Consumer Valuation of the Second Generation of Genetically Modified (GM) Foods. with Benefits Disclosure. Jae-Hwan Han and R.Wes.

Transcription

1 Consumer Valuaton of the Second Generaton of Genetcally Modfed (GM) Foods wth Benefts Dsclosure by Jae-Hwan Han and R.Wes.Harrson January 13, 2006 Dept. of Agrcultural Economcs and Agrbusness 101 Ag Admnstraton Buldng, Lousana State Unversty Baton Rouge, LA Tel: (225) Fax: (225) e-mal: and Selected Paper prepared for presentaton at the Southern Agrcultural Economcs Assocaton Annual Meetngs Orlando, Florda, February 5-8, 2006 Copyrght 2006 by Jae-Hwan Han and R.Wes.Harrson. 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 Abstract Consumer Valuaton of the Second Generaton of Genetcally Modfed (GM) Foods wth Benefts Dsclosure. Jae-Hwan Han and R.Wes Harrson, Lousana State Unversty. Employng contngent valuaton method (CVM), the study explores whether or not consumers rsk/beneft belefs and knowledge about GM foods affect ther behavor as measured by wllngness to pay (WTP) a premum for GM beef wth benefts. The results demonstrate that rsk/beneft perceptons play a sgnfcant role to elct WTP for GM beef wth benefts

3 Genetc modfcaton (GM) offers the potental for producton of foods and feed crops wth mproved characterstcs, such as more nutrtous components, mproved resstance to dsease and pests, better taste, and so on. GM foods are foods contanng ngredents from plant and anmal organsms produced usng scentfc technques that nvolves takng genes from one speces and nsertng them n another speces to transfer a desred trat or characterstc 1. GM crops offer opportuntes for farmers to lower producton cost, ncrease crop producton, and ncrease profts by usng nputs more effcently. Addtonally, GM crops provde other potental benefts, such as mprovng envronmental qualty by usng less pestcde and herbcde, enhanced food qualty and safety, and by mtgatng world food shortages. However, despte the benefts, some consumers vew botechnology as a rsky process, and have a greater nterest n assurng food safety. Consumers wth unfavorable atttudes toward GM products may expect to have the rght to know whether or not products are produced usng botechnology. Consumer concerns regardng botechnology are beleved to stem from potental unknown effects due to the modfcatons of genes and nutrtonal contents of food. In addton, concerns of envronmental qualty from contamnaton of organc crops and/or herbcde resstant weeds and moralty are other factors to nfluence consumer atttude of GM foods. Consumer acceptance of GM foods has been mxed due to dfferences n perceved rsk and beneft of these foods. Acceptance of GM products s assocated wth 1 FDA and USDA suggest usng boengneered or botech to descrbe foods produced usng botechnology. However, the terms genetcally modfed (GM) and genetcally engneered are commonly used n academc publcatons. In ths paper, the terms botechnology, botech, genetcally modfed, and genetcally engneered are used nterchangeably. The terms refer to all modern technques n cellular and molecular bology used to alter the genetc composton of foods or food ngredents, ncludng n vtro nuclec acd, recombnant DNA, genetc modfcaton, and genetc engneerng. 1

4 the consumers rsk/beneft belefs about botechnology. When consumers perceve benefts to themselves and socety, they are expected to have more a favorable atttude toward GM foods, relatve to consumers who perceve no beneft. On the other hand, f consumers perceve GM foods as a health rsk, and rsky to the envronment, they would possess a less favorable atttude to those foods. In ths regard, consumers rsk/beneft belefs of GM foods are expected to play a sgnfcant role n shapng ther behavor of GM foods. In analyzng consumer behavor of GM foods, however, a problem researchers confront s that U.S. consumers actual behavor of GM foods can t be fully observed. A man reason s that consumers are not provded much opportunty to reveal ther preference due to restrcted products experence from unavalablty of many GM foods and voluntary labelng polcy. Instead, researchers rely on consumers self reported behavor, or ntenton to behave. In psychology, consumers conscous decson s ntenton, and most behavoral scentsts agree that the consumers ntenton s the best predctor for ther behavor. The objectve of ths study s to explore whether or not consumers rsk/beneft belefs and knowledge about GM foods affect ther behavor as measured by wllngness to pay (WTP) a premum for GM foods wth benefts dsclosure. Lterature Revew Several studes elcted publc perceptons of botechnology. Grobe et al. (1999) studed consumer rsk percepton assocated wth recombnant Bovne growth hormone (rbgh), whch s a food-related botechnology used n mlk producton. The study ndcated dverse consumer profles across rsk percepton categores. In addton, the study showed that consumers who engaged n a self-protectve acton were strongly correlated wth envronmentalst concerns. Hoban (1999) dscovered that consumers from 2

5 dfferent areas of the world, ncludng the U.S. and France, have qute dverse perceptons and understandng toward botechnology. The study concluded that consumer perceptons about botech products vary sgnfcantly dependng on type of nformaton, government credblty, and cultural preferences. Accordng to Harrson and Han (2005), as belefs regardng potental adverse effects of GM crops on wldlfe and the envronment ncrease, the less lkely consumers are to support FDA s current labelng polcy. The study suggests that consumer belefs are sgnfcant determnants of consumer atttude toward the current labelng polcy. A number of studes have also estmated WTP for GM and non-gm food products. An ntal effort to estmate WTP for GM free product s reported n Fox et al. (1994). The study demonstrated once consumers who had a strong negatve bas aganst bst pror to the experment receved balanced scentfc explanaton of the product, about 70% of them expressed a wllngness to buy the product at zero or small dscount. Stefano and Danele (2000) showed that ncome and nformaton about botechnology are sgnfcant determnants affectng WTP for GM foods. Ther analyss ndcated that when consumers are gven correct nformaton, they are more lkely to pay hgher prces to beneft from qualty mprovements. In addton, the study suggested that consumers WTP should be dfferent dependng upon degrees of rsk type and rsk avodance. A study by Lusk et al. (2001) showed that students had more receptve of GM foods and strong wllngness to consume them. Seventy percent of students were unwllng to pay a premum for non-gm corn chps, but 20% of partcpants were wllng to pay at least $0.25/oz for non-gm corn chps. The study found that students who often consume GM corn chps have less concerns of the perceved rsk assocated wth GM foods. Moon and 3

6 Balasubramanan (2001) assumed that consumers WTP premum for non-gm foods can be nvestgated by examnng subjectve rsk and perceptons about botechnology. The study revealed that strong health rsk perceptons for both US and UK consumers ncreases the probablty to pay a premum for non-gm foods. On the other hand, as they are aware of benefts about botechnology, they are less lkely to pay a premum for non- GM foods. An mpact of nformaton of GM products on WTP s nvestgated by Tamara et al. (2003). Ther results showed that when postve-based nformaton regardng GM products s provded, WTP for GM products ncreased. The study also suggested that the effect of based nformaton on acceptablty and WTP for GM products depend upon product type. Lourero and Bugbee (2005) estmated consumers WTP for enhanced GM tomato. Ther analyss suggested that consumes pay the hghest premums for modfcaton whch ncrease the tomato flavor or enhance the nutrtonal value. The study ponted that atttudnal varables (such as feelng about GM modfcaton) play a statstcally sgnfcant role n explanng consumer acceptance and WTP for dfferent modfcatons. The present study s dfferent from prevous studes n three ways. Frst, most of the lterature has dealt wth consumer WTP for non-gm foods. The frst generaton of GM foods offers benefts prmarly for producers and the envronment. However, second generaton of GM foods provdng benefts to consumers s just around corner. To date, few quanttatve studes have examned lnkages between a consumer s rsk/beneft belefs about GM foods, wth benefts dsclosure, and WTP for those foods. Second, the study utlzes a seres of dagnostc measures to apprase nternal consstency of theoretcal concepts, such as belef, atttude, and ntenton. Thrd, contngent valuaton 4

7 method (CVM) for the study s used to elct consumers WTP a premum for GM foods. To prevent hypothetcal bas stemmng from hypothetcal nature of questons presented to respondents, two wdely used approaches for correctng them, whch are a follow-up certanty queston wth some adjustment and cheap talk, are employed. (Cummngs and Taylor,1999; Lst, 2001; Lusk, 2003; Aadland and Caplan, 2003; Champ et al., 1997; Champ and Bshop, 2001; and Poe et al., 2002). To our best knowledge, none of the studes has used both methods at the same tme. The GM product chosen for the study s beef contanng less fat and lower cholesterol compared to usual beef. Gven that beef s a staple food, t s assumed that normal consumers are famlar wth the conventonal food. A Theoretcal Framework When analyzng consumer ntentons, an mportant queston s what factors cause ntenton development. The presumpton s that belefs are key elements n formng atttudes, ntentons, and eventually nfluencng behavor. Belefs represent the base set of nformaton that a consumer has about an object or concept (Fshben and Ajzen, 1975). Thus, these belefs descrbe all thoughts that a consumer has about GM foods n assocaton wth varous attrbutes, and belefs play an mportant role n formng atttude medatng ntenton (Moon and Balasubramanan, 2004; Bredahl, 2001; and Grove and Douthtt, 1995). Accordng to Fshben s mult-attrbute model, a person s atttude toward any object s a functon of hs/her belefs about the object and the mplct evaluatve responses (or aspects) assocated wth those belefs (Fshben, 1963). Engel, Blackwell, and Kollat (1978) defned atttude as a learned predsposton to respond consstently n 5

8 a favorable manner wth respect to a gven alternatve (p.388). Thus, atttude refers to consumers favorable or unfavorable evaluaton of GM foods, and atttude formaton s closely related to consumer evaluaton of GM foods. A consumer s atttude toward GM foods, followng Fshben s theory, s a functon of the strength wth whch a consumer holds belefs (.e., hs/her subjectve probablty that GM foods are related to specfc attrbutes) and of hs/her postve or negatve evaluaton of each attrbute. The strength of belef assocated wth a gven attrbute s multpled by the consumers postve or negatve evaluaton of the attrbutes nvolved. The belef effects are then summed across all attrbutes. Algebracally, t s hypotheszed that A = N = 1 B a, where A = consumer s total atttude toward GM foods, B = the consumers belef regardng attrbute, a = the evaluatve aspect of B, and N = the number of belefs. Belefs and ther evaluatve aspects are acqured va a consumer survey. Intenton ndcatng a certan amount of affect toward an object s defned as the subjectve probablty that belefs and atttudes wll be acted upon (p.388, Engel, Blackwell, and Kollat, 1978). Whle atttude s vewed as a general predsposton that does not predspose the person to perform any specfc behavor, ntenton s related to a specfc behavor. Past studes demonstrated that consumer belefs not only have a major medatng effect n shapng ther atttude, but also belefs are nfluenced by soco-demographc characterstcs (for example, Moon and Balasubramanan, 2004; Grove, Douthtt, and Zepeda, 1999; and Ln, 1995). In addton, a few prevous studes suggest that varous soco-demographc factors nfluence nformaton acquston, consequently atttude and behavor (for example, Nayga, 1996; Florkowsk et al., 1994; and Ippolto and Mathos, 1990). Thus, based on atttude theory and prevous studes, we hypothesze that atttude s 6

9 affected by both the nformaton avalable to consumers and consumers belefs about GM foods. To accomplsh the objectves of the study, the choce process model by Engel, Blackwell, and Kollat (1978) s used as a conceptual bass for our model specfcaton. The theoretcal framework for the analyss s presented n Fgure 1. It shows a consumer s cogntve process for WTP for GM foods. A consumers WTP regardng GM foods s determned by hs/her ntenton vewed as the determnant of the behavor. Fgure 1 depcts a basc framework for how consumers WTP a premum for GM foods s affected by varous types of nformaton, whch have a drect effect on consumer atttude Fgure1. A theoretcal model of explanng wllngness to pay a premum for GM foods. BELIEFS Health and Envronment Benefts of GM Foods Health and Envronment Rsks of GM Foods INFORMATION Subjetve Knowledge Objectve Knowledge Consumer Characterstcs for Food Consumpton Trust toward GM Insttutons Soco- demographcs ATTITUDE General predsposton of GM Foods Normatve Complance Moralty INTENTION Wllngness to buy GM Foods Wllngness to Pay a Premum for GM Foods wth Beneft Dsclosure Adapted from Engel et al., 1978 and an ndrect effect va the belef system. In addton, Fgure 1 shows a recursve (or sequental) lnkage between belefs, atttudes, and ntenton. Belefs comprse 2 factors, benefts and rsks perceptons of GM foods regardng the health and envronment. For atttude toward GM foods, consumers general predsposton wth respect to them s 7

10 explored. Consumers perceved moralty about GM foods reveals personal norms. It s assumed that perceved moralty drectly nfluences consumer ntenton to pay a premum for GM foods. Fnally, a consumer s WTP a premum for GM foods s hypotheszed to be a functon of atttude. Emprcal model It s assumed n the study that there are two reasons for a large number of zero values on WTP a premum for GM foods: ) consumers are not wllng to pay a premum for GM foods (nonpartcpaton n the market); and ) consumers do not pay a premum for GM foods at current ncome level (corner soluton). Tobt model developed by Tobn (1958) assumes that zero observaton s attrbutable to only economc factors, such as prces and ncome levels (corner soluton) (Jensen, 1995; and Newman, 2003). In addton, tobt model supposes that the decson to partcpate n the market s the same as the decson about the amount of the premum to pay. Ths mples that any varable that ncreases the probablty of nonzero value must also ncrease the condtonal mean of the postve values. Ths strong restrcton may not be approprate for WTP a premum for GM beef. Double hurdle model developed by Cragg (1971) allows the varables to affect the partcpaton and the quanttatve premum decsons separately. Double-hurdle model generalzes the tobt model n that even though consumers may have postve recepton toward GM foods wth drect benefts, mpedments to pay a premum for those foods, due to foods safety and envronmental concerns as well as budget constrant, may prohbt WTP a premum. Ths recognton leads to the modelng of consumer behavor n two stages: ) frst, based on hndrances to buy GM foods and pay a premum, consumers 8

11 decde whether or not to buy GM foods and pay a premum for GM beef; and ) second, accordng to the ntensty of the desre for the GM foods, the consumers decde on how much to pay a premum for GM beef. As economc theory provdes lttle gudance as to whch varable should appear n the frst and second hurdle, the approach followed has been to nclude the same set of varables n both decsons. The double hurdle model s specfed as follows: (1) where d y y y * ' = z q + η ' = x b + ε = y * f = 0 f d d > 0 0 * y represents the optmal premum level of th consumer for GM beef, and t can be nterpreted as the soluton to a utlty maxmzaton problem. * y, can take on negatve values, but values of * y less than zero are unobserved. y s the th consumer s observed premum for GM beef that he/she s wllng to pay, and y s censored at zero. d represents the decson (partcpaton) of whether to buy GM foods and pay a premum. It s assumed that only the sgn of only when d as a latent ndcator s observed, and * y s observed d s postve. z s vectors of explanatory varables n decson stage. The error terms, η and ε, are ndependently and normally dstrbuted wth zero means and 2 constant varances (1, σ ). * y, n terms of wllngness to buy GM foods, s rated on 5- pont Lkert scales, strongly dsagree-strongly agree scale. We formed a summated ratng scale, by summng respondents scores on 5 tems, and obtaned average score rangng from a low of 1 to a hgh of 5. To make sure f respondents tend to take smlar poston on the other tems, the data value of a varable wth negatve drecton s reversed (.g. go 9

12 from negatve to postve). Then, agree and strongly agree responses are treated as yes to wllng to buy GM foods. x s a vector of explanatory varables ncludng nformaton, belefs, atttude, and normatve complance explaned n the theoretcal model. It s assumed that latent constructs, such as nformaton, belefs, atttude, normatve complance, and ntenton, are not observable and drectly measured. Instead, these latent varables can be observed va other drect observable proxy ndcators. To measure each latent varable, multple ndcators that measure the same concept nto a sngle varable are summated, and the average score of the varables s used as a replacement varable. Ths summated scale provdes a specfc advantage. It offers a means of overcomng to some extent the measurement error n the estmaton process occurrng from abstract or theoretcal concepts, thus ncreases the relablty (Har et al., 1998). Because the construct relablty s a closer approxmaton of relablty, t s preferred over Chronbach s alpha. If construct relablty value s hgher than 0.6, t means that construct relablty s good wth hgh nternal consstency (Fornell and Booksten, 1982). Most of mult-tem scales demonstrate a relatvely hgh degree of the nternal consstences rangng from 0.75 to In the tobt model, the varables ( x ) and parameters (b) descrbes the decson of whether to buy a GM foods and pay a premum, and of how much to pay. In the double hurdle model dfferent sets of varables ( z, x ) and parameters (q,b) explan the two decsons. 10

13 The log lkelhood functon for an equaton (1) s (2) ln L = y > 0 + y > 0 1 [log( 2 2π) + log σ ' (y xb) + 2 σ xb (log Φ( zq) log Φ( )) σ 2 2 ] + y = 0 ln(1 Φ( z q)) Specfcaton test employng a lkelhood rato statstc for the tobt model and the double hurdle model s performed to decde whch model s more consstent wth the fundamental consumer behavor for GM beef. Data and Questonnare The data analyzed n ths study were collected n a random, natonal, mal survey of 3,999 households conducted n July Each of the 3,999 people was maled a survey package. The packet wth a postage-pad return envelope ncludes a letter whch brefly explans the purpose of the survey, encourages ther partcpaton, and provdes background nformaton about the genetc modfcaton. A remnder letter and a followup questonnare were sent to non-respondents three weeks after the ntal malngs. A representatve sample s always concerns to a researcher. Thus, to truly represent current U.S. populaton dstrbuton, the sample was stratfed by four geographc regons accordng to the U.S. census bureau n 2000.; Northeast, Mdwest, South, and West, The number of questonnare sent to each regon s as follows; Northeast 799 (19.0%), Mdwest 920 (22.9%), South 1,400 (35.6%), and West 880 (22.5%). Of the 3,999 survey maled, 490 were returned, yeldng overall response rate of 12.3%. After dscardng the ncomplete or otherwse unusable surveys, there were 393 usable responses for a response rate of about 10%. The wllngness to pay a premum was 11

14 elcted wth an open-ended queston as part of a mal survey. The study used 80% as cutoff certanty values. Results The profles of respondents based on the survey results are presented n the table 1. As shown n the table 1, our sample has lower percentage of females and s relatvely older. The sgnfcant dfference between the sample and U.S. census s the level of educaton attaned, whch s not unusual for a mal survey. However, t seems that U.S. populaton s decently represented by the survey sample. In addton, summary statstcs and data descrpton are provded n the table 2. The ndependent varables ncluded subjectve and objectve knowledge of GM foods, trust on GM nsttutons, rsk/beneft perceptons, and etc. Table 3 presents the results for the tobt and the double hurdle model for GM beef contanng less fat and lower cholesterol. The tobt results appear n the frst column, the probt results for the yes/no wllngness to buy and WTP appear n the second column, and the truncated normal estmatons for the nonzero payng premum decsons are n the thrd column. The second and thrd columns represent the alternate two-step WTP decson process. In the tobt model, both the decson of whether to be wllng to buy GM foods and to be wllng to pay a premum, and how much to pay a premum are captured n the b parameters. On the other hand, n the double hurdle model the partcpaton n the market s emboded n q, and b embodes the second decson of how much to pay a premum. The frst test was whether to accept the null hypothess that q=b/σ. As the tobt model s nested regardng the double hurdle model, the null hypothess can be used to test the tobt specfcaton aganst double hurdle. If the restrcton s vald and t s not 12

15 mposed, the estmates are neffcent but the results are stll statstcally correct. If the restrcton s not vald and tobt s used, parameter estmates are ncorrect and nferences can be msleadng (Hanes et al., 1988). If the null hypothess s accepted, the tobt specal case s accepted and tobt estmaton can be used to nvestgate quantty premum for GM beef. The null hypothess s tested usng a lkelhood rato statstc, λ = 2[ln L Tobt (ln LProbt + ln LTruncated)]. The null hypothess s rejected at the 0.05 level ( χ 2 df = 22 s 33.92) for GM beef. That s, the decson to buy GM foods and pay a premum for GM beef, and the quantty premum decson are based on the dfferent decsonmakng structure for GM beef. Therefore, gven the results from the lkelhood rato test, the remanng dscusson of the study focuses on the estmated coeffcents from the double hurdle model for GM beef. Usng estmated parameters from the double hurdle model for GM beef, mean WTP s calculated. Mean WTP for GM beef s 15.86%, whch suggests that consumers are aware of substantal benefts from GM beef. That s, consumers havng more nterest n heath are more lkely to pay a hgh premum for GM beef. The results of the double hurdle estmaton for GM beef are dsplayed n the table 3. It s assumed that whle consumers subjectve knowledge of GM foods s based on ther perceptons, or belefs, objectve knowledge s found on ther correct nformaton on t. Thus, dfferent nfluences of knowledge varables are expected, and t s hypotheszed that consumers subjectve knowledge has more strong mpact on WTP than objectve knowledge. In addton, t s hypotheszed that as respondents have more proper nformaton about GM foods, they feel more postve, thereby are more lkely to pay a premum. However, the results n table 3 show no sgnfcant mpact on t. It s found that 13

16 benefts of GM foods to the health and envronment have a sgnfcantly postve mpact on the market partcpaton, but no sgnfcant effects on premum level. As expected, f consumers have a postve atttude about GM foods, the probablty of ther partcpatng n the market and payng a premum ncreases. However, surprsngly, the rsk varable and moralty turned out to be nsgnfcant. In general, t s beleved that U.S. consumers have lttle knowledge about GM foods. For example, our survey results ndcate that only 13% of respondents gve correct answers to fve questons. Thus, to deal wth lack of knowledge, consumers are more lkely to rely on GM nsttutons that provde nformaton about GM foods. Accordngly, t s hypotheszed that as consumers have a hgh degree of trust on GM nsttutons, they are more lkely to partcpate n the market. The results suggest that trust toward GM nsttutons has a strong nfluence on decson of whether to buy GM foods and to pay a premum for GM beefs, but the premum level pad s nsgnfcantly and nversely related to trust. The results also ndcate that consumers market partcpaton s postvely assocated wth frequency of purchasng organc foods. Whle consumers n South relatve to Mdwest are more lkely to decde to partcpate n the market, consumers resdng n Northeast and West tend to pay a hgher premum sgnfcantly on GM beef than do consumers located n Mdwest. It s assumed that consumers who resde n urban area have a greater exposure to nformaton and meda concernng for GM foods compared to non-urban consumers. Thus, t s hypotheszed that the partcpaton n the market s postvely nfluenced by the urbanzaton. The results show that the consumers n urban area are less lkely to partcpate n the market, but they pay a greater premum once they decde to partcpate 14

17 n the market. Consumer groups between age 18 and 34 are less lkely to purchase GM foods and to pay a premum for GM beef, and apt to pay a lower premum. In addton, consumer group less than ncome $24,999 have a tendency to pay a premum at hgher percentage once they are n the market. The table 3 presents that the tobt model tends to pck up more of yes/no decson, and ts nablty to explan the quanttatve premum to pay. Another mportant fndng s that the tobt model understates the mpact of explanatory varables on a premum level pad. For example, the level of premum payng consumers n Northeast and urban s about 4.5 tmes and 18tmes the level estmated by the tobt model n absolute value, respectvely. In addton, t s found that several estmated parameters n the premum percentage of the double hurdle have dfferent sgns wth those from the tobt model. These conflctng results may be caused by the nvald restrcton of the tobt model that the decson to partcpate n the market s the same as the decson about how much to pay a premum. Thus, f the restrcton of the tobt model for GM beef s mposed, ths would produce based estmates, as well as mss the true behavoral patterns, eventually resultng n ncorrect conclusons. Conclusons Ths study conducted a natonal survey to nvestgate the effects of consumers rsk/beneft belefs on the level of a premum for GM beef wth less fat and lower cholesterol. To prevent the overestmaton problem n CVM, cheap talk and certanty scale methods are used together. In addton, for the nternal relablty of a scale, multple tems for each theoretcal concept are composed of. One bg contrbuton of the present study s that all of the perceved benefts and rsks of GM foods currently debated 15

18 n the market place are employed n ths survey applyng for natonal consumers for analyss. The ch-squared specfcaton test ndcates that the double hurdle model s a superor ft for GM beef. Rejecton of the tobt model for GM beef suggests that the decson to buy GM foods and to pay a premum for GM beef s separate from the premum level decson. The results provde a possble nterpretaton that zero premums of GM beef may be occurred not only corner soluton but also due to the health and envronmental concerns and moralty because consumer beleve that gene transfer of GM anmal s more radcal than GM plants. Consumers decson on partcpatng n the market and the level of a premum pad were hypotheszed to be related to ther belefs toward GM foods. The study found that the qualtatve factors, such as benefts of GM foods on the health and envronment, trust on GM nsttutons, and postve evaluaton of GM foods, are sgnfcant, postve nfluence on the wllngness to buy GM foods and to pay a premum. However, unexpectedly, the results show that rsks of GM food and moralty have expected sgns but nsgnfcant mpact on the partcpaton n the market, and nsgnfcant mpact on a level of premum pad for GM beef. A reasonable explanaton of these results s that to some extent benefcal attrbutes of GM foods could mtgate consumers rsk perceptons (Moon and Balasubramanan, 2003; and Bech-Larsen and Grunert, 2000). Interestngly, consumes lvng n Northeast regon tend to pay a hgher premum for GM beef. Ths suggests that consumers resdng n Northeast have dfferent nformaton source and dfferent lfestyle, and they have more concerns about food nutrton. Soco-demographc characterstcs and regonal and locatonal dfferences are 16

19 ncluded to examne the sgnfcance of ther effects on the levels of a premum for GM beef. However, the study shows that many of soco-demographc varables are not statstcally sgnfcant, whch s consstent wth a prevous study (Baker and Burnham, 2001; and Huffman et al., 2003). A lmtaton of the present study s that most respondents have ether some college, or hgher level of educaton. Less educated consumers may show dfferent decsons on partcpaton n the market and premum percentage pad for GM foods relatve to the hghest educated consumers. In addton, low response rate due to complexty of questonnare may lead to nonresponse bas. For example, consumers respondng to the survey are more lkely to be nterested n GM foods relatve to nonrespondents, and thus more senstve to the rsks and benefts of GM foods relatve to the general populaton. Ths may lead to an upward bas n the estmates of consumer ntenton toward decson on the partcpaton n the market and premum percentage they pay. 17

20 References Aadland, D., and A. J. Caplan. Wllngness to Pay for Curbsde Recyclng wth Detecton and Mtgaton of Hypothetcal Bas. Amercan Journal of Agrcultural Economcs, 85(2) (May 2003): Baker, Gregory A. and Thomas A. Burnham. Consumer Response to Genetcally Modfed Foods: Market Segment Analyss and Implcatons for Producers and Polcy Makers. Journal of Agrcultural and Resource Economcs 26(2) (2001): Bech-Larsen, T. and K. G. Grunert. Can Health Benefts Break Down Nordc Consumers Rejecton of Genetcally Modfed Food?: A Conjont Study of Dansh, Norwegan, Swedsh and Fnnsh Consumer Preferences for Hard Cheeze. ANZMAC 2000 Vsonary Marketng for the 21st Century: Facng the Challenge. Bredahl, Lone. Determnants of Consumer Atttudes and Purchase Intentons wth Regard to Genetcally Modfed Foods: Results of a Cross-Natonal Survey. Journal of Consumer Polcy, 24(2001): Champ, P. A. and R. C. Bshop. Donaton Payment Mechansms and Contngent Valuaton: An Emprcal Study of Hypothetcal Bas. Envronmental and Resource Economcs, 19 (2001): Champ, P.A., R. C. Bshop, T. C. Brown, and D. W. McCollum. Usng Donaton Mechansms to Value Nonuse Benefts from Publc Goods. Journal of Envronmental Economcs and Management, 33 (1997):

21 Cragg, John G. Some Statstcal Models for Lmted Dependent Varables wth Applcaton to the Demand for Durable Good. Econometrca, v39 (5) (September, 1971): Cummngs, Ronald G. and Laura O. Taylor. Unbased Value Estmates for Envronmental Goods: A Cheap Talk Desgn for the Contngent Valuaton Method. The Amercan Economc Revew, June 1999: Engel, Jame F., Roger D. Blackwell, and Davd T. Kollat. Consumer Behavor. The Dryden Press, 3 rd, Fshben, Martn and Icek Ajzen. Belef, Atttude, Intenton, and Behavor: An Introducton to Theory and Research. Addson-Wesley, Fshben, Martn. An Investgaton of the Relatonshp between Belefs about an Object and the Atttude toward That Object. Human Relatons, 16(1963): Florkowsk, Wojcech, Catherne Halbrendt, Chung L. Huang, and Lesa Sterlng. Socoeconomc Determnants of Atttude toward Boengneered Products. Revew of Agrcultural Economcs, 16(1994): Fornell, C. and F.L. Booksten. Two structural equaton models: LISREL and PLS Appled to Consumer Ext-Voce Theory, Journal of Marketng Research, 19(4) (1982): Fox, John A., Dermot J. Hayes, James B. Klebensten, and Jason F. Shogren. Consumer Acceptablty of Mlk from Cows Treated wth Bovne Somatotropn. Journal of Dary Scence 77(1994):

22 Grobe, Deana., Robn Douthtt, and L. Zepeda. Consumer Rsk Percepton Profles Regardng Recombnant Bovne Growth Hormone (rbgh). The Journal of Consumer Affars, 33(2) (1999): Grove, Deana and Robn Douthtt. Consumer Acceptance of Recombnant Bovne Growth Hormone: Interplay between Belefs and Perceved Rsks. The journal of Consumer Affars, v29(1) (1995): Hanes, Pamela S., Davd K. Gulkey, and Barry M. Popkn. Modelng Food Consumpton Decsons as a Two-Step Process. Amercan Journal of Agrcultural Economcs, 70(3) (August 1988): Har, Jr. Joseph F., Rolph E. Anderson, Ronald L. Tatham, Wllam C.Black. Multvarate Data Analyss. 5 th edton, Prentce-Hall, Inc. Upper Saddle Rver, Harrson, R Wes and J.H. Han. The Effects of Urban Consumer Perceptons on Atttudes for Labelng of Genetcally Modfed Foods. Journal of Food Dstrbuton Research 36(2) (2005): Hoban, T.j. Publc Perceptons and Understandng of Agrcultural Botechnology. North Carolna State Unversty, Ralegh, NC(1999). Huffman, Wallace E., Jason F. Shogren, Matthew Rousu, and Abe Tegene. Consumer Wllngness to Pay for Genetcally Modfed Food Labels n a Market wth Dverse Informaton: Evdence from Expermental Auctons. Journal of Agrcultural and Resource Economcs, 28(3) (2003): Ippolto, P. M., and A. D. Mathos. Informaton, Advertsng and Health Choces: A Study of the Cereal Market. The Rand Journal of Economcs, 21(1990):

23 Jensen, Km. Flud Mlk Purchase Patterns n the South: Effects of Use of Nutrton Informaton and Household Characterstc. Journal of Agrcultural and Appled Economcs, 27(2), (December 1995): Ln, C.T.J. Demographc and Socoeconomc Influence on the Importance of Food Safety n Food Shoppng. Agrcultural and Resource Economcs Revew 24(2) October 1995): Lst, John. A. Do Explct Warnngs Elmnate the Hypothetcal Bas n Elctaton Procedure? Evdence from Feld Auctons for Sportscards. The Amercan Economc Revew, December 2001: Lourero, Mara L. and Marca Bugbee. Enhanced GM Foods: Are Consumer Ready to Pay for the Potental Benefts of Botechnology? The Journal of Consumer Affars, v39(1) (2005): Lusk, J. L., M. S. Danel, D. L. Mark, and C. L. Lusk. Alternatve Calbraton and Aucton Insttutons for Predctng Consumer Wllngness to Pay for Nongenetcally Modfed Corn Chps. Journal of Agrcultural and Resource Economcs 26(1) (2001): Lusk, Jason L. Effects of Cheap Talk on Consumer Wllngness To-Pay for Golden Rce. Amercan Journal of Agrcultural Economcs, 85(4) (November 2003): Moon, Wank and Sva K. Balasubramanan. Publc Atttudes toward Agrobotechnology: The Medatng Role of Rsk Perceptons on the Impact of Trust, Awareness, and Outrage. Revew of Agrcultural Economcs, v26(2) (2004):

24 . Wllngness to Pay for Non-Botech Foods n the U.S. and U.K. The Journal of Consumer Affars, v37(2) (2003): Publc Perceptons and Wllngness-to-Pay a Premum for Non-GM Foods n the US and UK. AgBoForum 4 (3&4),(2001): Nayga, Rodolfo M. Socodemographc Influences on Consumer Concern for Food Safety: The Case of Irradaton, Antbotcs, Hormones, and Pestcdes. Revew of Agrcultural Economcs, 18(1996): Newman, Carol, Maeve Henchon, and Alan Matthews. A Double-Hurdle Model of Irsh Household Expendture on Prepared Meals. Appled Economcs, 35(2003): Poe, G.L., J. E. Clark, D. Rondeau, and W. D. Schulze. Provson Pont Mechansms and Feld Valdty Tests of Contngent Valuaton. Envronmental and Resource Economcs, 23(1) (2002): Stefano Boccalett and Danele Moro. Consumer Wllngness-to-Pay for GM Food Products n Italy. AgBoForum, 3(4), (2000): Tamara Van Wechel, Cheryl J. Wachenhem, Erc Schuck, and Davd K. Lambert. Consumer Valuaton of Genetcally Modfed Foods and the Effect of Informaton Bas. Agrbusness and Appled Economcs Report No.513, North Dakota State Unversty, May Tobn, James. Estmaton of Relatonshp for Lmted Dependent Varables. Econometrca, 26(1958): U.S. Census Bureau, Statstcal Abstract of the Unted States:

25 Table1. Stratfcaton Categores and Descrptve Statstcs of Sample and U.S. Populaton a Characterstc Sample Number Sample (%) U.S. Census (%) Gender Male Female Age(years) or older Income Under $15, $15,000 - $24, $25,000 - $34, $35,000 - $49, $50,000 - $74, $75,000 - $99, $100,000 and over Race Whte Non-Whte Martal Status Marred Sngle Educaton Less than hgh school Hgh school (or equvalency) Techncal or some college Assocate degree Bachelor degree Advanced degree Lvng Area Rural area Urban area b Regons Northeast Mdwest South West a Data n the fourth column obtaned from the Statstcal Abstract of the Unted States (U.S. Census Bureau: 2000 and 2003). b Included suburban area.

26 Table 2. Summary Statstcs and Varable Defntons Varable Descrpton Mean Std. Dev. Sub_Knowledge a Subjectve knowledge of GM foods Obj_Knowledge b Objectve knowledge of GM foods Benefts c Benefts of GM foods on the health and envronment Rsks d Rsks of GM foods on the health and envronment Moralty e Moralty ssue of GM foods Acceptance f General predsposton of GM foods Trust g Trust on GM nsttutons Food_Label Frequency of readng food label (1=never, 5=all of the tme) Org_Food Frequency of purchasng organc foods (1=never, 5=all of the tme) Northeast Northeast (1= f resdence s n the Northeast; 0 otherwse) South South (1= f resdence s n the South; 0 otherwse) West West (1= f resdence s n the West; 0 otherwse) Rural Rural (1= f resdence s n the rural area; 0 otherwse) Urban Urban (1= f resdence s n the urban area; 0 otherwse) Gender Gender (1= male) Marred Marred (1= marred; 0 otherwse) Age18_34 1= age group between 18 and 34; 0 otherwse Age35_59 1= age group between 35 and 59; 0 otherwse Whte 1= whte; 0 otherwse More_College 1= more than college; 0 otherwse Inc_less $24,999 1= ncome group less than $24,999; 0 otherwse Inc_more $75,000 1= ncome group more than $75,000; 0 otherwse a Subjectve knowledge of GM s measured by consumer s self reportng. Respondents are asked how knowledgeable they are about GM foods on 1 through 10 scales. b Objectve knowledge of GM s rated on fve true-false tems. The fve tems are added together to create an objectve knowledge scale whch ranges from 0 to 5, where 0 represents a respondent who does not answer any of fve questons correctly, and 5 represents a respondent who answers all fve questons correctly. Don t know responses are coded as wrong responses. cd Benefts and rsks assocated wth GM foods consst of 5 tems on the health and 5 tems on the envronment. The tems are assessed on 5-pont Lkert scales, strongly dsagree-strongly agree scale. Then, we formed a summated ratng scale, by summng respondents scores on all 10 tems, and obtaned average score rangng from a low of 1 to a hgh of 5. ef Respondents were asked to rate on a scale of 1 to 5 (wth 1 correspondng to strongly dsagree and 5 correspondng to strongly agree) ther level of moralty and acceptance of GM foods wth 5 tems, respectvely. In calculatng the ndex, the responses to the frst and thrd queston n acceptance of GM foods were nverted so that a low number corresponded to less acceptance of those foods and a hgh number corresponded to more acceptance, to be consstent wth other tems. The answers to all fve tems were then summed and averaged for each respondent to generate the moralty and acceptance varables. g Trust on GM nsttutons s measured on 5 scales, where 1 ndcates no trust at all and 5 represents a very hgh degree of trust, rangng from 1 to 5.

27 Table 3. Estmated Tobt and Double Hurdle Model of GM Beef wth Beneft Dsclosure Tobt Probt Truncated Margnal Probs. Coeffcent Margnal Probs. Coeffcent (Std. Err.) (Std. Err.) (Std. Err.) (Std. Err.) Varable Coeffcent (Std. Err.) Margnal Probs. (Std. Err.) Constant (63.505) (2.033) ( ) Sub_Knowledge (1.957) (0.247) (0.064) (0.006) (3.986) (1.191) Obj_Knowledge (2.833) (0.371) (0.098) (0.009) (6.364) (1.942) Benefts (8.958)** (1.154)** 0.501(0.293)* (0.028) (18.101) (5.545) Rsks (7.952) (1.048) (0.275) (0.025) (16.150) (4.880) Moralty (7.780)* (0.963) (0.234) (0.020) (26.879) (8.112) Acceptance (8.831)*** (1.099) *** (0.287)*** (0.033)*** (21.235)* (5.659)* Trust (6.300)** (0.791)** (0.208)** (0.019)** ( ) (5.065) Food_Label (4.051) (0.528) (0.143) (0.013) (11.714) (3.483) Org_Food (5.452)* (0.703)* (0.191)*** (0.020)** (10.343) (3.164) Northeast (11.692) (1.836) ( 0.380) (0.064) (37.959)** (28.169) South (9.280)* (1.346)* (0.306)** (0.044) (24.483) (7.425) West (10.433) 1.461(1.516) (0.343) (0.040) (27.100)** ( )* Rural (8.414) (1.083) (0.278) (0.023) (19.285) (7.296) Urban (9.018) (1.148) (0.298) (0.025) (25.375)** (12.478)* Gender (8.056) (1.069) (0.259) (0.025) ( ) (10.279) Marred (7.700)* (1.079) (0.260) (0.029) (18.325) (6.189) Age18_ (14.807)* (1.386)** (0.477)* (0.019)** (47.142) (4.767)** Age35_ (7.634) (1.020) (0.261) (0.026) (16.250) (4.593) Whte (11.346) (1.690) (0.380) (0.041) (32.092) (7.816) More_College (11.643) (1.517) (0.391) (0.041) ( ) (6.424) Inc_less $24, (12.047) (1.572) (0.453) (0.021)** (38.608)*** (27.922)*** Inc_more $75, (7.701) (0.978) (0.253) (0.022) (21.522) ) (6.239) sgma (3.673)*** (4.826)*** *,**,***, ndcates estmated coeffcent s sgnfcant at the 0.10, 0.05, and 0.01 level, respectvely. Log-L for Probt= , Log-L for Truncated = , and Log-L for Tobt =