cloned animals. Would you vote in favor of this policy if the policy

would increase the price you would pay for meat and milk products by Y% due to the

added enforcement and oversight required by the policy?

3. Suppose the next time you went to vote, there was a referendum on the ballot that would

ban the practice of animal cloning altogether. Would you vote in favor of this policy if

the policy would increase the price you would pay for meat and milk products by Z% due

to the added enforcement and oversight required by the policy?

Response categories were of the form: 1 = I would vote in favor of <<policy>> and a X%

increase in the price of meat and milk, and 0 = I would vote against <<policy>> and the X%

increase in the price of meat and milk.

An exact screen-shot of one of the questions administered by KN is shown below.

The percentage price increases, X, Y, and Z, were randomly chosen for each individual among

the values of 5%, 10%, 15%, 25%, 50%, 75%, and 100%. The literature on experimental design

suggests the most efficient design (in terms of generating the smallest standard errors on

willingness-to-pay) is one in which the price levels are centered on “true” willingness-to-pay. Of

course, we do not know the “true” willingness-to-pay. Our a priori expectations was that the

average willingness-to-pay values was likely to be in the range of a 10-20% price increase, and

14

as such, we chose to vary several price levels around this range (5%, 10%, 15%, 25%). However,

given the uncertainty in the prior expectation, and the belief that it might take much higher dollar

amounts for people to be indifferent to the policies, we also chose three higher price ranges (50%,

75%, and 100%).

People‟s choices can be analyzed in a random utility framework, where it is assumed that people

choose the option (either vote in favor or against) that maximizes utility. Because people‟s

preferences are not perfectly observed, we make use of the random utility framework

popularized by McFadden (1973) and applied to contingent valuation by Hanemann (1984). In

particular, assuming the errors in the random utility function are logistically distributed, the

probability that a person votes in favor of the policy is given by

(4) Prob[individual i votes in favor of policy j] = ijjj

ijjj

P

P

e

e

1

where, Pij is the percentage food price increase randomly assigned to individual i and policy j.

As shown by Hanemann (1984), λj represents the utility difference between having and not

having the outcome provided by policy j, and δj is the marginal utility of income. Hanemann

(1984) shows that mean willingness-to-pay for policy j is given by -λj/δj. In this simple

framework, this value is the price increase that makes people indifferent to having and not

having the policy, i.e., the price increase that sets the probability statement in (4) to 0.50. The

parameters shown in equation (4) are easily estimated by maximum likelihood estimation using

data on people‟s discrete choices of whether they voted in favor or against each policy at a given

price level.

4.4.6 Relative Importance of Competing Objections to Animal Cloning

In this section of the survey, we once again employed the paired-comparison method to tease out

the motivations behind people‟s underlying concerns about animal cloning. Again, the

advantage of this approach (over, say, responses to simple Likert scale questions) is that people

are forced the indicate their relative degree of concern (i.e., not all issues can be most important),

making inter-personal comparisons is less problematic (i.e., there is only one way to make a

choice), and the measured levels of concern can be easily stated on a ratio scale.

To begin this section of the survey, people were told the following.

Some people are in favor of animal cloning and some people object to the practice. We

are interested in your opinions about a few of the objections that some people have about

animal cloning. For each of the following questions, please indicate which of the two

statements best describes your views toward animal cloning. We recognize that, in some

cases, you may not particularly agree with either statement; however, please choose

which of the two statements best matches your views.

Then, people were asked eight repeated questions of the form, “Which of the following two

statements best describes your views toward animal cloning? X or Y”

The two statements X and Y were randomly selected from the list of 8 issues below:

1. Animal cloning is morally wrong

2. Meat and milk from clones and their offspring is unsafe to eat

15

3. Animal cloning will lead to human cloning

4. Cloning will result in unhealthy farm animals

5. Cloning is “unnatural” because it is not a process that occurs in nature

6. Cloning will reduce genetic diversity to an unacceptable level

7. Cloning results in animals being viewed as “objects‟ to be produced as opposed to being

valuable in and of themselves

8. The scientists and biotechnology companies who developed cloning technology cannot

be trusted to look out for my best interest.

For example, one question might have been, “Which of the following two statements best

describes your views toward animal cloning? „Animal cloning is morally wrong‟ or „Meat and

milk from clones and their offspring is unsafe to eat.‟”

In total, there are (8*8-8)/2=28 possible questions that that can be created representing all

possible pairs of the issues listed above. Each person randomly received 8 of these pairings and

made discrete choices of which statement best described their view toward animal cloning.

To determine the relative importance of each of the 8 issues, a logistic regression was estimated.

The procedures used to estimate the model are exactly the same as that described in section 4.4.1

Food Values, and as such we refrain from repeating the information in here. As with the food

values, we are able to calculate “importance scores” and derive individual-specific estimates of

the importance of each of the cloning issues by estimating a random parameter logit model.

16

4.4.7 Ground Beef Conjoint Questions

In section 7 of the survey, people were asked to answer a series of discrete choice questions

regarding which ground beef option (or none) they would buy when grocery shopping. In

selecting a meat product to choose as the focal product for the conjoint exercise, ground beef was

chosen because: (i) the FDA report on cloning focused on cloning in cattle, swine, and goats (not

poultry), (ii) of these three meat types, per-capita consumption of beef is the highest, and (iii) in

the beef category, ground beef represents the vast majority of products consumed, and this holds

for all income levels, at home, and away from home (Davis and Lin, 2005). Thus, we chose the

most popular species (beef) and the most popular type of beef consumed (ground beef).

To construct the choice scenarios, each ground beef purchase option was described by four

different attributes:

1. Price per Pound

a. $1.99/lb

b. $3.99/lb

2. Percent Lean

a. 80%

b. 90%

3. Percent Saturated Fat

a. 5%

b. 10%

4. Use of Cloning

a. Meat from non-cloned animal

b. Meat from cloned animal

c. Meat from offspring of cloned animal.

The purpose of including several additional attributes other than price and cloning was: (i) to

present realistic choice options to consumers like the ones they would encounter in the

supermarket, and (ii) to determine the importance of cloning relative to these other attributes.

The first three attributes, price, percent lean, and percent saturated fat, were varied at two levels

each. The last attribute (use of cloning) was treated as an alternative-specific attribute, such that

option A was always “meat from non-cloned animal,” option B, was always “meat from cloned

animal,” and option C was always “meat from offspring of cloned animal.” To these three

options, we also added an option D which allowed people to “opt out” or indicate “no purchase.”

To determine which ground beef options to present to respondents, a main effects fractional

factorial design was utilized. In particular, there are three attributes being varied at two levels

each, meaning that there are 23 possible combinations of ground beef options that could be

created for each choice option A, B, and C. Because there are three ground beef options, there

are 23 x 2

3 x 2

3 possible choice sets that could be presented to people. From this full factorial, 12

choices tasks were selected such that the correlations between attributes, both within and across

options, are exactly zero. An example of one of the 12 choices presented to subjects in the KN

sample is shown below.

17

Responses to the choice questions can be analyzed using the random utility framework of

McFadden (1973), where the systematic portion of the utility function is assumed to depend on

the attributes of the choice option. In addition to this systematic portion, the utility function is

assumed to contain a stochastic error term representing the fact that the analyst cannot observe

people‟s preferences with certainty. It is assumed that the consumer chooses the option that

generates the highest utility given available choice options and constraints. More formally, a

random utility function is defined by a deterministic (Vij) and a stochastic ( ij) component:

(5) ijijij VU

where Uij is the ith

consumer‟s utility of choosing option j, Vij is the systematic portion of the

utility function determined by ground beef attributes in alternative j, and ij is a stochastic

element. The probability that a consumer chooses alternative j from a choice set with J total

choice options is

(6) } allfor Prob{ jkVV ikikijij .

If the random errors in equation (5) are independently and identically distributed across the J

alternatives and N individuals with a type I extreme value distribution, McFadden (1973), shows

that the probability of alternative j being chosen is the familiar multinomial logit model (MNL),

18

(7) J

k

V

V

ik

ij

e

ej

1

chosen} is n Prob{optio .

In this application, the consumers‟ utility function for alternative j is assumed to be a linear

function of total amount of fat, type of fat, price, and use of cloning:

(8) Vj = β1 (% lean)j + β2 (% saturated fat)j + β3 (non-clone) + β4(clone) +

β5(clone off spring) j + β6 (price)j

where βk represent marginal utilities of each of the attributes. For identification purposes, the

utility of the “none” option is normalized to zero. Given this normalization, β3, β4, and β5,

represent the utility of having a package of ground beef from a non-cloned, cloned, and offspring

of cloned animal, respectively, relative to not purchasing ground beef at all on the particular

shopping occasion.

Once the parameters in equation (8) are estimated via the maximization of a log-likelihood

function based on the probability statement in equation (7), a variety of useful statistics can be

calculated. For example, market shares can be readily calculated simply by substituting the

estimated parameters back into equation (7) along with the characteristics of the choice options

assumed to be presented to consumers. Given certainty about which option is chosen, simple

willingness-to-pay estimates can be also calculated. For example, willingness-to-pay to have a

particular ground beef choice option relative to “none” is simply: -[β1 (% lean)j + β2 (% saturated

fat)j + β3 (non-clone) + β4(clone) + β5(clone off spring) j]/β6. This is the price of the option that

would make people indifferent to choosing the particular ground beef option and choosing none.

Similarly, the premium someone would be willing to pay for meat from a non-cloned animal

relative to a cloned animal is given by: -[β3 - β4]/β6. This is the price difference would make

people indifferent to choosing a package of ground beef from a non-cloned animal and a package

of ground beef from a cloned animal, assuming all other attributes were the same. Finally, one

can estimate a person‟s willingness-to-pay to keep an option in the choice set. Following Small

and Rosen (1978), this statistic is determined by identifying the maximum expected utility from

a choice set with the option and the maximum expected utility of a choice set without the option,

scaled by the marginal utility of income. Given the assumption about the distribution of the error

term, this statistic is calculated as:

(9) {willingness-to-pay for option k = 1} = J

k

VJ

k

V kk eeβ

-

216

lnln1

.

One drawback to using the MNL outlined above is that it assumes (i) people are homogeneous

and (ii) the independence of irrelevant alternatives. This second assumption implies that the

ratio of market shares between any two options are unaffected by the presence or characteristics

of a third option. To relax these two assumptions, we also estimated a random parameter logit

model.

The random parameter logit can be characterized by letting β represent a vector of all non-price

attributes, such that individual i‟s utility parameters are given by ii , where and ζ

are vectors of the means and standard deviations of β in the population, and μi is a vector of

random terms normally distributed with mean zero and unit standard deviation. Substituting

19

ii into equation (7) yields a probability statement that depends on the random term,

μi:

(10) J

k

V

V

i

ik

ij

e

euj

1

}|chosen is n Prob{optio

Rather than attempting to explicitly integrate over the random terms μi, following Train (2003),

the model was estimated via simulation. The parameters were estimated by maximizing a

simulated log-likelihood function, evaluated at 100 pseudo-random Halton draws for μi. The

random draws are individual-specific, which takes into consideration the panel nature of the data

resulting from the fact that each person answered 12 repeated choice questions. Train (2003)

provides more information on computational details for the RPL. As with the MNL, mean WTP

in the RPL for meat from a non-cloned animal relative to a cloned animal (assuming a constant

price effect) is 643 /][ . The standard deviation of this WTP measure in the population

(again assuming a non-random price effect) is: )()/1( 2

4

2

3

2

6 , where 2

3 and 2

4 are the

variances of β3 and β4, respectively.

4.4.8 Milk Conjoint Questions

Section 8 of the survey was similar to the previous section except, people were asked to answer a

series of discrete choice questions regarding which milk option (or none) they would buy when

grocery shopping. In choosing a dairy product for use in the conjoint questions, plain fluid milk

was chosen because it represents the largest category of dairy purchases. Total consumption of

fluid plain milk was about 116 lbs/person/year in 2005, whereas consumption of cheese

(American, Italian, and miscellaneous) was only 23.8 lbs/person/year, and frozen dairy products

was only 17 lbs/person/year, and yogurt was only about 6 lbs/person/year (USDA-ERS, 2008).

To construct the choice scenarios, each milk option was described by four different attributes:

1. Price per Gallon

a. $2.99/lb

b. $5.99/lb

2. Fat Content

a. Whole

b. 2%

c. 1%

d. Skim

3. Use of rBST

a. No rBST used

b. rBST used

4. Use of Cloning

a. Milk from non-cloned animal

b. Milk from cloned animal

c. Milk from offspring of cloned animal.

20

As in the beef conjoint task, the last attribute (use of cloning) was treated as an alternative-

specific attribute, such that option A was always “milk from non-cloned animal,” option B, was

always “milk from cloned animal,” and option C was always “milk from offspring of cloned

animal.” To these three options, we also added an option D which allowed people to “opt out” or

indicate “no purchase.” To determine which milk options to present to respondents, a main

effects fractional factorial design was utilized. In particular, there are two attributes being varied

at two levels each (price and rBST use) and one attribute varied at four levels (fat content),

meaning that there are 22 x 4 possible combinations of milk options that could be created for

each choice option A, B, and C. Because there are three milk options, there are 22 x 4 x 2

2 x 4 x

22 x 4 possible choice sets that could be presented to people. From this full factorial, 16 choices

tasks were selected such that the correlations between attributes, both within and across options,

are exactly zero. An example of one of the 16 choice tasks presented to subjects in the KN

sample is shown below.

The responses to the choice questions can be analyzed in exactly the same fashion as the beef

conjoint questions as described in section 4.4.7 Ground Beef Conjoint Questions, and as such we

refrain from repeating the information in this section.

21

4.4.9 Demographic Information

The last section of the survey included a few demographic questions. Because KN, IRI, and

Nielsen each maintain a panel of respondents, they are already in possession of information on

each respondent‟s, age, income, education, etc. Thus, there was no need to ask such information.

The last section asked a few questions germane to the present study including questions about

whether the respondent had any ties to farming, questions on people‟s consumption of beef and

milk, and a question regarding whether the respondent was the primary shopper of food in their

household.

22

5. Results from the Randomly Recruited Sample

This section presents the results from the KN sample. KN utilized a random recruitment method

where each individual in the population has an equal chance of inclusion in the sample; a fact

which implies that the results from the KN sample can be used, along with statistical theory, to

make statements about the percentage of the U.S. population having particular attitudes about

animal cloning.

5.1 Awareness of Animal Cloning and Other Animal Breeding Techniques

Table 2 reports people‟s stated awareness of assisted reproduction technologies that are used to

breed animals for meat and milk production. Overall, people indicated that they had heard or

read more about cloning than any of the other techniques. For example, in the sample that did

not receive prior information, only 14% had never heard about animal cloning, whereas 47% had

never heard of embryo transfer, 36% had never heard of biotechnology used to breed animals,

32% had never heard of in vitro fertilization, and 25% had never heard about artificial

insemination. Not surprisingly, providing people information about animal cloning one week

prior to administration of the survey significantly increased awareness of this and several other

reproductive technologies at the time of the survey.

5.2 Willingness to Eat Cloned Meat and Milk

Table 3 reports the extent to which people agreed or disagreed with statements about willingness

to eat and purchase cloned meat and milk. First, we note that providing people a week to digest

information on animal cloning had no affect on stated willingness to eat cloned meat or milk.

Apparently, people who were only provided information on cloning at the time of the survey

were not simply giving answers as result of a “shock value” or “gut reaction,” assuming that they

actually contemplated the information provided. The answers given after a week of time to

contemplate the information were no different than those given “on the spot.” This result may be

due, in part, to the fact that people were already at least somewhat aware of the technology,

especially in comparison to other assisted reproductive technologies (see table 2), and as such,

people may have already formed opinions on the issue prior to the study.

Results in table 3 reveal that there was virtually no difference in willingness to eat meat and

willingness to drink milk from cloned animals. For both meat and milk, about 31% indicated

that they were willing to eat meat/milk from cloned animals, whereas 43% to 44% indicated they

were not. People did not differentiate much between meat/milk from clones and the meat/milk

from the offspring of clones. Regardless of whether the meat/milk was from cloned animals or

their offspring, the percentage of people willing to eat remained about 31% and the percentage

unwilling to eat was about 43% to 44%. A little more than 40% of respondents indicated that

they would likely alter their consumption of meat and milk if they learned that the products came

from cloned animals.

23

Table 3 also reports the result of an “indirect question.” In particular, people were asked to

indicate whether the “average American” was willing to eat meat from cloned animals. People

indicated that they were more willing to eat meat from cloned animals (31%) as compared to the

percentage of people who thought that the “average American” was willing to eat (21%). In

previous research, we have argued that differences in direct and indirect questioning are likely a

result of a type of social desirability bias (see Lusk and Norwood, 2008a,b,c). That is, people

answer direct survey questions in a way to make themselves “look good,” but have no such

motivation when answering questions about what they think others will do. The differences in

direct and indirect questions observed here on cloning are much smaller than the differences we

have observed on questions about organic food and animal welfare. Thus, relative to these other

issues, social desirability bias appears to be of lesser concern for the issue of cloning.

Nevertheless, results do suggest a slight tendency for people to over-state their acceptance of

cloned meat, perhaps out of an attempt to portray themselves as more open to new technologies.

5.3 Beliefs about Safety and Acceptability of Cloned Meat and Milk

People answered a series of agree/disagree questions related to statements about the safety and

acceptability of cloned meat and milk. Table 4 shows that most people (57.5%) were unsure

whether meat currently sold in grocery stores is from cloned animals, suggesting people exhibit a

great deal of uncertainty about the technologies currently being used to breed livestock. About a

quarter of the respondents thought no meat from cloned animals or their offspring was currently

being sold in stores.

Respondents were equally split on the acceptability of animal cloning, with about a third finding

the practice acceptable, a third finding the practice unacceptable, and a third neutral. Only about

21% believed that animal cloning would result in beneficial outcomes for them.

People were equally split on the safety of cloned meat. About 30% agreed that meat from cloned

animals was safe to eat, where as about 29% believed the meat to be unsafe; 41% neither agreed

nor disagreed that meat from cloned animals was safe to eat.

Despite potential concerns about the safety of meat from cloned animals, people expressed

confidence in the safety of meat and milk typically bought in the grocery store. About 64% of

the public believed that, in general, the meat and milk they buy from the grocery stores is safe to

eat. Only 10% disagreed with this statement.

5.4 Beliefs about Federal Government and Cloned Meat and Milk

Although people expressed confidence in the safety of meat and milk (see table 4), somewhat

paradoxically, they expressed little trust or confidence in the federal government to regulate food

safety or cloned meat/milk (see table 5). For example, almost 40% of the public did not believe

the government was doing everything it could to ensure the safety of food products (only 30%

thought they were doing all they could). Only 20% believed that animal cloning is carefully

24

regulated by the U.S. government. Further, only 24% of the public trust the government to

properly regulate the use of animal cloning.

Expressed levels of trust in information about cloning were also relatively low. In order of

decreasing trustworthiness, 32% trust information about cloning from University scientists and

researchers, 29.3% trust information about cloning from the USDA, 28.8% trust information

from the FDA, and only 26.1% of people trust information from the EPA.

These results suggest that the trust the public has in the safety of the general food supply is

apparently not a result of confidence in the government regulating food safety.

5.5 Why Are People Concerned about Animal Cloning?

5.5.1 Relative Importance of Competing Objections to Cloning

People were asked to answer a series of questions in which they were presented with two

statements related to potential objections about animal cloning, and were asked to indicate which

statement best matched their view. Discrete choice models were used to place each issue on an

underlying scale of importance. The models allow us to estimate the probability of a respondent

choosing one issue as more important than another.

The “importance scores” take the form of probabilities, and thus the sum of the estimated

importance scores across all 8 issues must equal 100. If two issues (say issues A and B) are

roughly equivalent in importance to respondents, roughly half the subjects will say Issue A is

more important and half will say Issue B is more important. The importance score calculation

will then assign an identical number (50%) to both issues. Conversely, if Issue A is deemed

more important by 750 individuals, and Issue B deemed more important by 250 people, the

importance score calculation will assign an importance score to Issue A of 75% and an

importance score to issue B of 25%: thus, Issue A is three times as important as Issue B.

Therefore, the importance scores assigned to each issue reflects the percentage of times that issue

was considered to better match people‟s views than other issues. Because these probability

statements are on a ratio scale, they can be compared proportionally. That is, if Issue A‟s

importance score is two times larger than Issue B, then Issue A is twice as important as Issue B.

Table 6 reports the model estimates for the logit and RPL models and the calculated importance

scores for each statement or issue. Likelihood ratio tests indicate that the logit model can be

rejected in favor of the RPL model, and as such, we focus on the results from the RPL

specification, which are shown in figure 1. Results indicate that the two most popular objections

to animal cloning were: (i) “Cloning is „unnatural‟ because it is not a process that occurs in

nature” and (ii) “Animal cloning will lead to human cloning.” These statements provide almost

two times a better match for people‟s views toward cloning than statements such as “Animal

cloning is morally wrong” or “Cloning will reduce genetic diversity to unacceptable levels.”

People were relatively unconcerned that cloning will result in unhealthy farm animals or that

meat and milk from clones and their offspring are unsafe to eat. Indeed, these statements are

about four to five times less likely to match people‟s views toward animal cloning as compared

to concerns about unnaturalness and the potential for human cloning.

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The results presented in figure 1 provide insight into messages that may persuade people to

become more or less accepting of cloning, but also suggests people are unlikely to be affected

much by persuasion. For example, people seemed to object to cloning primarily because it is not

a process that occurs in nature. That cloning does not occur in nature is, of course, true and no

amount of scientific evidence or persuasion is likely to alter this perception. Concerns about

animal cloning leading to human cloning; however, might be partially mitigated by careful

regulation and oversight. Messages that attempt to alleviate the public‟s concern about the safety

of cloned meat and milk (which was the focus of the report from the FDA) are unlikely to have

much impact because, as shown in table 1, most consumers do not view this issue to be of great

concern in relation to other issues.

5.5.2 Correlations between Willingness-to-Eat and Beliefs about Government Involvement

Table 7 reports simple bi-variate correlations between people‟s agree/disagree responses to the

Likert scale questions. Results reveal high correlations, in the range of 0.5 and higher, between

(i) trust in information about cloning from the USDA, (iii) the belief that the government is

doing all it can to ensure the safety of food products, (iv) perceptions about the safety of cloned

meat, and (v) willingness to eat cloned meat. People who have more trust in the information

from the USDA and believe the government is doing what it can to ensure the safety of food are

also the same people who are more convinced of the safety of meat from cloned animals and are

more willing to eat cloned meat/milk. Another interesting result shown in table 7 is that the

belief that cloned meat is already sold in grocery stores products is positively correlated with

people‟s willingness to eat cloned meat. This potentially points to a type of endowment effect

where people are supportive of what they perceive to be the status quo: if people believe cloned

meat is already being sold, they are more willing to eat: if people believe cloned meat is not

being sold, they are less willing.

5.5.3 Correlations between Competing Concerns for Cloning and Willingness-to-Eat

Although the results presented in Table 6 and Figure 1 provided a picture of the relative level of

concern for several issues related to animal cloning, it is of interest to ask whether people who

express a higher overall level of concern about animal cloning find certain issues to be more or

less problematic than people who express a lower overall level of concern.

Table 8 provides some insight into this issue by reporting bi-variate correlations between

agree/disagree responses to selected Likert scale questions and the individual-specific

“importance scores” for competing cloning concerns derived from the random parameter logit.

Results shown in table 8 indicate that people who are relatively more concerned about the

morality of animal cloning are the same people who are less willing to eat meat from cloned

animals. Thus, although the morality of animal cloning only ranked fourth on the list of

competing concerns, it is an issue highly related to willingness to eat cloned meat. Interestingly,

the issue of most concern to people – that cloning is unnatural because it is not a process that

occurs in nature – is virtually unrelated to people‟s willingness to eat cloned meat. That is,

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people for whom “unnaturalness” is a relatively big concern are just as likely to express

willingness to eat cloned meat as are people for whom “unnaturalness” is not as big a concern.

5.5.4 Relationships between Socio-Economic, Demographic Factors and Cloning Attitudes

To determine the relationship between socio-economic factors and attitudes toward cloning,

several ordered probit models were estimated (see table 9). The dependent variables are

responses to the agree/disagree Likert-scale questions. Given that the responses to these

questions fall on a 5-point scale, the ordered probit model is the appropriate specification as it

treats the dependent variable as ordinal rather than cardinal. The reported parameter estimates

correspond to the marginal effects on the underlying latent (unobserved) variable, which is the

propensity to agree with each statement.

Table 9 reports the results of the probit regressions. Results reveal that providing respondents

with a week to digest information on animal cloning had no effect on responses to the

agree/disagree Likert scale questions.

Results reveal that females are more likely to agree that animal cloning is unacceptable than

males. Likewise, males are more likely to be willing to eat meat from cloned animals and are

more likely to believe that cloned meat is safe to eat than females. Results also indicate that

people with only a high school diploma were more likely to believe cloning was unsafe and

believe that cloning is unacceptable than people with a bachelor‟s degree or higher. Thus,

education appears to have some relationship to the acceptability of cloning.

Interestingly, and somewhat surprisingly, whether people lived in a household with Internet

access was strongly associated with most of the dependent variables shown in table 9. People in

households without Internet access are more likely to believe that animal cloning is unacceptable

than households with Internet access. Similarly, people in households with Internet access are

more likely to believe meat from clone animals is safe to eat, are more willing to eat cloned meat,

and express greater trust in information from the USDA than non-Internet households. This

finding may be due to the fact that households with Internet access have received more

information about cloning. An alternative explanation is that people with Internet in the

household may be more accepting of technology in general than non-Internet households, and

this general acceptance of technology may spill over into acceptance of cloning technology.

The last few rows in table 9 indicate that people who are the primary shoppers of food in their

household are more likely to disagree with the statement that animal cloning is unacceptable.

Further, people that had children under the age of 12 in their household are less likely to believe

that meat from cloned animals is safe to eat.

5.5.5 Food Values and Their Correlations with Cloning Concerns

Table 10 reports on the results of an analysis carried out to identify people‟s food values, i.e.,

which general issues are most important to people when they purchase food. As shown in figure

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2, food safety is overwhelmingly the most important food value, being twice as important as the

next most important food value, nutrition. Out of the 11 competing food values, four represent

73% of the overall importance score: safety, nutrition, taste, and price. This latter finding is

consistent with that reported by Lusk and Briggeman (2008).

Of more direct relevance to this study is the relationship between food values and concerns for

cloning. Table 11 reports bi-variate correlations between people‟s agree/disagree responses to

selected Likert scale questions and individual-specific “importance scores” for the food values.

The food value of “naturalness” defined as “the extent to which food is produced without

modern technologies” appears to be most related to trust in the government and willingness to

eat cloned meat and milk. People for whom naturalness was a more important food value were

less likely to believe the government is doing everything it can to ensure the safety of food and

were less willing to eat meat from cloned animals. A similar finding is true for people that

believe origin is a more important general food value. Table 11 shows that people who believe

food safety is a relatively more important general food value are no more or less willing to eat

cloned meat/milk than people who think food safety is a less important food value.

5.6 Preferences for Cloning Policies

People were asked how they would vote on three different federal policies related to animal

cloning. Table 12 reports a simple cross-tabulation reporting the percentage of people who

would vote in favor of each policy at each of the seven price levels randomly assigned to

respondents. Table 13 analyzes this data more formally using logistic regressions predicting the

probability of a “yes” vote as a function of the price increase. Figure 3 illustrates the predicted

probabilities of voting in favor of each policy as a function of the change in food prices.

Results reveal low levels of support for a policy requiring the mandatory tracking of cloned

animals and a policy banning animal cloning. Indeed, table 13 shows that the point-estimate on

mean willingness-to-pay is negative and that 0% is clearly within the 95% confidence intervals.

These results indicate that the public is not willing to pay to enforce a mandatory tracking system

or to ban the practice of animal cloning. One possible explanation for the finding that the point

estimate on the ban is negative (-13%) is that people expect that some benefits may result from

research on animal cloning and they are reluctant to impede scientific discoveries that may result

in some future benefit. Indeed, Hamilton, Sunding, and Zilberman (2003) argue that people are

often unwilling to pay for policies because of a lost option value; when a regulation or ban takes

place it is often difficult to reverse and people lose the option or ability to change their mind as

more information becomes available in the future.

The only policy for which mean willingness-to-pay was significantly greater than zero was a

mandatory labeling policy. Results indicate that people would be willing to pay up to 31%

higher food prices for the ability to know whether meat and milk is from a cloned animal; a

policy which provides the option of choosing which product best suits their preferences given

market prices. One important note about a mandatory labeling policy is that, depending on how

it was implemented, it may require mandatory tracking. Thus, although people were unwilling to

pay for mandatory tracking per se, they might value it as a part of a labeling system.

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5.7 Ground Beef Market Simulator

People answered a series of questions regarding which option of ground beef they would buy (or

none), where each ground beef option was described by a series of attributes including fat

content, price, and use of cloning. The discrete choice data was analyzed using multinomial and

random parameter logit models (see table 14), which provide estimates of people‟s attribute-

based utility function. Likelihood ratio tests indicate that the RPL provides a significantly better

fit to the data, and as such, results from this specification are discussed.

Table 14 shows that the mean price effect is negative (-1.14), meaning increases in price

decrease utility (i.e., higher priced options are less likely to be chosen than lower priced options,

all else held constant). People enjoy increases in ground beef leanness and decreases in saturated

fat content. Comparing the relative magnitude of the dummy variables related to cloning

indicates that people strongly preferred ground beef from a non-cloned animal to ground beef

from a cloned animal (3.922 vs. 0.112). The last column in table 14 reports significant standard

deviations for all product attributes, meaning there is significant heterogeneity in the population

in terms of people‟s preferences for fat content and cloning. For example, while the mean

marginal utility of leanness was 0.057 (i.e., a 1% increase in leanness increases utility by 0.057

units), the standard deviation was 0.067, meaning 95% of the population has a preference

parameter for leanness between -0.074 and 0.188. That some people actually prefer fattier

ground beef is of course consistent with the notion that some people prefer taste over healthiness.

Following previous literature, the standard deviation on the price coefficient was restricted to

zero because: (i) for economic theory to hold, a parametric distribution that is non-negative

would have to be used for the price coefficient (e.g., the log-normal), which typically generates

willingness-to-pay distributions with very fat, and often unrealistic, tails, (ii) it ensures normally

distributed willingness-to-pay estimates, and (iii) it facilitates model convergence.

Table 15 reports willingness-to-pay estimates derived from the models reported in table 14.

Results reveal large willingness-to-pay premiums for meat from non-cloned animals relative to

meat from clones or offspring of clones. The mean willingness-to-pay for non-clone vs. cloned

ground beef is $4.23 per choice occasion. Stated differently, if ground beef from a non-cloned

animal was priced at a premium of $4.23 to ground beef from a cloned animal, the “average”

person would be indifferent to buying the two products. Despite this large willingness-to-pay

estimate, the standard deviation is also quite large. The estimates in table 14 imply that the

standard deviation of willingness-to-pay for non-clone vs. cloned ground beef is $3.44, meaning

that 95% of the population has a willingness-to-pay premium for non-cloned ground beef

between -$2.52 and $10.98. In fact, these estimates imply that 11% of the people in the

population are unwilling to pay a premium for ground beef from a non-cloned animal over

ground beef from a clone.

Results reveal people are willing to pay a $0.50 for a 10% increase in leanness. The implied

marginal effect (a $0.05 increase for each one percent increase in leanness) is very similar to the

$0.04/lb estimate reported by Parcell and Schroeder (2007), who obtained their estimate using

actual market transactions and hedonic price analysis. That our choice-based conjoint model

provides similar results to that obtained from real market transactions provides some confidence

in the underlying validity of the model.

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The estimates reported in tables 14 and 15 can also be used to get a feel for the relative

importance of cloning as compared to, say, fat content. The results reveal that, on average, it

would take an 84.5% change in leanness to make people indifferent to a cloned and non-cloned

product. That is, people would be indifferent to purchasing ground beef from a cloned product

that was 95% lean and a non-cloned product that was only 10.5% lean (e.g., 95% - 84.5% =

10.5%), holding prices constant. Of course, it is silly to think that anyone would want a product

that is only 10.5% lean, and the difference in leanness involved (84.5%) is extrapolating well

beyond the differences in leanness that existed in the data; however, the results qualitatively

suggest that the attribute of cloning is much more important to people than the attribute of

leanness. A similar comparison can be made for saturated fat content. On average, it would take

a 24.5% change in saturated fat content to make people indifferent to a cloned and non-cloned

product. That is, people would be indifferent to purchasing ground beef from a cloned product

that had 5% saturated fat and a non-cloned product that had 29.5% saturated fat. Although

saturated fat appears relatively more important than leanness, the attribute of cloning is more

important still.

Given the estimates in table 14, any number of market simulations can be constructed. To

facilitate such analyses, a market simulator was constructed, and can be accessed at:

http://agecon.okstate.edu/faculty/publications/3103.xls . Figure 4 shows an example of the

output that can be generated under one particular simulation. Examples of insights that can be

gleaned from the simulator are: (i) when faced with a choice between ground beef from a cloned

and a non-cloned animal, more than 75% of shoppers are predicted to choose the non-cloned

beef even when sold at a $1.50 price premium over ground beef from a cloned animal, and (ii) if

faced with a choice of only being able to buy ground beef from a cloned animal or no ground

beef at all, the majority of consumers would choose to purchase the cloned ground beef

(assuming the price of ground beef was $3.50/lb or lower).

5.8 Milk Market Simulator

People answered a series of questions regarding which milk option they would buy (or none),

where each option was described by a series of attributes including fat content, price, and use of

cloning. The discrete choice data was analyzed using multinomial and random parameter models

(see table 16), which provide estimates of people‟s attribute-based utility function. Likelihood

ratio tests indicate that the RPL provides a significantly better fit to the data, and as such, results

from this specification are discussed.

Table 16 shows that the mean price effect is negative (-0.734), meaning increases in price

decrease utility (i.e., higher priced options are less likely to be chosen, all else held constant).

On average, people most preferred 2% milk, followed by Skim milk, 1% milk, and then whole

milk. However, the RPL model shows, as expected, significant heterogeneity in preferences for

fat content. For example, while the mean marginal utility for whole milk versus skim was -

0.545, the standard deviation was 2.054, meaning 95% of the population has a preference

parameter for whole milk between -4.57 and 3.48. Clearly, the variation in preferences for this

attribute is of more importance than the mean. Comparing the magnitude of the dummy

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variables related to cloning indicates that people strongly preferred milk from a non-cloned

animal to milk from a cloned animal (4.333 vs. 1.668). As in the ground beef models, the

standard deviation on the price parameter was restricted to zero.

Table 17 reports willingness-to-pay estimates derived from the models reported in table 16.

Results reveal large willingness-to-pay premiums for milk from non-cloned animals relative to

meat from clones or offspring of clones. The mean willingness-to-pay for non-clone vs. cloned

milk is $3.63 per choice occasion. Despite this large willingness-to-pay estimate, the standard

deviation is also quite large. The estimates in table 16 imply that the standard deviation of

willingness-to-pay for non-clone vs. cloned ground beef is $4.91, meaning that 95% of the

population has a willingness-to-pay value between -$5.99 and $13.25. These estimates imply

that 23% of the people in the population are unwilling to pay a premium for milk from a non-

cloned animal over milk from a clone.

The estimates reported in tables 17 provide a feel for the relative importance of cloning.

Although people are, on average, willing to pay a $1.80 premium for “non rBST” milk, this is

only about half the amount they are willing to pay to avoid milk from a cloned animal. Cloning

is more important to people than the use of rBST.

Given the estimates in table 16, any number of market simulations can be constructed. To

facilitate such analyses, a market simulator was constructed, and can be accessed at:

http://agecon.okstate.edu/faculty/publications/3104.xls. Figures 5 and 6 show examples of

outputs that can be generated under two particular simulation scenarios. Examples of insights

that can be gleaned from the simulator are: (i) when faced with a choice of milk from a cloned

and a non-cloned animal, more than 65% of shoppers are predicted to choose the non-cloned

milk even when sold at a $1.50 price premium over milk from a cloned animal, and (ii) if faced

with a choice of only being able to buy milk from a cloned animal at $3.00/gallon or no milk at

all, only about 47% of consumers would choose to make the purchase.

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6. Comparing Results across Three Survey Samples

This section compares results from the KN, IRI, and Nielsen samples, and for the IRI and

Nielsen samples, shows the relationship between actual purchases of meat/milk and concerns for

cloning.

6.1 Sample Characteristics

Table 18 shows the original unweighted characteristics of each of the survey samples. None of

the samples perfectly match the U.S. population, but overall the KN random sample appears to

be most similar to the U.S. census data. There were substantially more females and primary

shoppers in the IRI and Nielsen samples than in the KN sample, a result that is not surprising

given the differences in the ways the three panels are constructed and used by the subcontractors.

To facilitate comparisons across survey samples, recall that for each survey sample, post-

stratification weights were created. This means that the remaining results reported from each

sample, KN, IRI, and Nielsen, are each reflective of the U.S. population in terms of geographic

location, age, race, gender, and education. Thus, although differences in concern for cloning

may be observed across samples, such differences are not a result of differences in geographic

location, age, race, gender, and education across the samples.

6.2 Food Values

To begin the comparison of responses from the three survey samples, it is instructive to start by

comparing responses to the food value questions because these questions were asked prior to any

information being provided about cloning, and as such, they allow for a straightforward

comparison across survey samples without having to worry about differences in information.

Table 19 reports the results of logit models estimated to identify people‟s food values, i.e., which

general issues are most important to people when they purchase food. For all three samples,

food safety is overwhelmingly the most important food value, being twice as important as the

next most important food value. The second most important food value was taste for the KN and

Nielsen samples, but the nutrition was the second most important food value for the IRI sample.

The only sample for which the difference in importance assigned to nutrition vs. taste is

quantitatively large is the Nielsen sample, and for the Nielsen sample, taste is 1.4 times more

important than nutrition (by contrast, nutrition is only 1.06 times more important than taste for

the IRI sample). For all three samples, “fairness” is the least important food value. The value of

“naturalness” was slightly more important to the people in the KN sample than for the people in

the IRI and Nielsen samples, and the opposite was true for the value of “appearance.”

A likelihood ratio test indicates that we can reject the null hypothesis that the estimated

parameters are equivalent across all three samples (P < 0.001). This provides evidence that even

after controlling for geographic location, age, race, gender, and education via weighting, there

are significant differences across the KN, IRI, and Nielsen samples – at least in a statistical sense.

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However, the results in table 19 indicate that the differences across samples are not particularly

large in that they would lead to substantially different conclusions about the food values people

are most concerned about. This is to say that although the differences are statistically significant,

they may not be economically significant.

6.3 Awareness of Animal Cloning and Other Animal Breeding Techniques

Table 20 reports people‟s stated awareness of assisted reproduction technologies that are used to

breed animals for meat and milk production for each of the three survey samples. Other than the

differences in the two KN treatments previously discussed, there are not large differences across

samples. There does appear to be a slight tendency for people in the opt-in panels to indicate a

higher mean level of awareness of all assisted reproductive technologies, but the differences are

not large. The Nielsen sample tended to have a higher fraction of people who had not heard

anything at all about each of the reproductive technologies. For example, 16.4% of the Nielsen

sample had not previously heard or read about cloning, whereas only 10.3% and 14.1% of the

IRI and KN samples, respectively had not previously heard or read about cloning.

6.4 Willingness to Eat Cloned Meat and Milk

Table 21 reports the mean responses (on the 5-point scale) related to the extent to which people

agreed or disagreed with statements about willingness to eat and purchase cloned meat and milk.

Table 22 reports the percentage of respondents in each of the three samples who agreed,

disagreed, and neither agreed nor disagreed with these statements. Because we previously

showed in section 5 that providing people a week to digest information on animal cloning had no

effect on stated willingness to eat cloned meat or milk in the KN sample, we simply pooled the

data across the information treatments in the KN sample.

Results in table 22 reveal that people in the IRI sample, who were only provided the short

information statement, were the least willing to eat cloned meat and milk. These differences are

statistically significant, and suggest that the information from the FDA provided to the KN and

Nielsen samples served to improve acceptance of cloning. Again, although the change was

statistically significant, it is important to emphasize that willingness to eat clone meat only

jumped 10% from the IRI to Nielsen sample and remained below 34% of the total population for

both samples. That is, the information did not generate a massive shift in conclusions about

public acceptance of cloning.

There were not large differences in the KN and Nielsen samples in terms of stated willingness to

eat meat/milk from clones and their offspring, but the Nielsen sample was more likely than the

KN or IRI samples to agree with the statement “If I learned that the meat/milk products I

regularly purchase came from clone animals, I would continue to buy the meat products as

usual.” This provides slight evidence that the Nielsen opt-in panel is more accepting of cloning

than is the general population, as represented by the KN panel.

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6.5 Beliefs about Safety and Acceptability of Cloned Meat and Milk

Tables 23 and 24 report results related to the series of agree/disagree questions on statements

about the safety and acceptability of cloned meat and milk. Results are similar to that discussed

in the preceding sub-section. The IRI sample was more likely to agree that animal cloning is

unacceptable than the KN and Nielsen samples (40% vs. 32% vs. 34%, respectively). The IRI

sample was least likely to agree that meat from cloned animals was safe to eat, whereas the

Nielsen sample was most likely to agree with this statement. Apparently, the lengthier

information statement served to somewhat reduce fears about the safety of consuming cloned

meat. Interestingly, the last row of table 23 indicates that both the IRI and Nielsen samples

indicated a higher level of agreement, on average, with the statement, “In general, the meat and

milk I buy from the grocery store is safe to eat,” providing some indication that the opt-in panels

are less concerned about food safety as compared to the general public represented by the KN

sample. This finding is consistent with the food values analysis reported on in table 19, where

the “importance score” for food safety was 33.1% for the KN sample, but only 27.8% for the IRI

sample and 30.2% for the Nielsen sample.

6.6 Beliefs about Federal Government and Cloned Meat and Milk

Tables 25 and 26 provide information on people‟s beliefs about the federal government and

cloned food in each of the three survey samples. Providing people lengthier information about

cloning served to increase people‟s beliefs that “animal cloning is carefully regulated by the U.S.

government,” as can be seen by comparing responses across the IRI, Nielsen, and KN samples.

The Nielsen sample was most optimistic that the U.S. government is doing all it can to ensure the

safety of food and can trace cloned animals back to the farm.

The last five rows of tables 25 and 26 indicate little difference across samples in terms the

expressed levels of trust. The ranking of trustworthiness was generally consistent across samples.

People most trusted University scientists and researchers, the USDA, the FDA, and then the EPA.

Regardless of the survey sample, the results suggest that the trust the public has in the safety of

the general food supply is apparently not a result of confidence in the government regulating

food safety; trust in information about cloning was low in all three samples.

6.7 Relative Importance of Competing Objections to Cloning

Table 27 reports an analysis carried out on all three survey samples to determine the relative

importance of competing objections about animal cloning. All three samples rating

“unnaturalness” as the most important objection to cloning, although the IRI sample rated this as

a slightly higher objection than the KN or Nielsen samples. The second most objectionable issue

with cloning, for all three samples, was that “scientists and biotechnology companies who

developed cloning technology cannot be trusted to look out for my best interest.” The least

objectionable issue for all three samples was that meat and milk from clones is unsafe to eat.

This is interesting because the IRI sample was not provided any information about the FDA‟s

statement on the safety of cloned meat and milk products.

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6.8 Relationship between Milk/Meat Purchases and Willingness to Eat Cloned Food

One of the purported advantages of the opt-in panels is the ability to link actual purchase data to

people‟s survey questions. In this section (and in tables 28 and 29), we explore whether such

actual purchase data are associated with people‟s stated willingness to eat cloned milk and meat,

and investigate whether actual purchases yield similar insights as people‟s stated purchases.

Investigating whether concerns for cloning are higher or lower for people that are heavier

consumers of meat or milk is important because it relates directly to the market impacts of the

new technology. For example, if heavy consumers of meat are significantly less concerned about

cloning, then the market impacts of introducing meat from cloned animals is likely to be much

smaller than if the opposite is true.

6.8.1 Milk

Table 28 reports the results of five ordered probit regressions, where the dependent variable in

each regression is the agree/disagree response on the 5-point scale to the statement “I am willing

to consume milk products from cloned animals.” The regressions include a variety of variables,

which hold constant the effect of age, gender, education, income, etc., when investigating the

effect of milk purchases on willingness to consume cloned milk products.

The last few rows in table 28 show the effect of stated and actual milk purchases on stated

willingness to consume milk from cloned animals. First looking at the effect of stated milk

consumption, there are contradictory results across samples. For the KN sample, people who

never purchase milk or only purchase about once a year are less willing to consume cloned milk

than people who say they purchase milk every day; a similar result is found for the Nielsen

sample. However, for the IRI sample, just the opposite is true - people who say they never

purchase milk or say they only purchase about once a year are more willing to consume cloned

milk than people who say they purchase milk every day.

Turning to the actual purchase data, there is no relationship between annual purchase volume (as

measured in gallons for the IRI sample and units for the Nielsen sample) and willingness to eat

cloned milk. For both samples, we also tested whether there might be a quadratic relationship

between actual milk purchases and willingness-to-consume, but such quadratic terms were not

statistically significant. The IRI data set also contained information for each household on

annual purchases of organic milk (in gallons). Based on this information, a second variable was

created which measures the share of total milk purchases attributable to organic milk. On

average, only 5.4% of total milk purchases were organic, but there was wide variation in the

sample with some people buying no organic milk (i.e., share = 0) and others only buying organic

milk (i.e., share = 1). As shown in table 28, there is a strong and statistically significant

relationship between organic purchases and stated willingness to consume cloned milk. Holding

total milk purchases constant, people who bought more organic milk were much less willing to

drink cloned milk than people who bought less organic milk. Stated differently, those people

who are more interested in organic products (as measured via actual purchase behavior) are also

more concerned about cloning.

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6.8.2 Meat

Table 29 reports the results of five ordered probit regressions, where the dependent variable in

each regression is the agree/disagree response on the 5-point scale to the statement “I am willing

to eat meat from cloned animals.” The regressions include a variety of variables, which constant

the effect of age, gender, education, income, etc., when investigating the effect of meat purchases

on concerns for cloned milk.

The last few rows in table 29 show the effect of stated and actual meat purchases on willingness

to consume meat from cloned animals. For all three samples, there is a tendency for people who

say they purchase meat every day to be more willing to eat cloned meat than people who never

purchase meat. This effect is strongest in the Nielsen sample.

Turning to the actual purchase data, we find that there is no relationship between annual

purchase volume (in lbs) of breakfast and lunch meat purchased and willingness to eat cloned

meat as indicated in the IRI sample. Unfortunately, IRI did have data on sales of organic meat or

data on sales of fresh met. The Nielsen data set contained information on annual fresh beef

purchases (in packages or units). As can be seen in the last row of table 29, increases in actual

purchase of fresh beef are associated with a higher willingness to consume cloned meat.

6.9 Preferences for Cloning Policies

Tables 30, 31, and 32 report average willingness-to-pay (WTP) for mandatory tracking,

mandatory labeling, and banning polices, respectively for each of the three samples.

Table 30 shows that although the KN sample was not willing to pay for a mandatory tracking

policy, the IRI sample was willing to pay 61.7% higher food prices and the Nielsen sample was

willing to pay 32% higher food prices for a mandatory tracking policy. The huge difference in

WTP between the IRI sample and the KN and Nielsen samples suggest that, in this context, there

could be significant economic value associated with information provision.

Table 30 reports mean WTP for a mandatory labeling policy. All three samples reported positive

WTP for this policy. WTP for both the KN and Nielsen samples was about 32% - i.e., people

were willing to pay up to 32% higher food prices to have a mandatory labeling policy on meat

and milk from cloned animals and their offspring. Consistent with the previous results, the IRI

sample was WTP an even higher amount – almost 100% higher prices.

Table 32 shows that WTP for a ban is not significantly different than zero for any of the three

samples. This finding suggests that even though the IRI sample was significantly more opposed

to cloning than the KN or Nielsen samples, they were not willing to prohibit the use of the

technology all together.

36

6.10 Ground Beef Choice-Based Conjoint Estimates

Table 33 shows the multinomial logit estimates fit to people‟s choices of which option of ground

beef they would buy (or none), where each ground beef option was described by a series of

attributes including fat content, price, and use of cloning. A likelihood ratio test indicates that

we can reject the null hypothesis that the estimated parameters are equivalent across all three

samples (P < 0.001). This provides evidence that that even after controlling for geographic

location, age, race, gender, and education by weighting, there are significant differences across

the KN, IRI, and Nielsen samples.

Table 34 translates the multinomial logit estimates into WTP for various beef attributes. WTP

for non-cloned vs. cloned ground beef in the KN and IRI samples is similar, but the Nielsen

sample is WTP $0.56 and $0.91 less than the IRI and Nielsen samples, respectively. It is

interesting that throughout the previous versions of the survey, the IRI sample exhibited higher

stated levels of concern for cloning, but in these choice questions on ground beef, WTP to avoid

cloned ground beef was not significantly higher than the KN sample than in the IRI sample.

Focusing on fat content, results indicate that the KN sample exhibited higher WTP for leanness,

but lower WTP for reductions in saturated fat content than the IRI and Nielsen samples. Results

from the KN sample imply that people are WTP about $0.05 increase for each one percent

increase in leanness, which is quite similar to the $0.04/lb estimate reported by Parcell and

Schroeder (2007), who obtained their estimate using actual market transactions and hedonic

price analysis. That the KN sample provides similar results to that obtained from real market

transactions provides some indication of the validity of the KN sample relative to the other two

samples.

6.11 Milk Choice-Based Conjoint Estimates

Table 35 shows the multinomial logit estimates fit to people‟s choices of which option of milk

they would buy (or none), where each milk option was described by a series of attributes

including fat content, price, and use of cloning. A likelihood ratio test indicates that we can

reject the null hypothesis that the estimated parameters are equivalent across all three samples (P

< 0.001). This provides evidence that that even after controlling for geographic location, age,

race, gender, and education by weighting, there are significant differences across the KN, IRI,

and Nielsen samples.

Table 36 shows the multinomial logit estimates translated into people‟s WTP for various milk

attributes. Unlike the case of beef discussed in the previous sub-section, the results here are

more similar to the rest of the analysis. In particular, WTP for non-cloned vs. cloned milk is

highest in the IRI sample and is lowest in the Nielsen sample.

Because of the strong interaction effect between organic milk purchases and concern for cloning

identified in a previous section, we modified the choice model fit to the IRI sample such that

preferences for cloning were conditioned on people‟s total volume of annual milk purchases (in

gallons) and the share of total purchases resulting from organic milk. The multinomial logit

37

estimates are shown in table 37 and the resulting WTP values are shown in table 38. Results in

table 38 show that WTP for non-cloned vs. cloned milk remains about $4.66 regardless of the

total amount of milk purchased (i.e., WTP is not sensitive to total annual milk purchases).

However, willingness-to-pay was strongly influenced by organic purchasing behavior. For

people who never buy organic milk, WTP for non-cloned milk vs. cloned milk is $4.49 and this

figure jumps to $7.88 for people who only buy organic milk. These findings suggest that

companies wishing to market “cloned free” milk will likely find it profitable to market to the

niche of consumers who are currently purchasing organic milk.

7. Conclusions

This report presented the results of three nationwide surveys on animal cloning conducted with

over 6,000 U.S. consumers.

Given the media attention devoted to the issue of cloning, one might suspect that people are

highly averse to the technology. The survey results, however, suggest a much more mixed

picture, with the public being evenly split on whether animal cloning is acceptable. For example,

in our survey of a random sample of U.S. citizens, we found that only 29% of the public thought

that cloned meat was unsafe to eat. Further, we found that only about 43% were unwilling to eat

meat or drink milk from cloned animals. Our findings are generally similar to those obtained by

previous opinion polls conducted on the issue. For example, our estimate on willingness-to-eat

falls in between the findings from a Pew study indicated that only 35% said they would never

buy meat from a cloned animal, and an IFIC (2007) study reporting that 53% of consumers said

they were either not too likely or not at all likely to purchase meat, milk, or eggs from the cloned

animals.

When asked which particular issues were of most concern related to animal cloning, we found

that concerns about food safety were least prominent. People were most concerned about animal

cloning because, “cloning is „unnatural because it is not a process that occurs in nature,” and

“animal cloning will lead to human cloning.” Only 13% of people believe that the most

problematic issue with animal cloning is that it is morally wrong. Although only a small portion

of the population believes morality to be the most troubling issue with animal cloning, people for

whom this is a primary concern, are much less willing to eat meat from cloned animals than

people who find other issues more problematic.

Comparing results across our three survey samples suggests that information can have a small

but significant influence on people‟s acceptance of cloning. For example, only 20.6% of people

in one sample (who were only given a two sentence definition describing cloning) agreed they

were willing to eat meat from cloned animals, but 34.1% and 30.8% of people in the other two

samples of consumers studied (who were provided a one-half page discussion on cloning)

indicated they were willing to eat meat from cloned animals.

Results also indicate slight differences in responses from “opt in” panels of consumers and true

random samples of consumers. There appeared to be a slight tendency for people in the “opt in”

panel to be more accepting of cloning than people in the random sample. One of the advantages

38

of the “opt in” panels employed in this study is that actual purchase information was available on

each household surveyed. There is a strong and statistically significant relationship between

actual organic purchases of milk and stated willingness to consume cloned milk. Holding total

milk purchases constant, people who bought more organic milk were much less willing to drink

cloned milk than people who bought less organic milk. Stated differently, those people who are

more interested in organic products (as measured via actual purchase behavior) are also more

concerned about cloning and are willing to pay higher amounts to avoid cloned products.

Although total milk consumption was unrelated to concerns for cloning, there is some evidence

that more frequent purchasers of fresh beef are more willing to eat meat from cloned animals as

compared to less frequent purchasers of fresh beef.

Our results revealed that people, on average, are willing to pay significant premiums to avoid

ground beef and milk from cloned animals. For example, the “average” person in the random

sample would be willing to pay a premium of up to $4.23 when purchasing a package of ground

beef to have ground beef come from a non-cloned vs. cloned animal. The willingness-to-pay

premiums to avoid cloning were significantly higher than that to change fat content in ground

beef and milk, and to avoid rBST use in milk. That is, use of cloning is apparently more

important to people than fat content or rBST use. Despite these findings, two important caveats

are in order. First, there is significant heterogeneity in people‟s valuations. For example, results

indicate that ninety-five percent of the population is willing to pay between -$5.99 and $13.25 to

avoid milk from cloned animals. On the one hand, this implies that not everyone is willing to

pay anywhere near the mean premium estimate. Indeed, 23% of the population is unwilling to

pay a premium for milk from a non-cloned animal over milk from a clone. Conversely, there are

some people willing to pay very large premiums for meat and milk from non-cloned animals,

suggesting the potential for viable niche marketing opportunities. For example, roughly 25% of

the population is willing to pay more than $7.00 to have milk from a non-cloned animal rather

than milk from a clone. Second, willingness-to-pay a market premiums to avoid cloned products

does not imply support for several cloning policies. For example, results from the random

sample of U.S. citizens indicates that willingness-to-pay for a mandatory tracking policy on

cloned animals and willingness-to-pay for a ban on animal cloning is effectively zero. The only

policy to receive majority support was a mandatory labeling policy on meat and milk from

cloned animals.

39

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41

Table 1. Characteristics of Survey Respondents in KN sample

Variable Definition Unweighted

mean

Weighted

mean

Age age in years 49.695 46.513

Treatmenta 1 if treatment1; 0 if treatment2 0.498 0.498

Gender 1 if female; 0 if male 0.492 0.517

Income annual household income in $1,000s 63.055 58.699

Internet 1 if household internet access; 0 otherwise 0.697 0.613

NoHS 1 if less than high school; 0 otherwise 0.101 0.138

HS 1 if high school; 0 otherwise 0.316 0.310

SomeCollege 1 if some college; 0 otherwise 0.274 0.279

Bachelors 1 if Bachelor‟s degree or higher; 0 otherwise 0.309 0.273

White 1 if white, non-hispanic; 0 otherwise 0.785 0.696

Black 1 if black, non-hispanic; 0 otherwise 0.069 0.111

Other 1 if other non-hispanic; 0 otherwise 0.039 0.054

Hispanic 1 if hispanic; 0 otherwise 0.076 0.127

Two-races 1 if 2+races, non-hispanic; 0 otherwise 0.031 0.011

Northeast 1 if in Northeast U.S Census Region; 0 otherwise 0.185 0.186

Midwest 1 if in Midwest U.S Census Region; 0 otherwise 0.225 0.222

South 1 if in South U.S Census Region; 0 otherwise 0.365 0.367

West 1 if in West U.S Census Region; 0 otherwise 0.224 0.225

Meat:Never 1 if never purchase meat; 0 otherwise 0.035 0.041

Meat:Yearly 1 if purchase meat a few times a year; 0 otherwise 0.090 0.096

Meat:Monthly 1 if purchase meat about once a month; 0 otherwise 0.278 0.301

Meat:Weekly 1 if purchase meat about once a week; 0 otherwise 0.558 0.521

Meat:Day 1 if purchase meat every day; 0 otherwise 0.034 0.038

Farm 1 if own/work on ranch/farm; 0 otherwise 0.164 0.157

Pshopper 1 if primary shopper for food; 0 otherwise 0.688 0.670

Child 1 if child under age of 12 in household; 0 otherwise 0.237 0.257 aIn treatment 1, respondents received an information statement about cloning one week prior to taking the survey

and received the statement again while taking the survey; in treatment 2, respondents only received the information

statement while taking the survey.

42

Table 2. Knowledge of Assisted Reproduction Technologies That Are Used to Breed Animals

for Meat and Milk Production

Technology Pooled

Treatment 1

Prior

Information

Treatment 2

No Prior

Information

P-

Valuea

Artificial Insemination 2.43

(1.14)b

[22.9%]c

2.50

(1.15)

[21.3%]

2.37

(1.13)

[24.5%]

0.01

In vitro fertilization 2.20

(1.08)

[29.8%]

2.25

(1.09)

[28.1%]

2.16

(1.06)

[31.5%]

0.03

Biotechnology 2.04

(1.05)

[37.1%]

2.05

(1.07)

[38.2%]

2.04

(1.04)

[36.0%]

0.89

Embryo transfer 1.90

(1.05)

[45.2%]

1.94

(1.07)

[43.7%]

1.86

(1.04)

[46.6%]

0.08

Cloning 2.57

(1.03)

[10.6%]

2.70

(1.03)

[7.1%]

2.45

(1.01)

[14.09%]

<0.01

Number of Observations 2,256 1,123 1,133

Note: response to question: “Overall, how much have you heard or read about each of the following assisted

reproduction technologies that are sometimes used to breed animals for meat and milk production?” Response

categories were: 1 = nothing at all, 2 = a little, 3 = a moderate amount, 4 = quite a bit, 5 = a great deal. aP-value from two-sample t-test that means are equivalent across treatments

bNumbers in parentheses ( ) are standard deviations

cNumbers in brackets [ ] are the percentage of respondents indicating 1=nothing at all

43

Table 3. Willingness-to-Eat Cloned Meat and Milk

Statement Pooled Treat

1a

Treat

2a

P-

valueb

Percent

disagreec

Percent

neither

agree nor

disagreed

Percent

agreee

I am willing to eat meat

from cloned animals

2.72

(1.28)f

2.73

(1.30)

2.70

(1.26)

0.57 43.2% 26.0% 30.8%

The average American is

willing to eat meat from

cloned animals

2.76

(0.98)

2.79

(0.98)

2.73

(0.97)

0.15 35.1% 44.2% 20.7%

I am willing to eat meat

from the offspring of cloned

animals

2.72

(1.29)

2.74

(1.32)

2.70

(1.27)

0.43 43.0% 26.1% 30.9%

I am willing to consume

milk products from cloned

animals

2.70

(1.29)

2.70

(1.31)

2.69

(1.27)

0.85 44.4% 24.8% 30.8%

I am willing to consume

milk products from the

offspring of cloned animals

2.73

(1.29)

2.71

(1.31)

2.74

(1.26)

0.53 43.0% 25.7% 31.3%

If I learned that the meat

products I regularly

purchase came from cloned

animals, I would continue to

buy the meat products as

usual

2.78

(1.29)

2.82

(1.30)

2.74

(1.29)

0.13 41.4% 25.7% 32.9%

If I learned that the milk

products I regularly

purchase came from cloned

animals, I would continue to

buy the milk products as

usual

2.78

(1.31)

2.79

(1.33)

2.77

(1.29)

0.65 42.1% 24.6% 33.3%

Note: response to question, “To what extent do you agree or disagree with each of the following statements?”

Response categories were: 1=strongly disagree, 2= somewhat disagree, 3=neither agree nor disagree, 4=somewhat

agree, and 5=strongly agree. aIn treatment 1, respondents received an information statement about cloning one week prior to taking the survey

and received the statement again while taking the survey; in treatment 2, respondents only received the information

statement while taking the survey. bP-value from two-sample t-test of the hypothesis that means are equivalent across treatments

cPercentage of respondents in the pooled sample indicating 1=strongly disagree or 2= somewhat disagree

dPercentage of respondents in the pooled sample indicating 3=neither agree nor disagree

ePercentage of respondents in the pooled sample indicating 4=somewhat agree or 5=strongly agree

fNumbers in parentheses are standard deviations

44

Table 4. Beliefs about Safety and Acceptability of Cloned Meat and Milk

Statement Pooled Treat

1a

Treat

2a

P-

valueb

Percent

disagreec

Percent

neither

agree nor

disagreed

Percent

agreee

Some of the meat currently

sold in grocery stores is

from cloned animals or their

offspring

2.79

(0.88)f

2.79

(0.87)

2.79

(0.90)

0.99 27.4% 57.5% 15.1%

Animal cloning is

unacceptable

3.03

(1.26)

3.03

(1.29)

3.03

(1.24)

0.94 34.4% 33.7% 31.9%

Animal cloning will result in

beneficial outcomes to me

2.71

(1.09)

2.75

(1.10)

2.66

(1.07)

0.05 35.8% 43.6% 20.6%

The meat from cloned

animals is safe to eat

2.94

(1.12)

2.96

(1.16)

2.93

(1.08)

0.47 29.2% 41.2% 29.6%

In general, the meat and

milk I buy from grocery

stores is safe to eat

3.68

(0.92)

3.72

(0.90)

3.64

(0.95)

0.05 10.3% 26.1% 63.6%

Note: response to question, “To what extent do you agree or disagree with each of the following statements?”

Response categories were: 1=strongly disagree, 2= somewhat disagree, 3=neither agree nor disagree, 4=somewhat

agree, and 5=strongly agree. aIn treatment 1, respondents received an information statement about cloning one week prior to taking the survey

and received the statement again while taking the survey; in treatment 2, respondents only received the information

statement while taking the survey bP-value from two-sample t-test of the hypothesis that means are equivalent across treatments

cPercentage of respondents in the pooled sample indicating 1=strongly disagree or 2= somewhat disagree

dPercentage of respondents in the pooled sample indicating 3=neither agree nor disagree

ePercentage of respondents in the pooled sample indicating 4=somewhat agree or 5=strongly agree

fNumbers in parentheses are standard deviations

45

Table 5. Perceptions about the Federal Government and Cloned Meat and Milk

Statement Pooled Treat

1a

Treat

2a

P-

valueb

Percent

disagreec

Percent

neither

agree nor

disagreed

Percen

t agreee

The U.S. government is

doing everything it can to

ensure the safety of food

products

2.80

(1.12)f

2.81

(1.11)

2.78

(1.14)

0.46 40.7% 29.7% 29.6%

The U.S. government can

trace the meat from cloned

animals back to the farm on

which the animal lived

2.98

(1.05)f

2.98

(1.06)

2.98

(1.05)

0.87 27.6% 42.8% 29.6%

Animal cloning is carefully

regulated by the U.S.

government

2.71

(1.01)

2.75

(1.01)

2.68

(1.01)

0.14 37.3% 42.7% 20.0%

I trust the U.S. government

to properly regulate the use

of animal cloning

2.60

(1.15)

2.62

(1.17)

2.57

(1.13)

0.30 47.1% 29.0% 24.0%

I trust information about

cloning from the U.S.

Department of Agriculture

(USDA)

2.76

(1.16)

2.79

(1.18)

2.74

(1.13)

0.33 40.0% 30.7% 29.3%

I trust information about

cloning from the U.S. Food

and Drug Administration

(FDA)

2.74

(1.15)

2.75

(1.16)

2.73

(1.14)

0.62 41.3% 29.8% 28.8%

I trust information about

cloning from U.S.

Environmental Protection

Agency (EPA)

2.70

(1.14)

2.73

(1.14)

2.67

(1.14)

0.20 41.7% 32.2% 26.1%

I trust information about

cloning from University

scientists and researchers

2.89

(1.12)

2.92

(1.11)

2.86

(1.12)

0.25 34.5% 33.5% 32.0%

Note: response to question, “To what extent do you agree or disagree with each of the following statements?”

Response categories were: 1=strongly disagree, 2= somewhat disagree, 3=neither agree nor disagree, 4=somewhat

agree, and 5=strongly agree. aIn treatment 1, respondents received an information statement about cloning one week prior to taking the survey

and received the statement again while taking the survey; in treatment 2, respondents only received the information

statement while taking the survey bP-value from two-sample t-test of the hypothesis that means are equivalent across treatments

cPercentage of respondents in the pooled sample indicating 1=strongly disagree or 2= somewhat disagree

dPercentage of respondents in the pooled sample indicating 3=neither agree nor disagree

ePercentage of respondents in the pooled sample indicating 4=somewhat agree or 5=strongly agree

fNumbers in parentheses are standard deviations

46

Table 6. Relative Importance of Competing Objections to Cloning: Logit and Random

Parameter Logit Estimates fit to Paired Comparison Choices

Variable

Econometric

Estimates

Importance

Scores

Logit RPL

Meana

RPL

St.Dev.b Logit RPL

Intercept (order effect) -0.056

(0.032)c

-0.103*

(0.034)

1.265*

(0.072)

Cloning is “unnatural” because it is not a

process that occurs in nature

0.543*d

(0.050)

0.688*

(0.049)

1.759*

(0.049)

24.5% 23.9%

Animal cloning will lead to human

cloning

-0.073

(0.059)

-0.087

(0.060)

2.630*

(0.047)

13.2% 20.6%

Cloning results in animals being viewed

as “objects‟ to be produced as opposed

to being valuable in and of themselves

-0.060

(0.042)

-0.160*

(0.039)

1.966*

(0.001)

13.4% 14.9%

Animal cloning is morally wrong -0.476*

(0.071)

-0.929*

(0.074)

2.632*

(0.062)

8.8% 13.1%

Cloning will reduce genetic diversity to

an unacceptable level

-0.081

(0.045)

-0.142*

(0.042)

1.269*

(0.057)

13.1% 10.5%

The scientists and biotechnology

companies who developed cloning

technology cannot be trusted to look out

for my best interest

0 0 0

14.2% 7.7%

Cloning will result in unhealthy farm

animals

-0.525*

(0.053)

-0.747*

(0.051)

0.916*

(0.058)

8.4% 5.1%

Meat and milk from clones and their

offspring is unsafe to eat

-1.208*

(0.066)

-1.844*

(0.072)

1.845*

(0.069)

4.3% 4.2%

aThe estimates refer to the estimated mean in the population from the random parameter logit model

bThe estimates refers to the estimated standard deviation in the population from the random parameter logit model

cNumbers in parentheses are standard errors

dOne asterisk represents parameter is statistically different than zero at the 0.05 level or lower

Notes: Results based on 17,434 choices made by 2,231 individuals; Log-likelihood function value for logit was -

11052.71 and for random parameter logit was -9826.55; a likelihood ratio test could not reject the hypothesis that

the parameters were the same across the two information treatments

47

Cloning is “unnatural” because it is not a process that occurs in

nature, 23.9%

Animal cloning will lead to human cloning, 20.6%

Cloning results in animals being viewed as “objects’ to be

produced as opposed to being

valuable in and of themselves, 14.9%

Animal cloning is morally wrong, 13.1%

Cloning will reduce genetic diversity to an unacceptable

level, 10.5%

The scientists and biotechnology companies who developed cloning technology

cannot be trusted to look out for my best interest, 7.7%

Cloning will result in unhealthy

farm animals, 5.1%

Meat and milk from clones and their offspring is unsafe to eat,

4.2%

Figure 1. Relative Importance of Competing Objections to Cloning

48

Table 7. Bivariate Correlations between Responses to Statements Related to the Acceptability

of Cloning

Some of

the meat

currently

sold in

grocery

stores is

from

cloned

animals

or their

offspring

The U.S.

governm

ent is

doing

everythin

g it can to

ensure

the safety

of food

products

I trust

informati

on about

cloning

from the

(USDA)

I am

willing to

eat meat

from

cloned

animals

The meat

from

cloned

animals

is safe to

eat

Some of the meat currently sold

in grocery stores is from cloned

animals or their offspring

1.00*a

The U.S. government is doing

everything it can to ensure the

safety of food products

0.16* 1.00

*

I trust information about cloning

from the U.S. Department of

Agriculture (USDA)

0.23* 0.66

* 1.00

*

I am willing to eat meat from

cloned animals

0.29* 0.45

* 0.62

* 1.00

*

The meat from cloned animals is

safe to eat

0.29* 0.51

* 0.65

* 0.79

* 1.00

*

Animal cloning is unacceptable -0.07* -0.22

* -0.35

* -0.55

* -0.48

*

Note: statistics are correlations between responses to questions, “To what extent do you agree or disagree with each

of the following statements?” Response categories were: 1=strongly disagree, 2= somewhat disagree, 3=neither

agree nor disagree, 4=somewhat agree, and 5=strongly agree. aOne asterisk implies that the parameter is statistically different than zero at the 0.05 level or lower.

49

Table 8. Bivariate Correlations between Responses to Statements Related to the Acceptability

of Cloning

Responses to Agree/Disagree Statements

a

Relative Importance of

Objection to Cloningb

Some of

the meat

currently

sold in

grocery

stores is

from

cloned

animals

or their

offspring

The U.S.

governm

ent is

doing

everythin

g it can

to ensure

the

safety of

food

products

I trust

informati

on about

cloning

from the

USDA

I am

willing

to eat

meat

from

cloned

animals

The meat

from

cloned

animals

is safe to

eat

Animal

cloning

is

unaccept

able

Animal cloning is morally

wrong

-0.07*c

-0.07* -0.13

* -0.24

* -0.21

* 0.21

*

Meat and milk from clones and

their offspring is unsafe to eat

-0.11* -0.12

* -0.12

* -0.16

* -0.16

* 0.10

*

Animal cloning will lead to

human cloning

0.04 0.04 0.06* 0.09

* 0.08

* -0.04

Cloning will result in unhealthy

farm animals

-0.05* -0.13

* -0.13

* -0.13

* -0.13

* 0.03

Cloning is “unnatural” because

it is not a process that occurs in

nature

-0.06* 0.02 -0.01 -0.01 0.00 -0.01

Cloning will reduce genetic

diversity to an unacceptable

level

0.02 -0.03 0.01 0.04 0.02 -0.06*

Cloning results in animals being

viewed as “objects‟ to be

produced as opposed to being

valuable in and of themselves

0.12* 0.12

* 0.16

* 0.20

* 0.18

* -0.14

*

The scientists and

biotechnology companies who

developed cloning technology

cannot be trusted to look out for

my best interest

0.00 -0.14* -0.13

* -0.10

* -0.11

* 0.05

*

aResponses to questions, “To what extent do you agree or disagree with each of the following statements?”

bRelative importance of competing objections to cloning determined by calculating posterior probabilities from the

random parameter logit model fit to paired comparison choice data. cOne asterisk implies the parameter is statistically different than zero at the 0.05 level or lower.

50

Table 9. Relationship between Socio-Economic Characteristics and Cloning Concerns: Ordered

Probit Estimates

Dependent Variablea

Variable

I am

willing to

eat meat

from

cloned

animals

Some of

the meat

currently

sold in the

grocery

stores is

from

cloned

animals or

their

offspring

The U.S.

governme

nt is doing

everything

it can to

ensure the

safety of

food

products

The meat

from

cloned

animals is

safe to eat

Animal

cloning is

unaccepta

ble

I trust

informatio

n about

cloning

from the

(USDA)

Threshold Parameter1 0.618*b

(0.273)c

1.049*

(0.281)

0.433

(0.269)

0.800*

(0.272)

1.201*

(0.271)

0.511

(0.270)

Threshold Parameter2 -0.511*

(0.024)

-0.559*

(0.029)

-0.790*

(0.03)

-0.499*

(0.026)

-0.662*

(0.029)

-0.632*

(0.027)

Threshold Parameter3 -1.23*

(0.033)

-2.237*

(0.044)

-1.581*

(0.037)

-1.653*

(0.039)

-1.578*

(0.038)

-1.462*

(0.036)

Threshold Parameter4 -2.198*

(0.047)

-3.340*

(0.073)

-2.713*

(0.054)

-2.611*

(0.051)

-2.076*

(0.043)

-2.629*

(0.054)

Age 0.004*

(0.002)

0.003

(0.002)

0.003

(0.002)

0.006*

(0.002)

-0.003*

(0.002)

0.000

(0.002)

Treatment 0.018

(0.045)

-0.014

(0.047)

0.017

(0.045)

0.037

(0.045)

0.003

(0.045)

0.034

(0.045)

Gender -0.454*

(0.049)

-0.157*

(0.05)

-0.232*

(0.048)

-0.363*

(0.049)

0.336*

(0.049)

-0.276*

(0.048)

Income 0.002*

(0.001)

-0.001

(0.001)

0.001

(0.001)

0.001*

(0.001)

-0.001

(0.001)

0.001

(0.001)

Internet 0.240*

(0.055)

0.187*

(0.057)

0.200*

(0.054)

0.250*

(0.055)

-0.185*

(0.055)

0.252*

(0.054)

NoHSd 0.023

(0.087)

0.005

(0.09)

0.199*

(0.086)

-0.117

(0.087)

0.045

(0.087)

0.059

(0.086)

HSd -0.116

(0.067)

-0.113

(0.069)

0.097

(0.066)

-0.214*

(0.066)

0.184*

(0.067)

-0.034

(0.066)

SomeColleged 0.037

(0.064)

-0.048

(0.066)

0.083

(0.063)

0.024

(0.064)

0.037

(0.064)

-0.049

(0.064)

Whitee 0.056

(0.218)

-0.108

(0.223)

0.129

(0.214)

-0.009

(0.216)

-0.210

(0.213)

0.112

(0.214)

Blacke -0.220

(0.228)

0.126

(0.232)

0.030

(0.223)

-0.442*

(0.225)

-0.283

(0.223)

-0.079

(0.224)

Othere -0.143

(0.237)

0.133

(0.243)

0.187

(0.233)

-0.362

(0.235)

0.01

(0.233)

-0.006

(0.234)

51

Hispanice -0.15

(0.227)

-0.068

(0.232)

0.152

(0.222)

-0.233

(0.224)

-0.049

(0.222)

0.184

(0.223)

Northeastf -0.079

(0.072)

0.235*

(0.075)

0.03

(0.072)

-0.070

(0.072)

0.120

(0.072)

0.091

(0.072)

Midwestf -0.014

(0.07)

0.091

(0.072)

0.027

(0.069)

0.009

(0.070)

0.122

(0.070)

0.020

(0.070)

Southf -0.143*

(0.063)

0.136*

(0.065)

0.003

(0.062)

-0.123*

(0.063)

0.230*

(0.063)

-0.069

(0.062)

Meat:Neverg -0.304

(0.164)

-0.132

(0.169)

-0.200

(0.163)

-0.038

(0.163)

0.067

(0.165)

-0.038

(0.163)

Meat:Yearlyg -0.227

(0.138)

0.037

(0.144)

0.207

(0.137)

0.132

(0.138)

0.088

(0.14)

0.075

(0.138)

Meat:Monthlyg -0.025

(0.124)

0.005

(0.130)

0.148

(0.124)

0.137

(0.124)

0.223

(0.126)

0.157

(0.124)

Meat:Weeklyg 0.039

(0.121)

0.073

(0.127)

0.181

(0.120)

0.197

(0.121)

0.076

(0.123)

0.220

(0.121)

Farm 0.022

(0.063)

-0.004

(0.065)

0.016

(0.062)

0.059

(0.063)

-0.111

(0.063)

0.073

(0.062)

Pshopper 0.038

(0.054)

0.046

(0.056)

0.089

(0.054)

0.086

(0.054)

-0.132*

(0.055)

0.123

(0.054)

Child -0.072

(0.055)

-0.083

(0.057)

-0.006

(0.055)

-0.108*

(0.055)

0.105

(0.055)

-0.068

(0.055)

Log-Likelihood -3,322.4 -2,613.0 -3,276.8 -3,118.5 -3,341.7 -3,259.7

Number of

Observations

2,216 2,214 2,219 2,217 2,200 2,218

aDependent variable is response to question, “To what extent do you agree or disagree with each of the following

statements?” Response categories were: 1=strongly disagree, 2= somewhat disagree, 3=neither agree nor disagree,

4=somewhat agree, and 5=strongly agree. bOne asterisk indicates that the parameter is statistically different than zero at the 0.05 level or lower.

cNumbers in parentheses are standard errors

dParameter estimate compared to education of Bachelor‟s degree or higher

eParameter estimate compared to ethnicity of 2+ Races, non-hispanic

fParameter estimate compared to residents in West U.S Census Region

gParameter estimate compared to purchasing meat every day

52

Table 10. Food Values: Logit and Random Parameter Logit Estimates fit to Paired Comparison

Choices

Variable

Econometric

Estimates

Importance

Scores

Logit RPL

Meana

RPL

St.Dev.b Logit RPL

Constant 0.149*d

(0.028)c

0.172*

(0.026)

0.489*

(0.019)

Naturalness (extent to which food is

produced without modern

technologies)

0.243*

(0.067)

0.135*

(0.06)

1.892*

(0.055)

4.2% 6.3%

Taste (extent to which consumption

of the food is appealing to the

senses)

1.608*

(0.069)

1.699*

(0.059)

1.085*

(0.048)

16.4% 12.7%

Price (the price that is paid for the

food)

1.094*

(0.062)

1.080*

(0.052)

1.352*

(0.048)

9.8% 8.7%

Safety (extent to which consumption

of food will not cause illness)

2.310*

(0.064)

2.753*

(0.065)

2.043*

(0.070)

33.1% 35.5%

Convenience (ease with which food

is cooked and/or consumed)

0.346*

(0.056)

0.328*

(0.046)

1.565*

(0.051)

4.6% 5.5%

Nutrition (amount and type of fat,

protein, vitamins, etc.)

1.502*

(0.053)

1.679*

(0.048)

1.564*

(0.053)

14.7% 15.8%

Tradition (preserving traditional

consumption patterns)

-0.058*

(0.051)

-0.093*

(0.042)

1.248*

(0.047)

3.1% 2.9%

Origin (where the agricultural

commodities were grown)

0.156*

(0.049)

0.010

(0.041)

1.629*

(0.053)

3.8% 4.4%

Fairness (the extent to which all

parties involved in the production of

the food equally benefit)

-0.091*

(0.046)

-0.250*

(0.04)

1.451*

(0.050)

3.0% 3.1%

Appearance (extent to which food

looks appealing)

0.190*

(0.045)

0.156*

(0.035)

1.174*

(0.045)

4.0% 3.5%

Environmental Impact (effect of food

production on the environment)

0 0 0 3.3% 1.7%

aThe estimates refer to the estimated mean in the population from the random parameter logit model

bThe estimates refers to the estimated standard deviation of the food value in the population from the random

parameter logit model cNumbers in parentheses are standard errors

dOne asterisk implies that the parameter is statistically different than zero at the 0.05 level or lower.

Notes: Results based on 24,665 choices made by 2,255 individuals; Log-likelihood function values for logit and

random parameter logit models are -13,785.58 and -12,890.40, respectively; a likelihood ratio test could not reject

the hypothesis that the parameters were the same across the two information treatments

53

Safety , 35.5%

Nutrition , 15.8%Taste, 12.7%

Price, 8.7%

Naturalness, 6.3%

Convenience, 5.5%

Origin , 4.4%

Appearance , 3.5%

Fairness, 3.1%

Tradition , 2.9% Environmental Impact , 1.7%

Figure 2. Relative Importance of Competing Food Values

54

Table 11. Bivariate Correlations between Responses to Statements Related to the Acceptability

of Cloning

Responses to Agree/Disagree Statements

a

Relative

Importance of

Food Valuesb

Some of

the meat

currently

sold in

grocery

stores is

from

cloned

animals or

their

offspring

The U.S.

governme

nt is doing

everythin

g it can to

ensure the

safety of

food

products

I trust

informatio

n about

cloning

from the

USDA

I am

willing to

eat meat

from

cloned

animals

The meat

from

cloned

animals is

safe to eat

Animal

cloning is

unaccepta

ble

Naturalness 0.01 -0.14*c

-0.09* -0.08

* -0.09

* 0.04

Taste 0.04 0.01 0.09* 0.08

* 0.08

* -0.03

Price 0.00 0.07* 0.07

* 0.05

* 0.06

* -0.05

*

Safety -0.04 0.00 -0.05* -0.03 -0.04 0.05

*

Convenience 0.02 0.04* 0.06

* 0.05

* 0.05

* -0.05

*

Nutrition 0.01 0.02 0.02 -0.01 0.02 -0.05*

Tradition 0.02 0.01 0.00 -0.03 -0.02 0.04*

Origin 0.01 -0.13* -0.08

* -0.10

* -0.10

* -0.02

Fairness 0.03 -0.02 0.01 0.00 0.00 0.02

Appearance 0.08* 0.03 0.03 0.05

* 0.04 -0.04

*

Environmental

Impact 0.05

* -0.03 0.03 0.01 0.02 -0.03

aResponses to questions, “To what extent do you agree or disagree with each of the following statements?”

bRelative importance of competing food values determined by calculating posterior probabilities from the random

parameter logit model fit to paired comparison choice data. cOne asterisk implies that the parameter is statistically different than zero at the 0.05 level or lower.

55

Table 12. Percentage of Respondents Voting in Favor of Three Policies Related to Cloning at

Seven Price Levels

Percent Voting in Favor of . . .

Percent

Increase in

Food Prices

Mandatory

tracking of

cloned animals

Mandatory

labeling of

meat and milk

from cloned

animals

Ban on

practice of

animal cloning

5% 57.1% 65.0% 54.5%

10% 53.8% 63.9% 44.3%

15% 46.1% 52.1% 39.9%

25% 32.4% 46.7% 42.1%

50% 27.2% 38.6% 33.7%

75% 29.5% 31.4% 31.8%

100% 36.5% 33.2% 32.9% Note: The approximate number of observations in each cell is 315

56

Table 13. Probability of Affirmative Vote on Three Cloning Policies: Logit Estimates

Variable

Mandatory

tracking of

cloned animals

Mandatory

labeling of

cloned meat

and milk

Ban on

practice of

animal cloning

Constant (utility of policy vs. no policy) -0.012

(0.067)a

0.468*

(0.066)

-0.103

(0.068)

Percentage Price Increase -0.009*b

(0.001)

-0.015*

(0.001)

-0.008*

(0.001)

Willingness-to-Pay -1.3%

[-15.0%, 12.0%]

32.1%

[22.6%, 43.2%]

-13.2%

[-32.7%, 2.9%]

Log-Likelihood -1,469.5 -1,473.7 -1,466.4

Number of Observations 2,220 2,219 2,214 aNumbers in parentheses are standard errors.

bOne asterisk implies the parameter is statistically different than zero at the 0.05 level or lower

57

25%

30%

35%

40%

45%

50%

55%

60%

65%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Pe

rce

nt

Vo

tin

g In

Fav

or

of

Po

licy

Percent Increase in Food Price

Mandatory tracking of cloned animals

Mandatory labeling of cloned meat and milk

Ban on practice of animal cloning

Figure 3. Predicted Probabilities of Voting In Favor of Three Cloning Policies as a Function of

the Change in Food Price Resulting from the Policy

58

Table 14. Ground Beef Conjoint Models: Multinomial and Random Parameter Logit Estimates

Attribute

Multi-

nomial

Logit

RPL

Meana

RPL

St.Dev.b

Clone vs. None -0.967*d

(0.185)c

0.929*

(0.277)

0.112*

(0.077)

Offspring of Clone vs. None 0.649*

(0.185)

1.200*

(0.279)

0.593*

(0.077)

Non-Clone vs. None 1.357*

(0.185)

5.746*

(0.296)

3.922*

(0.098)

Percent Leanness 0.030*

(0.002)

0.057*

(0.003)

0.067*

(0.002)

Percent Saturated Fat 0.090*

(0.002)

-0.197*

(0.006)

0.056*

(0.011)

Price -0.559*

(0.011)

-1.140*

(0.019)

0

aThe estimates refer to the estimated mean in the population from the random parameter logit model

bThe estimates refers to the estimated standard deviation in the population from the random parameter logit model

cNumbers in parentheses are standard errors

dOne asterisk represents parameter is statistically different than zero at the 0.05 level or lower

Notes: Results based on 26,536 choices made by 2,243 individuals; Log-likelihood function values for multinomial

logit and random parameter logit models are -24,381.91 and -14,897.62, respectively.

59

Table 15. Willingness-to-Pay for Selected Ground Beef Attributes Calculated from Conjoint

Estimates

Willingness-to-Pay ($/choice) for . . . MNL

Mean

RPL

Mean

RPL

St.Dev.

Non-Clone vs. Cloned $4.16 $4.23 $3.44

Non-Clone vs. Offspring of Clone $3.59 $3.99 $3.48

Offspring of Clone vs. Clone $0.57 $0.24 $0.53

Increase in Leanness (90% vs. 80%) $0.54 $0.50 $0.59

Reduction in Saturated Fat (5% vs. 10%) $0.80 $0.86 $0.25

60

Figure 4. Example Output from Ground Beef Market Simulator

61

Table 16. Milk Conjoint Models: Multinomial and Random Parameter Logit Estimates

Variable

Multi-

nomial

Logit

RPL

Meana

RPL

St.Dev.b

Clone vs. None 0.664*d

(0.035)c

1.668*

(0.069)

2.232*

(0.051)

Offspring of Clone vs. None 0.530*

(0.035)

1.591*

(0.070)

2.539*

(0.060)

Non-Clone vs. None 2.240*

(0.034)

4.333*

(0.069)

2.829*

(0.049)

rBST vs. no RBST -0.602*

(0.017)

-1.323*

(0.037)

1.626*

(0.049)

Fat Content: 1% vs. Skim -0.123*

(0.024)

-0.274*

(0.037)

0.550*

(0.057)

Fat Content: 2% vs. Skim 0.261*

(0.023)

0.285*

(0.039)

1.197*

(0.048)

Fat Content: Whole vs. Skim 0.171*

(0.023)

-0.545*

(0.050)

2.054*

(0.051)

Price -0.378*

(0.006)

-0.734*

(0.010)

aThe estimates refer to the estimated mean in the population from the random parameter logit model

bThe estimates refers to the estimated standard deviation in the population from the random parameter logit model

cNumbers in parentheses are standard errors

dOne asterisk represents parameter is statistically different than zero at the 0.05 level or lower

Notes: Results based on 35,373 choices made by 2,237 individuals; Log-likelihood function values for multinomial

logit and random parameter logit models are -39,091.28 and -26,187.91, respectively.

62

Table 17. Willingness-to-Pay for Selected Milk Attributes Calculated from Conjoint Estimates

Willingness-to-Pay ($/choice) for . . . MNL

Mean

RPL

Mean

RPL

St.Dev.

Non-Clone vs. Cloned $4.17 $3.63 $4.91

Non-Clone vs. Offspring of Clone $4.53 $3.73 $5.18

Offspring of Clone vs. Clone -$0.35 -$0.10 $4.60

No rBST vs. rBST $1.59 $1.80 $2.21

63

Figure 5. Example Output from Milk Market Simulator

64

Figure 6. Example Output from Milk Market Simulator

65

Table 18. Characteristics of Survey Respondents from Three Survey Samples

Variable Percent in Each Category U.S.

Census

KN

Un-

weighted

IRI

Un-

weighted

Nielsen

Un-

weighted

Age1 18-34 years 30.7% 20.9% 16.7% 15.0%

Age2 35-44 years 19.2% 18.4% 23.2% 18.4%

Age3 45-54 years 19.5% 19.7% 24.4% 26.7%

Age4 55-64 years 14.5% 21.9% 18.7% 25.9%

Age5 65+ years 16.2% 19.1% 17.0% 14.0%

HS High School Degree or Less 46.6% 41.7% 19.5% 33.0%

SomeCollege Some College 27.2% 27.4% 38.6% 33.3%

Bachelors Bachelor‟s degree or higher 26.2% 30.9% 42.0% 33.7%

Female Female 51.6% 49.2% 78.2% 68.3%

White White, non-Hispanic 69.1% 78.5% 76.8% 74.7%

Black Black, non-Hispanic 11.7% 6.9% 11.8% 10.0%

Hispanic Hispanic 13.3% 7.6% 5.6% 10.3%

Other Other race 6.0% 7.0% 5.9% 5.0%

Northeast Northeast U.S Census Region 18.1% 18.5% 20.3% 17.4%

Midwest Midwest U.S Census Region 22.0% 22.5% 23.7% 23.6%

South South U.S Census Region 36.6% 36.5% 35.5% 37.3%

West West U.S Census Region 23.2% 22.4% 20.5% 21.7%

Inc1 Annual HH income less than $25,000 25.3% 17.9% 18.6% 23.9%

Inc2 Annual HH income $25,000 to $99,999 55.6% 65.9% 65.8% 59.0%

Inc3 Annual HH income $100,000 or more 19.1% 16.2% 15.6% 17.2%

Meat:Never never purchase meat

3.5% 1.2% 1.5%

Meat:Yearly purchase meat a few times a year

9.0% 6.9% 6.4%

Meat:Monthly purchase meat about once a month

27.8% 31.0% 29.2%

Meat:Weekly purchase meat about once a week

55.8% 58.5% 60.0%

Meat:Day purchase meat every day

3.4% 2.3% 2.9%

Farm Own/work on ranch/farm

16.4% 10.8% 8.7%

Pshopper Primary shopper for food

68.8% 97.2% 97.9%

Child Child under age of 12 in household

23.7% 29.0% 24.7%

N

2,256 1,691 2,120

66

Table 19. Food Values: Logit Estimates fit to Paired Comparison Choices: Comparison across

Three Survey Samples

Variable

Econometric

Estimates

Importance

Scores

KNa IRI

b Nielsen

c KN

a IRI

b Nielsen

c

Constant 0.149*c

(0.028)d

0.186*

(0.017)

0.094*

(0.015)

Naturalness (extent to which food is

produced without modern

technologies)

0.243*

(0.067)

0.037

(0.051)

0.059

(0.051)

4.2% 3.8% 3.6%

Taste (extent to which consumption

of the food is appealing to the

senses)

1.608*

(0.069)

1.445*

(0.053)

1.668*

(0.057)

16.4% 15.7% 18.0%

Price (the price that is paid for the

food)

1.094*

(0.062)

1.181*

(0.052)

1.205*

(0.055)

9.8% 12.1% 11.3%

Safety (extent to which consumption

of food will not cause illness)

2.310*

(0.064)

2.015*

(0.058)

2.186*

(0.061)

33.1% 27.8% 30.2%

Convenience (ease with which food

is cooked and/or consumed)

0.346*

(0.056)

0.366*

(0.05)

0.566*

(0.054)

4.6% 5.4% 6.0%

Nutrition (amount and type of fat,

protein, vitamins, etc.)

1.502*

(0.053)

1.498*

(0.054)

1.335*

(0.056)

14.7% 16.6% 12.9%

Tradition (preserving traditional

consumption patterns)

-0.058*

(0.051)

-0.018

(0.050)

0.092

(0.053)

3.1% 3.6% 3.7%

Origin (where the agricultural

commodities were grown)

0.156*

(0.049)

-0.068

(0.051)

-0.012

(0.054)

3.8% 3.5% 3.4%

Fairness (the extent to which all

parties involved in the production of

the food equally benefit)

-0.091*

(0.046)

-0.133*

(0.051)

-0.098

(0.054)

3.0% 3.2% 3.1%

Appearance (extent to which food

looks appealing)

0.190*

(0.045)

0.192*

(0.049)

0.266*

(0.054)

4.0% 4.5% 4.4%

Environmental Impact (effect of food

production on the environment)

0 0 0 3.3% 3.7% 3.4%

a Results based on 24,665 choices; Log-likelihood function value = -13,785.58; a likelihood ratio test could not

reject the hypothesis that the parameters were the same across the two information treatments in the KN sample. bResults based on 18,601 choices; Log-likelihood function value = -10,709.4.

cResults based on 23,320 choices; Log-likelihood function value = -13,417.29.

cOne asterisk implies that the parameter is statistically different than zero at the 0.05 level or lower.

dNumbers in parentheses are standard errors.

Note: The log-likelihood function value for a model where parameters are pooled across all three samples is

-37,990.8 ( N=66,586). A likelihood ratio test indicates that we can reject the null hypothesis that parameters are

equal across all three samples (Chi-square value =157.05; df=22; P-value<0.001).

67

Table 20. Knowledge of Assisted Reproduction Technologies That Are Used to Breed Animals

for Meat and Milk Production from Three Survey Samples

Technology

KN

Treatment 1

Prior

Information

KN

Treatment 2

No Prior

Information

IRI Nielsen

Artificial Insemination 2.50

(1.15)

[21.3%]

2.37

(1.13)

[24.5%]

2.58

(1.24)

[22.4%]

2.44

(1.22)

[25.8%]

In vitro fertilization 2.25

(1.09)

[28.1%]

2.16

(1.06)

[31.5%]

2.36

(1.20)

[29.2%]

2.22

(1.19)

[34.0%]

Biotechnology 2.05

(1.07)

[38.2%]

2.04

(1.04)

[36.0%]

2.17

(1.13)

[34.2%]

2.02

(1.09)

[40.3%]

Embryo transfer 1.94

(1.07)

[43.7%]

1.86

(1.04)

[46.6%]

1.95

(1.13)

[46.9%]

1.85

(1.07)

[49.8%]

Cloning 2.70

(1.03)

[7.1%]

2.45

(1.01)

[14.09%]

2.79

(1.14)

[10.3%]

2.53

(1.11)

[16.4%]

Number of Observations 1,123 1,133 1,691 2,120

Note: response to question: “Overall, how much have you heard or read about each of the following assisted

reproduction technologies that are sometimes used to breed animals for meat and milk production?” Response

categories were: 1 = nothing at all, 2 = a little, 3 = a moderate amount, 4 = quite a bit, 5 = a great deal. aP-value from two-sample t-test that means are equivalent across treatments

bNumbers in parentheses ( ) are standard deviations

cNumbers in brackets [ ] are the percentage of respondents indicating 1=nothing at all

68

Table 21. Willingness-to-Eat Cloned Meat and Milk from Three Survey Samples

Statement KN

Pooled IRI

Nielsen

I am willing to eat meat from

cloned animals

2.72

(1.28)a

2.46

(1.24)

2.86

(1.33)

The average American is willing

to eat meat from cloned animals

2.76

(0.98)

2.58

(0.99)

2.72

(0.99)

I am willing to eat meat from the

offspring of cloned animals

2.72

(1.29)

2.48

(1.22)

2.85

(1.32)

I am willing to consume milk

products from cloned animals

2.70

(1.29)

2.47

(1.20)

2.87

(1.32)

I am willing to consume milk

products from the offspring of

cloned animals

2.73

(1.29)

2.56

(1.24)

2.87

(1.33)

If I learned that the meat

products I regularly purchase

came from cloned animals, I

would continue to buy the meat

products as usual

2.78

(1.29)

2.59

(1.30)

2.95

(1.34)

If I learned that the milk

products I regularly purchase

came from cloned animals, I

would continue to buy the milk

products as usual

2.78

(1.31)

2.62

(1.29)

2.93

(1.36)

Note: mean response to question, “To what extent do you agree or disagree with each of the following statements?”

Response categories were: 1=strongly disagree, 2= somewhat disagree, 3=neither agree nor disagree, 4=somewhat

agree, and 5=strongly agree. aNumbers in parentheses are standard deviations

Note: given the sample sizes and observed variability, the estimated means ratings are expected to be within plus or

minus roughly 0.07 of the true population means with 95% confidence.

69

Table 22. Willingness-to-Eat Cloned Meat and Milk from Three Survey Samples

Statement KN IRI Nielsen

Da

Nb

Ac

D

N A

D

N

A

I am willing to eat meat

from cloned animals

43.2% 26.0% 30.8% 48.1% 31.4% 20.6% 37.9% 27.9% 34.1%

The average American is

willing to eat meat from

cloned animals

35.1% 44.2% 20.7% 40.2% 44.4% 15.4% 39.2% 39.8% 21.1%

I am willing to eat meat

from the offspring of cloned

animals

43.0% 26.1% 30.9% 47.4% 31.4% 21.2% 38.2% 28.2% 33.6%

I am willing to consume

milk products from cloned

animals

44.4% 24.8% 30.8% 48.4% 31.4% 20.2% 38.1% 27.5% 34.4%

I am willing to consume

milk products from the

offspring of cloned animals

43.0% 25.7% 31.3% 45.9% 31.4% 22.8% 38.4% 26.4% 35.2%

If I learned that the meat

products I regularly

purchase came from cloned

animals, I would continue to

buy the meat products as

usual

41.4% 25.7% 32.9% 47.0% 26.3% 26.6% 36.4% 24.6% 39.0%

If I learned that the milk

products I regularly

purchase came from cloned

animals, I would continue to

buy the milk products as

usual

42.1% 24.6% 33.3% 44.2% 29.8% 26.0% 37.2% 24.3% 38.5%

Note: response to question, “To what extent do you agree or disagree with each of the following statements?”

Response categories were: 1=strongly disagree, 2= somewhat disagree, 3=neither agree nor disagree, 4=somewhat

agree, and 5=strongly agree. aPercentage of respondents in the pooled sample indicating 1=strongly disagree or 2= somewhat disagree

bPercentage of respondents in the pooled sample indicating 3=neither agree nor disagree

cPercentage of respondents in the pooled sample indicating 4=somewhat agree or 5=strongly agree

Note: given the sample sizes, the reported percentages are estimated to be within plus or minus about 2.2% of the

true population percentages with 95% confidence.

70

Table 23. Beliefs about Safety and Acceptability of Cloned Meat and Milk from Three Survey

Samples

Statement KN

Pooled IRI

Nielsen

Some of the meat currently

sold in grocery stores is from

cloned animals or their

offspring

2.79

(0.88)a

2.63

(0.94)

2.89

(0.94)

Animal cloning is unacceptable 3.03

(1.26)

3.34

(1.26)

3.01

(1.28)

Animal cloning will result in

beneficial outcomes to me

2.71

(1.09)

2.51

(1.09)

2.82

(1.14)

The meat from cloned animals

is safe to eat

2.94

(1.12)

2.78

(1.08)

3.10

(1.17)

In general, the meat and milk I

buy from grocery stores is safe

to eat

3.68

(0.92)

3.81

(0.92)

3.91

(0.89)

Note: mean response to question, “To what extent do you agree or disagree with each of the following statements?”

Response categories were: 1=strongly disagree, 2= somewhat disagree, 3=neither agree nor disagree, 4=somewhat

agree, and 5=strongly agree. aNumbers in parentheses are standard deviations

Note: given the sample sizes and observed variability, the estimated means ratings are expected to be within plus or

minus roughly 0.07 of the true population means with 95% confidence.

71

Table 24. Beliefs about Safety and Acceptability of Cloned Meat and Milk from Three Survey

Samples

Statement KN IRI Nielsen

Da

Nb

Ac

D

N

A

D

N

A

Some of the meat currently

sold in grocery stores is

from cloned animals or their

offspring

27.4% 57.5% 15.1% 32.0% 57.7% 10.4% 22.7% 59.7% 17.6%

Animal cloning is

unacceptable

34.4% 33.7% 31.9% 24.9% 35.1% 40.1% 35.5% 30.5% 34.0%

Animal cloning will result in

beneficial outcomes to me

35.8% 43.6% 20.6% 41.5% 43.4% 15.1% 33.2% 40.8% 26.0%

The meat from cloned

animals is safe to eat

29.2% 41.2% 29.6% 31.6% 47.0% 21.3% 24.8% 39.9% 35.3%

In general, the meat and

milk I buy from grocery

stores is safe to eat

10.3% 26.1% 63.6% 8.4% 22.2% 69.4% 6.9% 17.9% 75.2%

Note: response to question, “To what extent do you agree or disagree with each of the following statements?”

Response categories were: 1=strongly disagree, 2= somewhat disagree, 3=neither agree nor disagree, 4=somewhat

agree, and 5=strongly agree. aPercentage of respondents in the pooled sample indicating 1=strongly disagree or 2= somewhat disagree

bPercentage of respondents in the pooled sample indicating 3=neither agree nor disagree

cPercentage of respondents in the pooled sample indicating 4=somewhat agree or 5=strongly agree

Note: given the sample sizes, the reported percentages are estimated to be within plus or minus about 2.2% of the

true population percentages with 95% confidence.

72

Table 25. Perceptions about the Federal Government and Cloned Meat and Milk from Three

Survey Samples

Statement KN

Pooled IRI

Nielsen

The U.S. government is doing

everything it can to ensure the

safety of food products

2.80

(1.12)a

2.89

(1.14)

2.96

(1.19)

The U.S. government can trace

the meat from cloned animals

back to the farm on which the

animal lived

2.98

(1.05)

3.02

(1.05)

3.22

(1.07)

Animal cloning is carefully

regulated by the U.S.

government

2.71

(1.01)

2.56

(1.03)

2.82

(1.09)

I trust the U.S. government to

properly regulate the use of

animal cloning

2.60

(1.15)

2.65

(1.19)

2.57

(1.19)

I trust information about cloning

from the U.S. Department of

Agriculture (USDA)

2.76

(1.16)

2.72

(1.15)

2.72

(1.18)

I trust information about cloning

from the U.S. Food and Drug

Administration (FDA)

2.74

(1.15)

2.69

(1.14)

2.70

(1.19)

I trust information about cloning

from U.S. Environmental

Protection Agency (EPA)

2.70

(1.14)

2.73

(1.13)

2.69

(1.18)

I trust information about cloning

from University scientists and

researchers

2.89

(1.12)

2.89

(1.13)

3.00

(1.15)

Note: mean response to question, “To what extent do you agree or disagree with each of the following statements?”

Response categories were: 1=strongly disagree, 2= somewhat disagree, 3=neither agree nor disagree, 4=somewhat

agree, and 5=strongly agree. aNumbers in parentheses are standard deviations.

Note: given the sample sizes and observed variability, the estimated means ratings are expected to be within plus or

minus roughly 0.07 of the true population means with 95% confidence.

73

Table 26. Perceptions about the Federal Government and Cloned Meat and Milk from Three

Survey Samples

Statement KN IRI Nielsen

Da

Nb

Ac

D

N

A

D

N

A

The U.S. government is

doing everything it can to

ensure the safety of food

products

40.7% 29.7% 29.6% 34.4% 34.9% 30.7% 35.9% 26.4% 37.7%

The U.S. government can

trace the meat from cloned

animals back to the farm on

which the animal lived

27.6% 42.8% 29.6% 24.6% 45.6% 29.8% 20.6% 39.8% 39.6%

Animal cloning is carefully

regulated by the U.S.

government

37.3% 42.7% 20.0% 40.2% 45.2% 14.6% 33.0% 43.4% 23.6%

I trust the U.S. government

to properly regulate the use

of animal cloning

47.1% 29.0% 24.0% 44.6% 31.2% 24.2% 48.5% 27.3% 24.2%

I trust information about

cloning from the U.S.

Department of Agriculture

(USDA)

40.0% 30.7% 29.3% 38.8% 35.0% 26.2% 42.3% 31.0% 26.8%

I trust information about

cloning from the U.S. Food

and Drug Administration

(FDA)

41.3% 29.8% 28.8% 40.8% 34.2% 24.9% 42.2% 31.0% 26.8%

I trust information about

cloning from U.S.

Environmental Protection

Agency (EPA)

41.7% 32.2% 26.1% 37.9% 37.9% 24.2% 42.1% 32.0% 25.9%

I trust information about

cloning from University

scientists and researchers

34.5% 33.5% 32.0% 32.5% 37.7% 29.8% 30.9% 32.7% 36.5%

Note: response to question, “To what extent do you agree or disagree with each of the following statements?”

Response categories were: 1=strongly disagree, 2= somewhat disagree, 3=neither agree nor disagree, 4=somewhat

agree, and 5=strongly agree. aPercentage of respondents in the pooled sample indicating 1=strongly disagree or 2= somewhat disagree

bPercentage of respondents in the pooled sample indicating 3=neither agree nor disagree

cPercentage of respondents in the pooled sample indicating 4=somewhat agree or 5=strongly agree

Note: given the sample sizes, the reported percentages are estimated to be within plus or minus about 2.2% of the

true population percentages with 95% confidence.

74

Table 27. Relative Importance of Competing Objections to Cloning: Logit Model fit to Paired

Comparison Choices; Comparison of Three Samples

Variable

Econometric

Estimates

Importance

Scores

KNa

IRIb

Nielsenc

KN IRI Nielsen

Intercept (order effect) -0.056

(0.032)d

0.018*

(0.020)

-0.036*

(0.016)

Cloning is “unnatural” because it is not a

process that occurs in nature

0.543*e

(0.050)

0.660*

(0.051)

0.135*

(0.051)

24.5% 27.1% 22.0%

Animal cloning will lead to human

cloning

-0.073

(0.059)

-0.284*

(0.050)

-0.45*

(0.05)

13.2% 10.5% 12.2%

Cloning results in animals being viewed

as “objects‟ to be produced as opposed

to being valuable in and of themselves

-0.060

(0.042)

-0.020*

(0.062)

-0.321*

(0.051)

13.4% 13.7% 13.9%

Animal cloning is morally wrong -0.476*

(0.071)

-0.538*

(0.049)

-1.023*

(0.049)

8.8% 8.2% 6.9%

Cloning will reduce genetic diversity to

an unacceptable level

-0.081

(0.045)

-0.067*

(0.049)

-0.394*

(0.051)

13.1% 13.1% 13.0%

The scientists and biotechnology

companies who developed cloning

technology cannot be trusted to look out

for my best interest

0 0 0

14.2% 14.0% 19.2%

Cloning will result in unhealthy farm

animals

-0.525*

(0.053)

-0.425*

(0.049)

-0.796*

(0.051)

8.4% 9.2% 8.7%

Meat and milk from clones and their

offspring is unsafe to eat

-1.208*

(0.066)

-1.216*

(0.053)

-1.538*

(0.053)

4.3% 4.2% 4.1%

aResults based on 17,434 choices made by 2,231 individuals; Log-likelihood function value = -11,052.71; a

likelihood ratio test could not reject the hypothesis that the parameters were the same across the two information

treatments in the Knowledge Networks sample bResults based on 13,528 choices; Log-likelihood function value = -8,597.77.

cResults based on 16,960 choices; Log-likelihood function value = -10,670.71

dNumbers in parentheses are standard errors

eOne asterisk represents parameter is statistically different than zero at the 0.05 level or lower

Note: The log-likelihood function value for a model where parameters are pooled across all three samples is

-30,355.36 ( N=47,922). A likelihood ratio test indicates that we can reject the null hypothesis that parameters are

equal across all three samples (Chi-square value =68.34; df=16; P-value<0.001).

75

Table 28. Relationship between Stated and Actual Milk Purchases, Socio-Economic

Characteristics and Stated Willingness to Drink Cloned Milk: Ordered Probit Estimates for Three

Survey Samplesa

Variable KN

IRI

(stated milk

consumption)

IRI

(actual milk

consumption)

Nielsen

(stated milk

consumption)

Nielsen

(actual milk

consumption)

Intercept 0.927**b

(0.187)c

-0.071

(0.259)

0.859

(0.221)

0.718**

(0.195)

0.583**

(0.137)

Intercept2 -0.515**

(0.024)

-0.52**

(0.029)

-0.531

(0.029)

-0.492**

(0.025)

-0.488**

(0.025)

Intercept3 -1.199**

(0.033)

-1.443**

(0.044)

-1.417

(0.044)

-1.237**

(0.034)

-1.23**

(0.034)

Intercept4 -2.156**

(0.046)

-2.323**

(0.063)

-2.305

(0.064)

-2.032

(0.044)

-2.021**

(0.044)

Male 0.479**

(0.046)

0.126*

(0.06)

0.108

(0.061)

0.518

(0.050)

0.508**

(0.050)

Age1 -0.128

(0.078)

-0.098

(0.099)

-0.088

(0.102)

0.125

(0.082)

0.144

(0.082)

Age2 -0.101

(0.084)

-0.22*

(0.104)

-0.24*

(0.105)

-0.179

(0.083)

-0.165*

(0.082)

Age3 -0.003

(0.08)

-0.109

(0.099)

-0.141

(0.100)

-0.102

(0.078)

-0.098

(0.078)

Age4d

-0.047

(0.078)

0.050

(0.105)

0.038

(0.106)

-0.144

(0.084)

-0.143

(0.084)

Whitee

0.149

(0.096)

-0.008

(0.122)

-0.07

(0.131)

0.149

(0.101)

0.172

(0.101)

Blacke -0.127

(0.117)

-0.583**

(0.145)

-0.551**

(0.154)

-0.378**

(0.119)

-0.378**

(0.119)

Hispanice -0.04

(0.114)

-0.237

(0.141)

-0.362*

(0.149)

-0.080

(0.115)

-0.047

(0.115)

HSf

-0.199**

(0.062)

-0.215**

(0.075)

-0.274**

(0.076)

-0.188**

(0.061)

-0.194**

(0.061)

SomeCollegef 0.021

(0.063)

-0.191*

(0.078)

-0.192*

(0.079)

-0.139*

(0.065)

-0.143*

(0.065)

Inc1g

-0.306**

(0.083)

-0.209

(0.110)

-0.241*

(0.111)

-0.050

(0.082)

-0.077

(0.081)

Inc2g

-0.14*

(0.069)

0.026

(0.095)

-0.084

(0.097)

-0.042

(0.07)

-0.051

(0.07)

Northeasth

-0.086

(0.072)

-0.147

(0.091)

-0.179

(0.094)

-0.008

(0.073)

0.009

(0.073)

Midwesth 0.004

(0.07)

0.082

(0.087)

0.06

(0.088)

0.126

(0.071)

0.123

(0.07)

Southh -0.136*

(0.063)

0.155*

(0.078)

0.151

(0.08)

0.120

(0.063)

0.138*

(0.063)

76

Children -0.08

(0.058)

0.026

(0.073)

0.062

(0.074)

-0.010

(0.061)

0.001

(0.061)

Farm 0.034

(0.063)

0.241*

(0.101)

0.273**

(0.101)

-0.062

(0.084)

-0.060

(0.084)

Milk:Neveri -0.536**

(0.163)

0.561*

(0.239)

-0.693**

(0.189)

Milk:Yearlyi -0.443**

(0.157)

0.689**

(0.226)

-0.202

(0.168)

Milk:Monthlyi -0.116

(0.142)

1.061**

(0.19)

-0.080

(0.144)

Milk:Weeklyi -0.128

(0.135)

0.672**

(0.175)

-0.031

(0.134)

Milk purchases

(gallons/year)j

-0.001

(0.001)

Organic share of

milk purchasesk

-0.885**

(0.174)

Milk purchases

(purchase units/year)l

0.004

(0.002) aDependent variable is response to question, “To what extent do you agree or disagree with each of the following

statement? I am willing to consume milk products from cloned animals.” Response categories were: 1=strongly

disagree, 2= somewhat disagree, 3=neither agree nor disagree, 4=somewhat agree, and 5=strongly agree. bOne and two asterisks indicates statistical significance at the 0.05 and 0.01 levels, respectively

cNumbers in parentheses are standard errors

d Variable defined in table 18; Parameter estimates relative to age 65 and over

eParameter estimate compared to “other races”

fParameter estimate compared to education of Bachelor‟s degree or higher

gVariable defined in table 18; parameter estimate compared to households making more than $100,000/year

hParameter estimate compared to residents in West U.S Census Region

i Dummy variables, with parameter estimates compared to those who purchase milk every day

jAnnual volume (gallons) of milk purchased determined from scanner data

kShare of total annual volume of milk purchased (gallons) resulting from sales of organic milk

lAnnual volume (in units purchased – not controlling for unit size) of milk purchased determined from scanner data

77

Table 29. Relationship between Stated and Actual Meat Purchases, Socio-Economic

Characteristics and Stated Willingness to Eat Cloned Beef: Ordered Probit Estimates for Three

Survey Samplesa

Variable KN

IRI

(stated milk

consumption)

IRI

(actual milk

consumption)

Nielsen

(stated milk

consumption)

Nielsen

(actual milk

consumption)

Intercept 0.764**

(0.170)

0.497

(0.267)

0.527*

(0.217)

0.979**

(0.208)

0.387*

(0.167)

Intercept2 -0.510**

(0.024)

-0.405**

(0.025)

-0.411**

(0.026)

-0.459**

(0.024)

-0.455**

(0.024)

Intercept3 -1.224**

(0.033)

-1.309**

(0.042)

-1.278**

(0.042)

-1.224**

(0.034)

-1.214**

(0.034)

Intercept4 -2.186**

(0.047)

-2.129**

(0.060)

-2.108**

(0.061)

-2.009**

(0.044)

-1.99**

(0.043)

Male 0.434**

(0.046)

0.214**

(0.060)

0.195**

(0.061)

0.562**

(0.051)

0.585**

(0.051)

Age1 -0.083

(0.077)

0.053

(0.099)

0.007

(0.105)

0.126

(0.083)

0.137

(0.083)

Age2 -0.102

(0.084)

-0.194

(0.105)

-0.251*

(0.107)

-0.197*

(0.083)

-0.193*

(0.083)

Age3 0.005

(0.08)

-0.090

(0.100)

-0.091

(0.101)

-0.126

(0.079)

-0.113

(0.078)

Age4d

-0.043

(0.078)

0.033

(0.106)

0.011

(0.107)

-0.165

(0.084)

-0.17*

(0.084)

Whitee

0.174

(0.095)

-0.094

(0.123)

-0.133

(0.132)

0.173

(0.102)

0.186

(0.101)

Blacke -0.147

(0.116)

-0.558**

(0.147)

-0.578**

(0.155)

-0.299*

(0.119)

-0.295*

(0.119)

Hispanice -0.029

(0.112)

-0.341*

(0.143)

-0.380*

(0.150)

-0.022

(0.116)

-0.001

(0.115)

HSf

-0.142*

(0.062)

-0.314**

(0.076)

-0.287**

(0.077)

-0.169**

(0.061)

-0.165**

(0.061)

SomeCollegef 0.002

(0.063)

-0.208**

(0.079)

-0.195*

(0.079)

-0.124

(0.065)

-0.119

(0.065)

Inc1g

-0.327**

(0.083)

-0.016

(0.111)

-0.121

(0.112)

-0.047

(0.082)

-0.081

(0.081)

Inc2g

-0.155*

(0.069)

0.056

(0.095)

-0.025

(0.096)

-0.024

(0.070)

-0.029

(0.070)

Northeasth

-0.085

(0.072)

-0.182*

(0.092)

-0.177

(0.095)

0.004

(0.073)

0.002

(0.073)

Midwesth -0.032

(0.07)

0.123

(0.087)

0.134

(0.088)

0.118

(0.071)

0.128

(0.070)

Southh -0.136*

(0.063)

0.140

(0.078)

0.183*

(0.079)

0.128*

(0.063)

0.131*

(0.063)

78

Children -0.075

(0.057)

0.135

(0.072)

0.088

(0.073)

0.013

(0.060)

0.013

(0.060)

Farm 0.014

(0.063)

0.260*

(0.101)

0.254*

(0.102)

0.066

(0.085)

0.081

(0.085)

Meat:Neveri -0.294

(0.163)

-1.242**

(0.313)

-1.684**

(0.251)

Meat:Yearlyi -0.209

(0.138)

-0.137

(0.199)

-0.595**

(0.155)

Meat:Monthlyi 0.008

(0.123)

-0.106

(0.172)

-0.539**

(0.131)

Meat:Weeklyi 0.075

(0.12)

-0.070

(0.167)

-0.473**

(0.128)

Breakfast meat purchases

(pounds/year)j

0.001

(0.003)

Lunch meat purchases

(pounds/year)k

0.001

(0.003)

Fresh beef purchases

(purchase units/year)l

0.010*

(0.004) aDependent variable is response to question, “To what extent do you agree or disagree with each of the following

statement? I am willing to eat meat from cloned animals.” Response categories were: 1=strongly disagree, 2=

somewhat disagree, 3=neither agree nor disagree, 4=somewhat agree, and 5=strongly agree. bOne and two asterisks indicates statistical significance at the 0.05 and 0.01 levels, respectively

cNumbers in parentheses are standard errors

d Variable defined in table 18; Parameter estimates relative to age 65 and over

eParameter estimate compared to “other races”

fParameter estimate compared to education of Bachelor‟s degree or higher

gVariable defined in table 18; parameter estimate compared to households making more than $100,000/year

hParameter estimate compared to residents in West U.S Census Region

i Dummy variables, with parameter estimates compared to those who purchase meat every day

jAnnual volume (pounds) of breakfast meat purchased determined from scanner data

kAnnual volume (pounds) of lunch meat purchased determined from scanner data

lAnnual volume (in units purchased – not controlling for unit size) of beef purchased determined from scanner data

79

Table 30. Probability of Affirmative Vote on Policy Related to Mandatory Tracking of Cloned

Animals; Comparison across Three Samples

Variable KNa IRI Nielsen

Constant (utility of policy vs. no policy) -0.012

(0.067)b

0.716*

(0.078)

0.362*

(0.073)

Percentage Price Increase -0.009*c

(0.001)

-0.012*

(0.001)

-0.011*

(0.001)

Willingness-to-Pay -1.3%

[-15.6%, 12.9%]

61.7%*

[51.7%, 71.3% ]

32.0%*

[24.0%, 40.1%]

Log-Likelihood -1,469.5 -1,126.3 -1,428.8

Number of Observations 2,220 1,691 2,120 aA likelihood ratio test could not reject the hypothesis that the parameters were the same across the two information

treatments in the KN sample.

bNumbers in parentheses are standard errors.

cOne asterisk implies the parameter is statistically different than zero at the 0.05 level or lower

80

Table 31. Probability of Affirmative Vote on Policy Related to Mandatory Labeling of Cloned

Meat and Milk; Comparison across Three Samples

Variable KNa

IRI Nielsen

Constant (utility of policy vs. no policy) 0.468*c

(0.066)b

0.757*

(0.080)

0.248*

(0.075)

Percentage Price Increase -0.015*

(0.001)

-0.008*

(0.001)

-0.008*

(0.001)

Willingness-to-Pay 32.1%*

[26.1%, 37.9%]

98.5%*

[73.4%, 123.5%]

32.2%*

[20.4%, 44.1%]

Log-Likelihood -1,469.5 -1,117.2 -1,451.3

Number of Observations 2,220 1,691 2,120 aA likelihood ratio test could not reject the hypothesis that the parameters were the same across the two information

treatments in the KN sample.

bNumbers in parentheses are standard errors.

cOne asterisk implies the parameter is statistically different than zero at the 0.05 level or lower

81

Table 32. Probability of Affirmative Vote on Policy Related to Ban on Practice of Animal

Cloning; Comparison across Three Samples

Variable KNa

IRI Nielsen

Constant (utility of policy vs. no policy) -0.103

(0.068)b

0.063

(0.077)

-0.020

(0.077)

Percentage Price Increase -0.008*c

(0.001)

-0.005*

(0.001)

-0.011*

(0.001)

Willingness-to-Pay -13.2%

[-33.7%, 7.4%]

12.4%

[-12.4%, 37.2%]

-1.9%

[-16.1%, 12.4%]

Log-Likelihood -1,466.4 -1160.8 -1,366.6

Number of Observations 2,214 1,691 2,120 aA likelihood ratio test could not reject the hypothesis that the parameters were the same across the two information

treatments in the KN sample.

bNumbers in parentheses are standard errors.

cOne asterisk implies the parameter is statistically different than zero at the 0.05 level or lower

82

Table 33. Ground Beef Conjoint Models: Multinomial Logit Estimates; Comparison across

Three Samples

Attribute KNa

IRIb

Nielsenc

Clone vs. None -0.967*e

(0.185)d

-0.157

(0.225)

0.166

(0.187)

Offspring of Clone vs. None -0.649*

(0.185)

0.057*

(0.225)

0.418*

(0.187)

Non-Clone vs. None 1.357*

(0.185)

2.439*

(0.225)

2.395*

(0.188)

Percent Leanness 0.030*

(0.002)

0.019*

(0.002)

0.023*

(0.002)

Percent Saturated Fat -0.090*

(0.002)

-0.057*

(0.004)

-0.084*

(0.004)

Price -0.559*

(0.011)

-0.681*

(0.014)

-0.683*

(0.011)

aResults based on 26,536 choices made by 2,243 individuals; Log-likelihood function value = -24,381.91.

bResults based on 20,292 choices; Log-likelihood function value = -29,341.8.

cResults based on 25,440 choices; Log-likelihood function value = -30,725.73.

dNumbers in parentheses are standard errors

eOne asterisk represents parameter is statistically different than zero at the 0.05 level or lower

Note: The log-likelihood function value for a model where parameters are pooled across all three samples is

-91,917.68 (N=72,268). A likelihood ratio test indicates that we can reject the null hypothesis that parameters are

equal across all three samples (Chi-square value =14,936.47; df=12; P-value<0.001).

83

Table 34. Willingness-to-Pay for Selected Ground Beef Attributes Calculated from Conjoint

Estimates; Comparison across Three Samples

Willingness-to-Pay ($/choice) for . . . KN

IRI

Nielsen

Non-Clone vs. Cloned $4.16 $3.81 $3.25

Non-Clone vs. Offspring of Clone $3.59 $3.50 $2.88

Offspring of Clone vs. Clone $0.57 $0.31 $0.37

Increase in Leanness (90% vs. 80%) $0.54 $0.28 $0.33

Reduction in Saturated Fat (5% vs. 10%) $0.80 $0.42 $0.61

84

Table 35. Milk Conjoint Models: Multinomial Logit Estimates; Comparison across Three

Samples

Attribute KNa

IRIb

Nielsenc

Clone vs. None 0.664*d

(0.035)e

0.399*

(0.041)

0.653*

(0.036)

Offspring of Clone vs. None 0.530*

(0.035)

0.201*

(0.042)

0.561*

(0.036)

Non-Clone vs. None 2.240*

(0.034)

2.287*

(0.041)

2.133*

(0.035)

rBST vs. no RBST -0.602*

(0.017)

-0.463*

(0.021)

-0.489*

(0.018)

Fat Content: 1% vs. Skim -0.123*

(0.024)

0.133*

(0.028)

-0.183*

(0.025)

Fat Content: 2% vs. Skim 0.261*

(0.023)

0.411*

(0.029)

0.290*

(0.024)

Fat Content: Whole vs. Skim -0.171*

(0.023)

-0.141*

(0.028)

-0.035*

(0.024)

Price -0.378*

(0.006)

-0.404*

(0.007)

-0.426*

(0.006)

aResults based on 35,373 choices made by 2,237 individuals; Log-likelihood function value = -39,091.28.

bResults based on 27,056 choices; Log-likelihood function value = -44,087.83.

cResults based on 33,920 choices; Log-likelihood function value = -47,351.13.

dOne asterisk represents parameter is statistically different than zero at the 0.05 level or lower

eNumbers in parentheses are standard errors

Note: The log-likelihood function value for a model where parameters are pooled across all three samples is

-145,223.65 (N=96,349). A likelihood ratio test indicates that we can reject the null hypothesis that parameters are

equal across all three samples (Chi-square value =29,386.82; df=16; P-value<0.001).

85

Table 36. Willingness-to-Pay for Selected Milk Attributes Calculated from Conjoint Estimates;

Comparison across Three Samples

Willingness-to-Pay ($/choice) for . . . KN

IRI

Nielsen

Non-Clone vs. Cloned $4.17 $4.68 $3.47

Non-Clone vs. Offspring of Clone $4.53 $5.17 $3.69

Offspring of Clone vs. Clone -$0.35 -$0.49 -$0.22

No rBST vs. rBST $1.59 $1.15 $1.15

86

Table 37. Effect of Actual Milk Purchase Behavior on Milk Conjoint Model; IRI sample

Attribute MNL

Estimate

Price -0.424*a

(0.007)b

Fat Content: 1% vs. Skim 0.153*

(0.029)

Fat Content: 2% vs. Skim 0.461*

(0.029)

Fat Content: Whole vs. Skim -0.087*

(0.029)

rBST vs. no RBST -0.489*

(0.021)

Non-Clone vs. None 2.500*

(0.045)

Non-Clone vs. None x

Annual milk purchased

-0.005*

(0.001)

Non-Clone vs. None x

Organic share

-0.057

(0.078)

Clone vs. None 0.594*

(0.049)

Clone vs. None x

Annual milk purchased

-0.005*

(0.001)

Clone vs. None x

Organic share

-1.492*

(0.194)

Offspring of Clone vs. None 0.427*

(0.049)

Offspring of Clone vs. None x

Annual milk purchased

-0.005*

(0.001)

Offspring of Clone vs. None x

Organic share

-0.903*

(0.174) aOne asterisk represents parameter is statistically different than zero at the 0.05 level or lower

bNumbers in parentheses are standard errors

Notes: Results based on 26,432 choices; Log-likelihood function value = -41,508.52.

87

Table 38. Relationship between Actual Milk Purchases and Willingness-to-Pay for Non-Cloned

Milk; IRI sample

Milk Consumption Behavior

WTP for non-

cloned vs. cloned

milk ($/choice)

Total annual milk purchasesa

1 gallon/year $4.67

25 gallons/year $4.66

50 gallons/year $4.66

Percent of total annual milk purchases that are organic

b

0% organic $4.49

50% organic $6.19

100% organic $7.88 Note: results derived by interaction actual transaction data with survey-based conjoint estimates. The mean total

annual milk purchased was 25.94 gallons/year (high = 291 gallons/year; low = 0 gallons/year). The mean percentage

of total annual milk purchases resulting from organic sales was 5.4% (high=100%; low=0%) aAssuming share of organic milk purchased is 5%

bAssuming total annual milk purchased is 25 gallons/year