Probit regression: Potatoes - bet 3

Results
Part A of table 2 shows the mean bid prices for all participants. Consumers, on average, discounted GM-labeled foods by fourteen percent. Part B shows that participants who received only positive information actually put a premium on the GM-labeled food for two of the three products. This was despite the fact that the genetic modification was only used to enhance the production process, and did not give the foods any enhanced attributes. Part C shows that when consumers received only negative information, they discount the GM-labeled foods by an average of approximately thirty-five percent. Part D shows that consumers who received both positive and negative information discount the GM-labeled foods by an average of seventeen to twenty-nine percent, depending on the food product.
Third-party information has an impact on the willingness to pay for GM-labeled foods. Part E shows that consumers who received positive and third-party information discounted GM-labeled foods slightly. This is in contrast to the consumers who received only positive information who valued the GM-labeled foods more than their plain-labeled counterpart on average. Part F shows that participants who received negative and third-party information still discounted the GM-labeled foods, but by a smaller amount than the participants who received only negative information. Part G shows that participants who received negative and third-party information discounted the GM-labeled foods by an average of seventeen to twenty-two percent, depending on the product. Participants who received positive, negative and third-party information were more accepting of the GM-labeled foods than those who received only positive and negative information. The participants who received positive, negative and third-party information discounted the GM-labeled food by an average of zero to eleven percent, depending on the product.
Our results are consistent with Viscusi (1997) who found that individuals placed a slightly greater weight on negative information than positive information. In our auction, participants who received only positive information did not discount the GM-labeled food, while those who received only negative information discounted the GM-labeled food by an average of 35 percent. Those who received both positive and negative information put slightly more weight on the negative information, discounting the GM-labeled foods by 20 percent. In addition, one explanation for a moderated negative auction outcome in our experiments where participants received positive and negative GM-product information is that some individuals have an asymmetric value function giving greater weight to marginal losses than to marginal gains (Kahneman and Tvesrky 1979), for example, they do not want to bear losses.
Also, our results are in contrast to Fox et al.’s (2001) who obtained the result that negative information dominated positive information. They argued that one reason could be due to a “status quo bias,” (or endowment effect) where participants were originally endowed with a regular pork sandwich and could bid to upgrade to an irradiated pork sandwich. Participants may have their bids biased due to being endowed with one type of sandwich.ix Our auction had participants bid on items in separate rounds (trials), thus our results are not influenced by a “status quo bias.”
Tables 3 and 4 show the percentage of participants who are out of the market for the GM-labeled commodities using both the strong and weak test. The number of observations differs, because if an individual bids zero for both the GM-labeled and plain-labeled versions of a commodity, they are not included in the analysis (they did not demand the product, so we cannot determine their taste for genetic modification). Similarly, when reporting on who is out of the market for all GM-labeled foods, those who bid zero for all the food products are not included.
A summary of 8 sets of probit results explaining the probability of a participant being out of the market for GM-labeled foods is presented in table 5, and the actual estimates of the coefficients in the probit models are reported in Appendix table 2 to 9 Several different specifications were used, to examine the robustness of the results. Negative information has a positive coefficient, indicating negative information increases the probability that a consumer is out of the market. The coefficients for these effects were consistently statistically significant, for all of the products under both the strong test and weak tests.
This result has important implications. If an anti-technology group wishes to slow scientific progress and asymmetric information exists, they could disseminate large amounts of negative information – even if the information is highly biased. They could even disguise their true intentions by telling consumers they want to keep everybody “fully informed” of the consequences of a product or technology. Yet, their negative information might help push demand down to zero for enough people that suppliers would not find it profitable to invest in the new technology. Also, even if firms do not fully believe the information, negative information will increase the uncertainty about genetic modification, which has been shown to decrease the likelihood of adoption (Purvis et al. 1995). Given that technological change is one of the driving forces behind the rising standard of living enjoyed in many developed countries, stalled progress could decrease welfare significantly over time.
This result also presents an alternative explanation for why Europeans demand for GM foods is so small. Many have hypothesized that Europeans dislike GM foods because of recent food scares like BSE, dioxin, and foot and mouth disease. Our results present an alternative explanation for the low Europeans demand for GM-labeled foods – environmental groups are more prevalent and have disseminated larger volumes of negative information about GM-technology and GM-foods and they do not have a trusted source of verifiable information.
Table 5 also shows that third party, verifiable information decreases the probability that an individual is out of the market, as these coefficients are negative under all of the model specifications, and are statistically significant at the 5 and 10 percent level in many of the models. This provides evidence that a third-party source that provides neutral, verifiable information on genetically modified foods could help prevent the market from disappearing due to lack of demand. Hence, in addition to value that verifiable information may have by providing consumers accurate information on the risks and benefits of genetic modification (estimated in Rousu et al. at $2.6 billion), verifiable information also may have value by keeping new GM food products in supermarkets, increasing the range of choices, which has a real option value.
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