A RISK PERCEPTION ANALYSIS OF GENETICALLY MODIFIED. Marcia J. Bugbee and Maria L. Loureiro

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1 A RISK PERCEPTION ANALYSIS OF GENETICALLY MODIFIED FOODS BASED ON STATED PREFERENCES Marca J. Bugbee and Mara L. Lourero Department of Agrcultural and Resource Economcs Colorado State Unversty Fort Collns, CO Paper Prepared for presentaton at the Amercan Agrcultural Economcs Assocaton Annual Meetng, Montreal, Canada, July 27-30, 2003 Copyrght 2003 by Marca Bugbee and Mara Lourero. All rghts reserved. Readers may make verbatm copes of ths document for non-commercal purposes by any means, provded that ths copyrght notce appears on all such copes.

2 A RISK PERCEPTION ANALYSIS OF GENETICALLY MODIFIED FOODS BASED ON STATED PREFERENCES Abstract Most of the exstng lterature deals wth consumer wllngness to pay for GM-free food, or consumer wllngness to accept for GM food. However, t s well know that consumers have mxed vews about GM foods. In ths research, we do not presume that all consumers may just have postve or negatve preferences about GM products. Rather, heterogeneous preferences are consdered. Ths paper presents a contngent valuaton questonng sequence and assocated modelng approaches that allow dentfcaton of both postve and negatve preferences. Wllngness to pay (WTP) for the GM product s contrasted wth wllngness to accept (WTA) compensaton to buy t. 1

3 Introducton The study of consumer response toward genetcally modfed (GM) crops and foods s becomng ncreasngly mportant. Whle there s consderable economc lterature on general atttudes toward GM products, nternatonal dfferences n polces regardng GM processes and labelng, and wllngness to pay for foods labeled as non-gm, there are stll many unanswered questons surroundng ths topc. To our knowledge, there s a stll a need to dentfy the role played by dfferent rsk factors n the consumer response toward these new types of food technologes, as well as how consumer response may change f the GM product offers a drect personal beneft to the purchaser. The mpact of perceved rsks and benefts assocated wth new food technologes has mportant economc and food safety mplcatons. Therefore, better understandng of consumer atttudes and behavor toward genetcally modfed (GM) food products s essental for desgnng new market strateges for the second-generaton of GM products whch, unlke the frst-generaton of producer and envronment-frendly GM, offer benefts to consumers. There are several known potental rsks assocated wth GM crops and foods. These nclude, but are not necessarly lmted to: health ssues such as allergencty, ncreased toxns, antbotc resstance, and unknown consequences to humans that may exst, and envronmental ssues such as effects on non-target organsms, crop to crop cross pollnaton, crop to weed pollnaton, and development of pest resstance to nsectcdes (Feldmann, Mors, and Hosngton, 2000; CSU Transgenc Crops webste). However, potental rsks do not always translate nto perceved rsks by consumers. On the other hand, benefts assocated wth GM manpulaton are also varous, 2

4 dependng on the fnal use or goal of the product. Some of the most common benefts nclude the ncrease n nutrtonal qualtes, the reducton of pestcdes applcatons, and ncrease n shelf lfe of the product. Though there are many studes about the economcs of rsk perceptons, and there s a growng body of lterature about consumer rsks and beneft perceptons assocated wth new food products, few economc studes have looked at the mpact of those rsk and beneft perceptons of GM food on nformaton-seekng or purchasng behavor. The current paper wll add to the economc lterature about GM products n the context of heterogeneous preferences about rsks and benefts assocated wth ths new type of food technology. The valuaton methods wll account for the ndvduals that wll pay for the benefts of GM food and those that wll not be wllng to pay anythng due to perceved rsks assocated wth the technology. The analyss ncludes two products, a genetcally modfed tomato and a genetcally modfed beef product. Heterogeneous preferences were consdered, thus the analyss ncludes both WTP and WTA regressons and, repectvely, WTP and WTA mean value calculatons.. Based on the results, nterestng comparsons can be made between the two product categores analyzed, crops and meats. Lterature Revew There are many studes dealng wth wllngness to pay (WTP) for dfferentated products, although only a handful regardng wllngness to pay for GM or GM-free food products. Exstng studes have elcted WTP for GM-free products by usng ether contngent valuaton (CV) methods or expermental aucton methods. Whle CV methods 3

5 wll be used for the purpose of ths study, t s nterestng and useful to look at the expermental methods and results as well. Usng expermental economcs methods of calbraton and frst- and second-prce auctons, Lusk et al. (2001) determned consumer wllngness to pay for non-gm corn chps. Results from the calbraton, usng scale-dfferental questons, ndcated a hgh level of acceptance of GM products. However, results from the double-hurdle model bds ndcated that 70% of partcpants were unwllng to pay for non-gm chps. Addtonally, 20% of consumers bd $0.25/oz. or more for the opportunty to exchange ther GM chps for non-gm chps. Another study, by Huffman et al. (2001), presented wllngness to pay for foods wth and wthout GM labels usng laboratory aucton experments for three food tems. The random nth-prce aucton format was used n these experments, elctng premums of about 14 percent for foods that respondents perceved as non-gm. Ths premum was smlar across the three dfferent products, makng t possble to conclude that consumer demand for GM foods s sgnfcantly lower than the demand for the non-gm counterpart. None of the socodemographc characterstcs appeared to alter consumer WTP for GM foods. Contngent valuaton (CV) methods were used by Lourero and Hne (2002), wth the objectve of determnng consumer wllngness to pay for a labeled value-added potato that could be marketed as organc, GMO-free, or Colorado grown. Perhaps the WTP research that may be most closely related to the objectves of the present paper s that of Moon and Balasubramanan (2001). The survey nstrument used n ther study ncluded CV questons to assess consumer wllngness to pay a premum for non-gm 4

6 breakfast cereals. They found that n both the UK and the US, rsk and beneft perceptons clearly translated nto purchasng ntentons and behavors as measured wth wllngness to pay. Equally mportant was the concluson that rsk percepton exerts a greater mpact on WTP than beneft percepton. It should be noted, however, that consumer recepton of GM foods may be sgnfcantly dfferent f the food products can offer drect, personal benefts. Such products, whch are referred to as neutraceutcal products or functonal foods, are the second generaton of GM products and are ncluded n the analyss of the present paper. The present study attempts to analyze consumer trade-offs between potental benefts and potental rsks assocated wth the GM technology, analyzng the role played by subjectve belefs and rsk perceptons on consumer acceptance of GM products. Wllngness to pay (WTP) for the product s contrasted wth wllngness to accept (WTA) compensaton to buy the product. Unlke most contngent valuaton studes where WTA represents the amount of money that has to be offered to a respondent n order to forego the consumpton of a specfc good and reman at the same utlty level (.e., equvalent varaton measure), n ths applcaton WTA corresponds to the mnmum amount of money that has to be offered to the respondent to accept a less preferred stuaton assocated wth the program (.e., compensatng varaton measure). In modelng heterogeneous preferences, we draw from exstng envronmental economcs lterature about lovers and haters (wnners and losers). Ths pror research shows that gnorng negatve preferences leads to consderable overestmaton of wllngness to pay (Huhtala, 2000; Clnch and Murphy, 2001). These researchers have demonstrated the mportance of allowng for lovers and haters n contngent valuaton, 5

7 assertng that the externaltes of a program (or good) may be vewed costs by some people and benefts by others. Krstrom (1997) dscusses the use of spke models for CV studes, allowng also for zero WTP (n addton to postve and negatve WTP). The next sectons of ths paper present the emprcal methods, the data, and concludng results. Theoretcal Background The consumer s decson process s modeled usng a random utlty approach. Consumer utlty, U ( y, x, m), s assumed to have three arguments: genetc manpulatons of food products that offer consumer benefts, y, consumer soco-demographc characterstcs and personal belefs that may affect choce, x, and the ncome level, m. The varable y s an ndcator varable, whch equals one f the product has been genetcally modfed, and zero otherwse. The consumer s wllng to pay c dollars to swtch to a GM product, whch wll make utlty at least as great as t would be f the product was not genetcally modfed. Mathematcally, c s represented as (1) U(, x, m) U ( 1, x, m ), c where the 0 and 1 subscrpts denote the choce of non-gm and GM food products, respectvely. The consumer s utlty functon s unknown snce some components are unobservable and thus, can be consdered random varables from the researcher s standpont. Therefore, utlty s decomposed nto an unobservable part and an error term, ε j U ( y, x. Mathematcally, j, m) = V ( y, x j, m) + ε j ε j. The random error term s assumed to be ndependently and dentcally dstrbuted wth a mean of zero. The 6

8 consumer s decson to pay c dollars n terms of utlty can be represented as: (2) V (, x, m) + ε V ( 1, x, m c) +, ε1 whch can be expressed n a probablty framework as: (3) P( WTP c) = P( V + ε V + ε ) = P( ε ε V ) V0 Ths theoretcal model sets the groundwork for the specfc emprcal models that follow. In the current study, a bnary choce model approach s chosen to analyze the decson of payng a premum (WTP) or acceptng compensaton (WTA) for two genetcally modfed food products, a tomato and a beef product. Methodology Based on the survey format, t s plausble to estmate the wllngness to pay and wllngness to accept measures usng a sample selecton framework. As stated prevously, the survey used a patterng format very smlar to the double bounded model n whch respondents face an ntal preference queston about GM products (at no premum). Based on ther ntal preferences, a follow-up queston asked consumers wllngness to pay or wllngness to accept. That s, only consumers who gve a postve answer to the frst queston receve the WTP follow-up queston. The opposte occurs for the WTA queston, snce only those that answered no to the ntal preference queston were asked n the follow-up queston ther wllngness to pay. Usng a general 7

9 framework, we can state that the sample equaton that determnes the selecton process s the frst ntal queston asked n the survey, * z = γ w + u. Let the equatons of prmary nterest be: (4) WTP = β x + ε, f z > 0, and (5) WTA = β x + ε, f z <= 0. Addtonally, we assume that ε and u have a bvarate normal dstrbuton wth mean zero an correlaton ρ. To obtan the model that apples to the observatons n our sample, we have: * (6) E[ WTP z > 0] = β x + ρσ λ ( α ), where α u = γ w / σ u and λ( α u ) = ϕ( γ w / σ u ) / Φ( γ w / σ u ). ε u Notce that the same apples for the WTA (after recodng the response of the selecton queston), such that: * (7) E[ WTA z < 0] = β x + ρσ λ ( α ), These selecton equatons wll be estmated usng LIMDEP. ε u 8

10 Data The data was gathered usng a mal survey n the Western States of the Unted States. A sample of 1000 partcpant households was drawn from a malng lstng purchased from Survey Samplng, Inc., a leader n the scence of samplng methodology and research qualty. Ths lstng s compled from the whte page drectores, and supplemented wth a varety of other sources such as Department of Motor Vehcles (DMV) nformaton, voter nformaton, census data, and school records. Thus, we expect that ths lstng s representatve of the current U.S. Census. Upon recevng the lstng of 1,000 households, scrpted calls were placed to each household. The purpose of the call was to determne f someone would be wllng to partcpate n the study by completng a mal survey. Based on the respondents wllngness to cooperate, the survey was sent to a total of 680 households. Before the survey was sent off, a pretest was conducted n two dfferent locatons n the states of Colorado and Calforna. After makng slght modfcatons usng the nformaton gathered n the pre-test, the fnal survey was sent out n a sx-page, booklet format, wth a cover letter explanng the project, and a pre-pad return envelope. The survey ncluded four dfferent sectons. In the frst secton, dfferent warm-up questons related to general knowledge and nformaton about rsks and benefts assocated wth genetcally modfed foods were presented to the respondents. The level of consumer concern wth socal/ethcal, health, and envronmental ssues surroundng genetc modfcatons was obtaned n secton two. The thrd secton contaned the elctaton of wllngness to pay for dfferent genetcally modfed processes n both anmals and crops, and wth and wthout the assocaton of any rsk for humans or for the envronment. 9

11 Fnally, the last secton contaned questons related to soco-demographcs varables. The thrd secton of the survey s of partcular mportance to the purpose of ths paper because t allows for the comparson of WTP and WTA measurements for both crop (tomato) and anmal (beef) products. In both cases, the ntal queston presents survey respondents wth a drect consumer beneft of hgher vtamn content for the tomato and lower fat content for the beef product. These potental benefts that are assocated wth the GM food are expected to elct a postve WTP value. The survey questons used to analyze the net WTP for the GM products were the followng: Assume that there s a new GM tomato wth hgher nutrtonal value and both GM and non-gm tomatoes of comparable appearance are avalable at the same prce, would you be wllng to buy the GM tomatoes? 1. Yes 2. No If you responded NO, would you be wllng to buy those same GM tomatoes at a prce 10% lower per pound ($2.06) than that of the non-gm tomatoes (regular prce=$2.29/pound)? 1. Yes 2. No If you responded YES, would you be wllng to spend 10% more per pound ($2.52) f the GM tomatoes have hgher vtamn content than the non-gm tomatoes (regular prce=$2.29/pound)? 1. Yes 2. No Assume that there s a new type of GM beef wth hgher nutrtonal content and less calores, f both GM and non-gm beef of comparable appearance were avalable for the same prce, would you be wllng to buy the GM beef? 1. Yes 2. No If you responded NO, would you be wllng to buy that same GM beef at a prce 10% lower per pound ($4.31) than that of the non-gm beef (regular prce=$4.79/pound)? 1. Yes 2. No If you responded YES, would you be wllng to spend 10% more per pound ($5.27) f the GM beef had lower fat content than the non-gm beef (regular prce=$4.79/pound)? 1. Yes 2. No 10

12 A total of 164 responses were receved The respondents' average age was between years, wth a mean educaton that ncluded junor college, 64.6% were marred, and 49% of all respondents had chldren under the age of 18 years old lvng n ther household. The average household sze was about 2.5 members, and average household ncome was between $50,000 and $59,000 for the 2001 fscal year. Summary statstcs of the soco-demographcs are presented n Table 1. When comparng our soco-demographc fgures wth the U.S. Census (U.S. Census Bureau), as n Table 2, we see that our sample s consderably older (approxmately 15 years older), wth hgher ncome levels and a hgher percentage of people that have attaned a Bachelor s Degree or hgher. The sample also has a lower percentage of females and a lower percentage of households wth chldren under 18 years of age. It s clear that ths sample populaton had consderably dfferent soco-demographc characterstcs than the broader U.S. populaton, however, t s dffcult to assess the effects that may be assocated wth these dfferences n our results. Whle a representatve sample s always of concern to a researcher, t s lkely that we encountered some degree of sample selecton bas n whch respondents who were more nterested n the topc of GM crops and food products elected to partcpate n the survey. In the current study, partcpaton was estmated to be about 24% of the total solcted populaton. Research conducted by Edwards and Anderson (1987) found sgnfcant dfferences between the characterstcs of survey respondents and nonrespondents. Fnally, Messonner et al. (2000) examned sample nonresponse and selecton bases, fndng out that unt nonresponses serously affected welfare measures. 11

13 In our study, snce we do not have any nformaton regardng the nonrespondents, we cannot assess the mpact of sample selecton bases on our WTP and WTA estmates. Gven the precedng observatons, we acknowledge that our fndngs are lmted n ther ablty to be appled to a fully generalzed broader populaton. Model Specfcaton and Varable Defntons The frst stage, probt models are specfed as follows: (8) 0 WTP GMTomato / GMBeef β + β MdAge + β Older + β Chld + β Manpulat on + β GMRsky = 3 + β Female + β Mddle + β Upper The results from ths frst stage are held and then the selecton models depcted n equaton (4) and equaton (5) are estmated for each of the four sub-groups: GM tomato WTP, GM tomato WTA, GM beef WTP, and GM beef WTA. The fnal specfcatons of the equatons are as follows: (9) WTP / WTA GMTomato β + β Bd + β SomeInf + β PoorInf + β Manpulat on + β GMRsky + β Lambda 0 1 and (10) WTP / WTA 2 GM Beef = 3 β + β Bd + β SomeInf + β PoorInf + β Manpulat on + β GMRsky + β Lambda = where Bd s the random percentage premum (or dscount) a consumer was faced wth 12

14 (rangng from 5-50%); MdAge s a dummy varable that represents ages n the nterval of years; Older s an ndcator varable representng those over 55 years of age; Chld s a dummy varable that represents the presence of chldren n the household; Female s an ndcator varable that represents a female respondent; Mddle s a cross product of a dummy varable that represents a household ncome wthn the range of $30,000 to $69,999 per year and a dummy varable that represents an educaton level of some college or junor college graduate ; Upper s a cross product representng those wth a household ncome greater than $70,000 per year and the mnmum educaton level of a 4- year unversty graduate; SomeInfo s an ndcator varable representng those who consder themselves somewhat nformed about GM food; and PoorInfo s a dummy varable representng those who consder themselves ether poorly nformed or not at all nformed about GM food; Manpulaton s a scale varable rangng from 1 to 10, wth 1 representng the preference of preservng natural speces at all costs, and 10 representng manpulatng natural speces n order to get a beneft at all costs; GMRsky s an ndcator varable representng those that beleve GM food carres both food safety and envronmental rsks. Results The probt model results presented n Table 4 are the frst stage of our model. Ths frst stage was based on the ntal dchotomous choce queston, whch addressed whether or not respondents would be wllng to purchase a GM product (tomato and beef) wth hgher nutrtonal content f t was of comparable appearance and prce. The results from the GM tomato probt regresson suggest that age, gender, socal 13

15 status, vews on manpulaton of natural speces, and rsk perceptons assocated wth GM foods are the sgnfcant determnants of whether or not one would purchase a GM tomato. Postve effects are assocated wth beng mddle aged or older (35-55, >55) and wth those that agree wth manpulaton of natural speces to obtan a beneft. Alternatvely, negatve effects are assocated wth beng female and from the mddle class, as well as belevng GM food carres both food safety and envronmental rsks. Also reported n Table 4 are the results from the GM beef probt regresson, whch ndcates that the presence of chldren n the household, vews of speces manpulaton, and rsk perceptons are the major determnants of whether or not one would purchase a benefcal GM beef product. The results from ths beef regresson, as well as those obtaned from the GM tomato regresson, were then retaned and factored nto the selecton models presented below. GM Tomato WTP Estmate About 63% of the survey respondents sad that they would be wllng to purchase a genetcally modfed tomato. The regresson presented n Table 5 ndcates the determnng factors that mpact the probablty that a person from ths group of consumers wll pay a premum for the GM tomato. The regresson results show that the sgnfcant varables mpactng the probablty that a consumer wll pay a premum for the GM tomato nclude: Bd, the random percentage premum a consumer was faced wth (rangng from 5-50%), and SomeInfo, an ndcator varable representng those who consder themselves somewhat nformed about GM food. These varables are both sgnfcant and negatve, whch means that a consumer presented wth a hgher premum 14

16 prce s less lkely to pay a premum for the product, and those that consder themselves somewhat nformed are also less lkely to pay a premum wth respect to the omtted category. Lookng at the margnal effects of these varables, as presented n Table 6, we can expand on the mpact of these two varables on the probablty of payng a premum. As the bd amount (Bd) ncreases by 1%, there s an approxmate 0.7 decrease n the probablty that a consumer wll be wllng to pay a premum for the GM tomato. The probablty also decreases by about 0.3 f the consumer consders themselves somewhat nformed about GM food. Based on these regresson results the estmated mean WTP value for GM tomatoes was calculated. The results, as reported n Table 7, show that consumers from ths group (whch conssted of 63% of our solcted populaton) are wllng to pay, on average, a premum of approxmately 25% for these genetcally modfed tomatoes. GM Tomato WTA Estmate Approxmately 36% of our respondents sad ntally that they would not buy the GM tomato. Thus, each of these consumers was asked f they would accept the tomato at a dscount. The estmated mean wllngness to accept value, reported n Table 7, s a dscount of about 9% the orgnal tomato prce. The probablty of consumers from ths group acceptng compensaton for the GM tomato s mpacted by two sgnfcant varables, Bd and PoorInfo. The postve sgn on the Bd varable s an ndcaton that the greater the amount of compensaton offered, the more lkely t s that consumers wll accept the modfed tomato. Alternatvely, the 15

17 negatve sgn of the PoorInfo coeffcent ndcates that those respondents that consder themselves poorly nformed or not at all nformed about GM food are less lkely to be wllng to accept the GM tomato. In fact, based on the margnal effect measure, the probablty that a consumer wll accept the GM tomato decreases by about 0.2 f the consumer s poorly nformed. GM Beef WTP Estmate Those consumers that were wllng to buy the GM beef conssted of about 55% of the solcted populaton. The estmated mean WTP for GM beef s a premum of about 46%. The only varable that mpacts the probablty that a consumer n ths group wll pay a premum for the GM beef product s the bd amount. As expected, Bd has a negatve and statstcally sgnfcant coeffcent. The margnal effect assocated wth the bd value ndcates that a 1% ncrease n the premum value results n a 1% decrease n the probablty that a consumer wll pay the premum. GM Beef WTA Estmate Approxmately 44% of the respondents sad that they would not purchase the GM beef product. In estmatng the probablty that consumers from ths group wll purchase the product at a dscounted rate, there was only one sgnfcant varable, Lambda. The sgnfcance of ths varable justfes the use of the Heckman estmator. If we were to have omtted the ntal queston from the CV questonng sequence of the survey, we would have lost some valuable nformaton about the WTP/WTA estmates.see Table 6 for the ndrect effects. 16

18 Conclusons The results from ths analyss nclude two products, a genetcally modfed tomato and a genetcally modfed beef product. Addtonally, heterogeneous preferences were consdered, thus the analyss ncludes WTP regressons and WTP mean value calculatons, as well as WTA regressons and WTA mean value calculatons. Results ndcate that the man nfluencer of mean WTP or WTA measures s the bd amount a respondent s presented wth. The hgher the premum, the less lkely t s that the consumer wll pay t. Also, the probt models suggest that the across-the-board determnants of whether a person s a lover or hater of GM foods are ther vews on manpulaton of natural speces (Manpulaton) and ther perceptons of the rsks assocated wth GM technology (GMRsky). Other soco-demographc varables were also found to be sgnfcant contrbutors. Interestng comparsons can be made between the two product categores analyzed, crops and meats. Frst, we note that t seems a hgher percentage of respondents prefer tomatoes than GM beef. It s possble then, that the general populaton s more acceptng of plant modfcatons than of GM anmal products. However, the ones preferrng GM beef also seem to be wllng to pay hgher premums than the lovers of GM tomatoes. Those people that enjoy ths benefcal GM beef product, whch offers hgher nutrtonal content and fewer calores, are wllng to pay premums of approxmately 46%. Future research should contnue to explore the dfferences n perceptons and WTP/WTA measures of GM crop and GM anmal products. 17

19 References Baker, G.A. and Burnham, T.A. (2001). Consumer Response to Genetcally Modfed Foods: Market Segment Analyss and Implcatons for Producers and Polcy Makers. Journal of Agrcultural and Resource Economcs, 26(2), Boman, M., G. Bostedt, and B. Krström (1999). Obtanng Welfare Bounds n Dscrete- Response Valuaton Studes: A Non-Parametrc Approach. Land Economcs, 75(2): Carson, R.T., L. Wlks and D. Imber (1994). Valung the Preservaton of Australa s Kakadu Conservaton Zone. Oxford Econom. Papers 46: Clnch, P. and A. Murphy (Aprl 2001). Modelng Wnners and Losers n Contngent Valuaton of Publc Goods: Approprate Welfare Measures and Econometrc Analyss. The Economc Journal 111: Transgenc Crops: An Introducton and Resource Gude, Colorado State Unversty Webste, Avalable at: Feldmann, M.P., Morrs, M.L., and Hosngton, D. (2000). Why All the Controversy? Choces, 15(1), Haab, T. and K. McConnell (1997). Referendum Models and Negatve Wllngness to Pay: Alternatve Solutons. Journal of Envronmental Economcs and Management 32: Hanemann, M (1989). Welfare Evaluatons n Contngent Valuaton Experments wth Dscrete Response Data: Reply. Amercan Journal of Agrcultural Economcs 71: and B. Kannnen The Statstcal Analyss of Dscrete-Response CV Data. In: Valung Envronmental Preferences, I. Bateman and K. Wlls Eds. Huang, J., Haab, T.C., and Whtehead, J.C. (2001). Absolute Versus Relatve Rsk Percepton: An Applcaton to Seafood Safety. Workng paper: AEDE-WP , Department of Agrcultural, Envronmental, and Development Economcs, The Oho State Unversty. Huffman, W.E., Shogren, J.F., Rousu, M., and A. Tegene (2001). The Value to Consumers of GM Food Labels n a Market wth Asymmetrc Informaton: Evdence From Expermental Auctons. Paper presented at the annual Amercan Agrcultural 18

20 Economcs Assocaton, Chcago, August 5-8. Huhtala, A (2000). Bnary Choce Valuaton Studes wth Heterogeneous Preferences Regardng the Program Beng Valued. Envronmental and Resource Economcs, 16: Hutchnson, G., R. Scarpa, S. Chlton, and T McCallon (January 2001). Parametrc and Non-Parametrc Estmates of Wllngness to Pay for Forest Recreaton n Northern Ireland: A Dscrete Choce Contngent Valuaton Study wth Follow-Ups. Journal of Agrcultural Economcs, 52(1): Krström, B. (May 1990). A Non-Parametrc Approach to the Estmaton of Welfare Measures n Dscrete Response Valuaton Studes. Land Economcs, 66: Krström, B. (1997). Spke Models n Contngent Valuaton. Amercan Journal of Agrcultural Economcs, 79: Lourero, Mara L. and Susan Hne, December Dscoverng Nche Markets: A Comparson of Consumer Wllngness to Pay for Local (Colorado Grown), Organc and GMO-free Products, Journal of Agrcultural and Appled Economcs 34(3): Lusk, J.L., Danel, M.S., Mark, D.R., and Lusk, C.L. (2001). Alternatve Calbraton and Aucton Insttutons for Predctng Consumer Wllngness to Pay for Nongenetcally Modfed Corn Chps. Journal of Agrcultural and Resource Economcs, 26(1), Moon, W. and Balasubramanan, S.K. (2001). Publc Perceptons and Wllngness-to- Pay a Premum for Non-GM Foods n the US and UK. AgBoForum, 4(3&4), Avalable on the World Wde Web: Smth, K.V. and Johnson, F.R. (1998). How Do Rsk Perceptons Respond to Informaton? The Case of Radon. The Revew of Economcs and Statstcs, 70(1): 1-8. Turnbull, B. W., (1976). The Emprcal Dstrbuton Functon wth Arbtrarly Grouped, Censored and Truncated Data. J. Roy. Statst. Soc. Ser. B. 38: U.S. Census Bureau, Unted States Census Avalable at: 19

21 Table 1. Summary Statstcs: Man Soco-Demographcs Sample Characterstcs Descrpton Mean St. Dv. Cases Age 1=Under = = = = = = = = =60+ years Gender 1=Female =Otherwse Educaton 1=Elementary school or less =Some hgh school 3=Hgh school graduate 4=Some college 5= Junor college graduate 6=4-year unversty graduate 7=Post graduate work 8=Any other educaton Income 1=Under $20, =$20,000-$29,999 3=$30,000-$39,999 4=$40,000-$49,999 5=$50,000-$59,999 6=$60,000-$69,999 7=$70,000+ Employment Student (1.25%) 160 Full-tme (51.25%) Part-tme (8.75%) Stay at home (4.38%) Retred (31.25%) Not Employed (3.12%) Household Contnuous Members Chldren Contnuous Under18 at Home Martal Status Marred (64.6%) Sngle (11.18%) Separated/Dvorced (8.7%) Domestc Partnershp (6.21%) Wdowed (9.32%)

22 Table 2. Comparson of Sample Soco-demographc Versus U.S. Populaton Soco-demographcs Sample U.S. Populaton a % Female 41.6% 50.9% % Household wth chldren under 18 years of age 25.2% 36.0% % Bachelor s degree or hgher 52.8% 24.4% b Medan ncome 5 ($50,000-$59,999) $41,994 Medan age 8 (50-54) 35.3 a Source: Consumer Survey and U.S. Census Bureau, Census b Persons of 25 years and over,

23 Table 3. Consumer Concern wth Socal/Ethcal, Health, and Envronmental Issues Surroundng Genetc Modfcaton 1= 2= 3= 4= 5= 6= Extremely Very Somewhat Not Very Not At All Don't Socal/Ethcal Issue Concerned Concerned Concerned Concerned Concerned Know n= 1. Patentng lfe/playng God 18.47% 5.73% 22.93% 22.29% 25.48% 5.10% Acceleratng growth of multnatonal 14.10% 17.95% 18.59% 25.64% 16.67% 7.05% 156 corporatons 3. May lead to human genetc 19.48% 12.99% 23.38% 19.48% 17.53% 7.14% 154 engneerng 4. Transferrng genes between plants 20.00% 13.75% 26.25% 16.88% 13.75% 9.38% 160 and anmals 5. Increase ncome nequaltes between rch and poor countres 12.90% 13.55% 20.65% 23.87% 20.00% 9.03% 155 Health Issue N= 1. Allerges 27.85% 19.62% 30.38% 11.39% 5.06% 5.70% Increased toxns 27.85% 22.98% 27.33% 9.32% 4.97% 7.45% Lower nutrent content n the food 23.72% 16.67% 27.56% 15.38% 9.62% 7.05% Unknown consequences to humans 43.75% 24.38% 18.75% 5.62% 3.75% 3.75% 160 Envronmental Issue N= 1. Effect on non-target organsms 27.85% 17.09% 30.38% 8.86% 6.33% 9.49% Crop to crop cross pollnaton 21.66% 19.75% 29.94% 10.83% 8.92% 8.92% Crop to weed pollnaton 19.87% 21.79% 30.13% 11.54% 5.13% 11.54% Development of pest resstance to nsectcdes 30.19% 32.70% 19.50% 5.03% 5.66% 6.92%

24 Table 4. Consumers Wllng to Purchase Genetcally Modfed Foods Probt Results Varable GM Tomato GM Beef Coeffcent P-Value Coeffcent P-Value CONSTANT MIDAGE 1.001** OLDER 0.789* CHILD ** FEMALE ** MIDDLE ** UPPER MANIPULATION 0.187*** *** GMRISKY *** *** LOG LIKELIHOOD CHI-SQUARED N= ***,**, and* represent statcally sgnfcant coeffcents at α = 0.001, α = 0.05, and α = 0. 1, respectvely. 23

25 Table 5. WTP/WTA for GM Tomatoes and GM Beef Varable GM Tomato WTP GM Tomato WTA GM Beef WTP GM Beef WTA Coeffcent P-Value Coeffcent P-Value Coeffcent P-Value Coeffcent P-Value CONSTANT 0.450** ** BID ** * *** SOMEINFO ** POORINFO * MANIPULATION GMRISKY LAMBDA * N= ***,**, and* represent statcally sgnfcant coeffcents at α = 0.001, α = 0. 05, and α = 0. 1, respectvely. 24

26 Table 6. Margnal Effects of Varables Drect effects n the regresson Varable GM Tomato WTP GM Tomato WTA GM Beef WTP GM Beef WTA Effect P-value Effect P-value Effect P-value Effect P-value CONSTANT BID SOMEINF POORINF MANIPULATION GMRISKY Indrect effects n LAMBDA CONSTANT E E E E E E-01 MIDAGE E E E E E E-01 OLDER E E E E E E-01 CHILD E E E E E E-01 GENDER E E E E E E-01 MIDDLE E E E E E E-01 UPPER E E E E E E-01 MANIPULATION E E E E E E-01 GMRISKY E E E E E E-01 Total effect for varables n both MANIPULATION E E E E E E-01 parts GMRISKY E E E E E E-01 25

27 Table 6. Mean WTP Calculatons MEAN WTP (% PREMIUM) MEAN WTA (% PREMIUM) GM TOMATO GM BEEF Note that the same framework s vald to analyze WTA, although t requres to make a change n all the sgns. 26